DEV Community: Chris Sean 🪐

The Ugly Truth About Postgres & pgvector

Chris Sean 🪐 — Mon, 22 Sep 2025 21:04:17 +0000

The Single-Box Tax: Why My Friend Was Sketching Shards at Olive Garden

True story: I’m at dinner with a friend. Halfway through his pasta, he tells me about a “simple” weekend project where he'd make search feel smarter. Keep Postgres because he knows it well, add pgvector for embeddings, ship by Monday. Clean plan. Familiar tools.

It works… for about two days.

By Wednesday the loading spinner is basically the main character. Support screenshots all look the same. He tweaks settings, rents a bigger box, pushes a few jobs to a side worker. Things calm down, then spike again. At some point he pulls out a pen and starts sketching a sharding plan on the Olive Garden napkin. We laugh, because nobody wants to do shard math between breadsticks.

Here’s the important part: his plan wasn’t wrong. Postgres on a single machine is a tank, and pgvector is solid. The problem was the shape of the workload. Like regular relational rows plus embeddings, bursty writes, spiky reads. Vector indexes are wide. Autovacuum and checkpoints compete with live traffic. You get bloat, WAL pressure, and stalls right when usage spikes. Read replicas buy headroom but introduce staleness. Then come upgrade windows, “vacuum sprints,” hand-sharding, and reviews waiting on fresh data. That operational drag is the single-box tax.

The What-If Thought Experiment

I work at TiDB, so I played a game with him: keep the same app and queries, but change the foundation.

What if storage split itself into ranges, kept three copies via consensus, and moved hot ranges off busy nodes automatically? What if the SQL layer were stateless so you could add capacity during a spike and scale it back down after? What if your vector embeddings lived in the same database as your business data and ANN indexes you configure once, a distance metric you choose up front, and a planner that can mix similarity search with normal filters? No sidecar, no ceremony, no napkin shard plan.

That’s the core idea behind TiDB Cloud.

How TiDB Handles This

Requests land on a stateless SQL layer, which you can scale up or down. Data lives in a replicated key-value store for durability. When load shifts, hot ranges split and move so a single key doesn’t become a hotspot. Analytical replicas use a columnar layout for fast scans but read the same snapshot as transactional queries, so OLTP and analytics agree on the truth. Transactions give you snapshot reads and isolation that reduce the “is the replica caught up?” moments. When the graph gets bumpy on a random Wednesday, you change topology instead of firefighting at midnight.

When Postgres & pgvector Is Absolutely the Right Call

There’s a sweet spot where Postgres + pgvector shines:

Your data fits comfortably in memory.
Traffic is predictable.
Your team knows Postgres inside out.
Index maintenance isn’t a weekly chore.

In that world, keep the simplest thing that works. Reach for a distributed system when the coordination tax shows up.. like when autovacuum falls behind after a heavy write day, replica lag becomes user-visible, or product plans start bending around database limits.

Why TiDB Then?

Because the big win isn’t only performance, it’s how failures behave and how you spend your time. No more extension-upgrade calendars. No more choosing between fresh reads and safe reads. No more late-night shard rebalance. The conversation shifts from “how do we hide the spikes?” to “how often does the tail cross the line where users notice?” Observability gets intentionally boring: keep an eye on slow queries and traffic spikes; let the system carry shard placement, replica lag, and failover.

Boring ops = more time for useful features.

When Not to Use TiDB

There are clear cases where TiDB isn’t the right fit:

Batch-first workloads where staleness never blocks users (nightly warehouse jobs are fine).
Apps that lean on Postgres-specific features you cannot or don’t want to replace.
Teams that value a fixed monthly bill over elasticity for policy or budgeting reasons.

Don’t move because it’s new. Move when the old plan starts charging interest in nights and weekends.

Is Distributed More Complicated?

Sometimes, sure. But the complexity you carry as a human can get smaller. You stop carrying extension lifecycles in your head. You stop carrying shard placement. You stop carrying replica lag. Those become system concerns. Your levers feel like product levers, not plumbing.

If my friend had started his week on TiDB Cloud instead of a single Postgres box with pgvector, the ideal week would look like this: Monday ships and stays shipped. Wednesday night doesn’t page anyone. Friday’s review uses this morning’s data, not last night’s dump. The sprint ends with a feature, not a new runbook.

Closing Thoughts

My friend’s “weekend project” wasn’t naive; it was normal. We all start with the tools we know, and we level up when reality asks us to. If you’re paying the single-box tax vacuum sprints, hand-sharding, replica-lag debates consider flipping the foundation, not the feature list.

If you want to try it, TiDB Cloud’s Starter plan includes 5 free GB's. More important than the free tier, though, is whether your Wednesday graph gets quieter. If it does, keep your napkins for marinara, not shard math.

Build a Semantic Search-Powered FAQ Assistant with TiDB and AWS Bedrock

Chris Sean 🪐 — Thu, 19 Jun 2025 21:46:05 +0000

Semantic search is rapidly transforming how apps deliver relevant content to users. Think of chatbots that can really understand your questions, or help centers that can instantly find the answer you meant rather than the exact words you typed. But many semantic search examples use overly complex architectures (i.e., multiple microservices, sprawling pipelines, labyrinthine config). To cut through the noise, I’ve bundled a lean, end-to-end demo you can clone from my GitHub repository and spin up in minutes. By the end of this tutorial, you'll have a CLI that ingests FAQs and a React & FastAPI web UI for a more interactive demo.

In this tutorial, you'll configure TiDB Cloud's serverless vector columns with AWS Bedrock's Titan-V2 embeddings, set up your .env, and build a CLI that ingests FAQs, generates and stores embeddings and answers queries in your terminal.

By the end, you'll have

A CLI that ingests FAQ data and answers questions semantically.
A React + FastAPI web UI for interactive demos.

Step 1: Prerequisites

MacOS

Please make sure you’ve installed the following software on your machine:

macOS with Python 3.8+
AWS CLI v2 configured with an IAM user that has AWS Bedrock access (aws configure)
A TiDB Cloud Serverless cluster (free tier - no credit card required)
System CA bundle at /etc/ssl/cert.pem

Windows

If you’re on Windows instead of macOS, you’ll need to tweak a couple of steps:
Install Git, Python & AWS CLI
- Git for Windows: https://git-scm.com/download/win
- Python 3.8+ from the Microsoft Store or https://python.org/downloads/windows/
- AWS CLI v2 MSI installer: https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html
Create & activate the virtualenv

cd semantic-qna
python -m venv .venv
# In PowerShell
.venv\Scripts\Activate.ps1
# Or in Command Prompt
.venv\Scripts\activate.bat

You should now see (.venv) at your prompt.
System CA bundle
- Windows doesn’t have /etc/ssl/cert.pem.
- Either omit the ssl_ca parameter (boto3/urllib will use the OS cert store),
- Or download a PEM bundle (e.g. from https://curl.se/ca/cacert.pem) and point to it:

Set env-vars in PowerShell or CMD

# PowerShell
$Env:AWS_REGION="us-east-1"
$Env:AWS_ACCESS_KEY_ID="YOUR_AWS_KEY"
$Env:AWS_SECRET_ACCESS_KEY="YOUR_AWS_SECRET"
$Env:DATABASE_URL="mysql+pymysql://<user>:<pass>@…"

REM Command Prompt
set AWS_REGION=us-east-1
set AWS_ACCESS_KEY_ID=YOUR_AWS_KEY
set AWS_SECRET_ACCESS_KEY=YOUR_AWS_SECRET
set DATABASE_URL=mysql+pymysql://<user>:<pass>@...

After that you can pip install -r requirements.txt and run everything exactly the same as on macOS.

Step 2: Clone & Bootstrap

Next, let's clone the demo project and install dependencies:

# 1. Clone the repo
git clone https://github.com/RealChrisSean/semantic-qna.git
cd semantic-qna

# 2. Create a virtual environment (recommended)
python3 -m venv .venv
source .venv/bin/activate   # (.venv) will appear in your shell prompt

# 3. Install the necessary packages
pip install --upgrade pip
pip install -r requirements.txt

Step 3: Configure Credentials with .env

Once you’ve cloned the repo, create your .env in the project root (same folder as app.py):

AWS_REGION=us-east-1
AWS_ACCESS_KEY_ID=YOUR_AWS_KEY
AWS_SECRET_ACCESS_KEY=YOUR_AWS_SECRET

**Note: The TiDB Cloud hostname will vary by region. Make sucopy yours from the TiDB Cloud console**
DATABASE_URL=mysql+pymysql://<TIDB_USER>:<TIDB_PASSWORD>@\
gateway01.us-west-2.prod.aws.tidbcloud.com:4000/test?\
ssl_ca=/etc/ssl/cert.pem&ssl_verify_cert=true&ssl_verify_identity=true

Make sure to replace and with the actual credentials from TiDB Cloud.

Find your TiDB connection string
- In TiDB Cloud, go to Connect → Public → Python. Copy the SQLAlchemy URL.
- Paste it into DATABASE_URL above, ensuring your user and password are correct.
Get your AWS keys that can talk to Bedrock
- Log into your AWS Console
- In the AWS console, click your username → Security Credentials → Create access key.
- Copy the Access key ID and Secret access key (you’ll only see the secret once).

Step 4: Sample Data: faqs.json

With your credentials in place, prepare some FAQ data in a JSON file so it’s easy to swap in your own later:

[
  {
    "id": "1",
    "question": "What is your return policy?",
    "answer": "You can return items within 30 days."
  },
  {
    "id": "2",
    "question": "How long does shipping take?",
    "answer": "Standard shipping takes 3–5 business days."
  },
  {
    "id": "3",
    "question": "Do you ship internationally?",
    "answer": "Yes, we ship to over 35 countries."
  },
  {
    "id": "4",
    "question": "How do I track my order?",
    "answer": "Check the tracking link in your confirmation email."
  }
]

Step 5: Command-Line App: app.py

Now that your data is ready, let’s build the CLI so you can see semantic search in your terminal. We’ll break it down section by section:

Imports and Configuration

import os, json
from pathlib import Path
from dotenv import load_dotenv       # loads our .env file
import boto3                         # AWS SDK for Python
from typing import List
from tidb_vector.integrations import TiDBVectorClient

# Load all variables from .env
load_dotenv()

# Read environment variables, with some defaults
AWS_REGION = os.getenv("AWS_REGION", "us-east-1")
TIDB_CONN_STR  = os.getenv("DATABASE_URL")
VECTOR_DIM = 1024        # Titan-V2 embeddings are always 1024 elements
TABLE_NAME = "faqs"      # name of the vector table we'll create

What’s happening here?

load_dotenv() loads .env so os.environ picks up our AWS keys, DB URL, etc.
TiDBVectorClient is a library that simplifies vector operations (insert, query) in TiDB, no need to craft raw SQL for vector math.
We store constants (VECTOR_DIM, TABLE_NAME) in variables for clarity.

The bedrock_embed Function

We need to convert text → numeric embeddings. That’s what we feed into TiDB for similarity search.

def bedrock_embed(text: str) -> List[float]:
    """
    Convert a single string into a Titan-V2 embedding (1024 floats).
    """
    # Create a 'bedrock-runtime' client in the correct region
    brt = boto3.client("bedrock-runtime", region_name=AWS_REGION)

    # Prepare the JSON payload. We just pass 'inputText': the text to embed.
    payload = {"inputText": text}

    # The 'invoke_model' call sends the payload to Amazon Titan
    resp = brt.invoke_model(
        modelId="amazon.titan-embed-text-v2:0",   # The specific Titan embedding model
        contentType="application/json",
        accept="application/json",
        body=json.dumps(payload),
    )

    # The response body is a streaming object, so we read and JSON-parse it
    response_body = json.loads(resp["body"].read())

    # Finally, return the list of floats
    return response_body["embeddingsByType"]["float"]

Key Points

We’re using the “bedrock-runtime” Boto3 client, which is how you call AWS Bedrock.
modelId="amazon.titan-embed-text-v2:0": This is Amazon’s Titan text embedding model.
The model returns multiple formats (like float or quantized embeddings). We’re grabbing the float array for maximum precision.

Ingesting FAQs into TiDB

We’ll create (or recreate) a table for FAQ vectors, then load data from faqs.json, embed it, and store it in TiDB.

def batch_embed_batch(texts: List[str]) -> List[List[float]]:
    """
    Embed multiple texts in one Titan batch request.
    Returns a list of 1024-float vectors, one per input string.
    """
    brt = boto3.client("bedrock-runtime", region_name=AWS_REGION)
    resp = brt.invoke_model(
        modelId=os.getenv("BEDROCK_MODEL_ID", "amazon.titan-embed-text-v2:0"),
        contentType="application/json",
        accept="application/json",
        body=json.dumps({"inputTextArray": texts}),
    )
    data = json.loads(resp["body"].read())
    try:
        return data["embeddingsByType"]["floatArray"]

Why this helper exists: Single-row embedding calls are fine for demos, but they slam the brakes the moment you load more than a handful of records. Every call to Bedrock is an HTTPS round-trip, so latency stacks up fast.
batch_embed_batch() bundles an entire list of texts into one request, turning N network hops into one. So this effectively cut our cold-start from 1 minute and 40 seconds for 200 FAQs down to under 4 seconds.

def ingest_faqs(file_path: str = FAQ_FILE):
    """Create the table and load FAQs from a JSON file."""
    client = TiDBVectorClient(
        table_name          = TABLE_NAME,
        connection_string   = TIDB_CONN_STR,
        vector_dimension    = VECTOR_DIM,
        drop_existing_table = False,
    )

    # Check if the table already has data using a standalone engine
    engine = create_engine(TIDB_CONN_STR)
    with engine.connect() as conn:
        row = conn.execute(text(f"SELECT 1 FROM {TABLE_NAME} LIMIT 1")).first()
    if row is not None:
        return client

    faq_path = Path(file_path)
    with faq_path.open("r", encoding="utf-8") as f:
        faqs = json.load(f)

    ids   = [row["id"] for row in faqs]
    texts = [row["question"] for row in faqs]
    metas = [{"answer": row["answer"]} for row in faqs]

    # Batch embed all questions at once
    embs = batch_embed_batch(texts)

    client.insert(ids=ids, texts=texts, embeddings=embs, metadatas=metas)
    return client

Key points to verify:

drop_existing_table= False – so you don’t recreate on each run.
The row-exists check uses a standalone SQLAlchemy engine.
The final client.insert(...) remains the same but uses the new ids, texts, embs, and metas arrays.

Querying for the Closest FAQ

Given a user’s question, we embed it, then run a similarity search for k=1 in TiDB, returning the best match.

def query_faq(question: str, client=None):
    """
    1) Embed the user question via bedrock_embed
    2) Query TiDB for the single closest vector
    3) Return that FAQ's question and answer
    """
    # Step 1: Convert user question into a 1024-dim vector
    q_vec = bedrock_embed(question)

    # Step 2: Run a vector search for the top-1 match
    results = client.query(q_vec, k=1)

    # If no results, we return a "not found" structure
    if not results:
        return {"question": None, "answer": None}

    # Otherwise, get the best match (index 0)
    best = results[0]

    # We expect 'text' to hold the question text (some versions might call it 'payload')
    stored_question = getattr(best, "text", None) or getattr(best, "payload", f"<id {best.id}>")

    # 'metadata' is where we stored the FAQ answer
    stored_answer = (best.metadata or {}).get("answer", "")

    return {"question": stored_question, "answer": stored_answer}

Why only k=1?

We just want the single best match for a standard FAQ scenario. If you wanted multiple top suggestions, you’d use k=3 or k=5.

Interactive Loop & main()

Finally, we provide a simple text-based UI so you can type questions in your terminal.

def main():
    # Ingest the FAQs, storing them in TiDB. Returns a client object for queries.
    client = ingest_faqs()

    # We'll prompt until the user types 'exit' or 'quit'
    while True:
        user_q = input("\n🧐  Ask a question ('exit' to quit): ").strip()
        if user_q.lower() in {"exit", "quit"}:
            break

        result = query_faq(user_q, client)
        if not result["question"]:
            print("🤷  No semantic match found.")
        else:
            print(f"🎯  Closest Q: {result['question']}")
            print(f"💡  Answer:   {result['answer']}")

if __name__ == "__main__":
    main()

How it works

ingest_faqs() is called once on startup to initialize the database table and embed all your FAQ data.
We then enter an infinite loop to ask for user input.
The user’s question is embedded and matched against the database.
We print out the best matching FAQ’s question and answer.

Step 6: Run the CLI

Next, fire up the terminal and launch your app:

python app.py

You'll see something like:

Type “What is your return policy?” and see if it retrieves the correct answer. Try a few variations (like “can I send something back for a refund?”) to see how it still returns the same or similar FAQ.
That’s your local semantic search in action!

Step 7: FastAPI Server: server.py

If you want a web-based Q&A experience, we’ll serve both:

Our React UI (via a static HTML file).
A /query endpoint that does the same embedding + vector search logic as the CLI.

from pathlib import Path
from pydantic import BaseModel
from app import ingest_faqs, query_faq
from fastapi import FastAPI, HTTPException
from fastapi.responses import FileResponse
from contextlib import asynccontextmanager

@asynccontextmanager
async def lifespan(app: FastAPI):
    # We'll reuse this client across requests
    global client
    client = ingest_faqs()
    yield

app = FastAPI(lifespan=lifespan)

# Serve our React index.html at the root path
@app.get("/", include_in_schema=False)
async def read_index():
    return FileResponse(Path(__file__).parent / "index.html")

client = None

# A Pydantic model for the incoming JSON from React
class QueryReq(BaseModel):
    question: str

@app.post("/query")
def ask(req: QueryReq):
    # Use the same logic we have in app.py
    res = query_faq(req.question, client)
    if not res["question"]:
        raise HTTPException(404, "No semantic match found")
    return res

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/ubpgbjhzoxsni0v0b5f2.png)
def health():
    return {"status": "ok"}

Key Points

Lifespan context: Replaces older startup/shutdown events in FastAPI, ensuring we call ingest_faqs() once on startup.
@app.get("/"): Returns our index.html so you can open the React interface in your browser.
/query: Receives a JSON payload ({"question": "some text"}), calls query_faq(), and returns JSON with {"question": "...", "answer": "..."}.

Step 8: Launch the Web Server

Now, run Uvicorn to glue it all together through our helper script (run_with_bar.py):

python run_with_bar.py

You’ll see a progress bar and the total load time before the FastAPI app is live.
Now open http://localhost:8000 in your browser.
You’ll see a basic Q&A interface. Type your question, watch the magic happen!

You've now walked through every step of building a semantic FAQ assistant. From setting up your environment to querying embeddings in both a CLI and Web UI. By combining TiDB's vector storage with AWS Bedrock's Titan V2 Embeddings, you've created a solution that is simple to understand and easy to extend.

Where to go from here?

Replace faqs.json with real support tickets, product specs or documentation.
Add GitHub Actions so every pull request runs pytest.
Pipe the top match into ChatGPT or Claude to create richer and more conversational answers.

TiDB Cloud gives you vector search without maintenance and Bedrock hides the heavy lifting of embeddings. Together they let you focus on what matters most, which is delivering answers that actually make sense.

All of the source code lives in one place. Feel free to revisit, fork, or open issues at https://github.com/RealChrisSean/semantic-qna

TiDB Serverless vs PlanetScale: The Ultimate Cloud Database Showdown

Chris Sean 🪐 — Fri, 14 Mar 2025 00:20:00 +0000

Introduction

If you're building an app, you likely juggle multiple roles—developer, DBA, and more—trying to choose the perfect cloud database solution. You need something scalable, reliable, and ready to handle global traffic spikes. Let's dive into a comparison between TiDB Serverless and PlanetScale to see which fits your needs best.

Scalability

TiDB Serverless Scalability

Imagine your app suddenly goes viral. With TiDB Serverless, there's no scrambling for additional resources—it automatically scales up and down in real-time, based entirely on actual demand. It even scales down to zero when idle, ensuring you only pay for what you use. Perfect for apps with unpredictable workloads, it's ideal for startups mindful of cost.

PlanetScale Scalability

PlanetScale offers automatic scaling but reserves this convenience for higher-tier enterprise plans. On lower tiers, you need to preselect resource allocations, potentially paying for unused capacity during low traffic periods. This can quickly become expensive for apps with fluctuating demands.

Advantage: TiDB Serverless offers greater flexibility in scaling.

Reliability

TiDB Serverless Reliability

TiDB Serverless's distributed, cloud-native architecture ensures your data remains available, thanks to built-in multi-region redundancy. If one region encounters issues, your app seamlessly shifts to another without downtime—critical for global, mission-critical applications.

PlanetScale Reliability

PlanetScale reserves multi-region support for its enterprise plans. Lower-tier users miss out on this crucial reliability feature, potentially limiting global reach and uptime during regional disruptions.

Advantage: TiDB Serverless again leads, providing multi-region reliability at all levels.

Developer-Friendly Features

TiDB Serverless

TiDB Serverless integrates advanced AI tools, including vector search for semantic queries, ideal for recommendation systems and knowledge graphs. Its AI-assisted SQL query editor simplifies optimization, and database branching accelerates development with isolated test environments.

PlanetScale

PlanetScale also supports database branching and excels with non-blocking schema changes, enabling continuous operation even during database adjustments. However, it lacks built-in AI-driven features.

Advantage: TiDB Serverless offers more comprehensive, forward-looking features for modern developers.

What Sets TiDB Serverless Apart?

TiDB Serverless stands out through its native AI integration, making it future-ready for the evolving demands of modern app development. Its design ensures developers aren't just managing current needs but are prepared for future trends like AI and real-time analytics.

Cost Comparison

TiDB Serverless Pricing

TiDB Serverless operates on a transparent, pay-as-you-go model—perfect for fluctuating workloads or tight budgets. A generous free tier also allows experimentation without upfront costs.

PlanetScale Pricing

PlanetScale requires upfront resource allocation, potentially resulting in higher costs during periods of low utilization. Essential advanced features typically require enterprise-level subscriptions.

Advantage: TiDB Serverless provides greater cost efficiency and transparency.

Key Takeaways

Both platforms have strengths, but TiDB Serverless excels in scalability, reliability, and future-ready AI integrations. Its flexible pricing and ability to scale to zero offer significant advantages for cost-sensitive or dynamic workloads. PlanetScale remains strong for developers heavily reliant on MySQL and traditional database workflows.

Final Thoughts

Choosing the right database is crucial, and with TiDB Serverless, developers gain powerful, scalable, AI-driven capabilities with minimal financial risk. Its free tier makes exploration easy, providing an accessible entry into next-generation database technology.

Conclusion

The future of databases is bright, with tools like TiDB Serverless and PlanetScale pushing innovation. While there's no one-size-fits-all solution, TiDB Serverless provides compelling benefits for modern, data-intensive, and AI-focused applications. Try it out, experiment, and see firsthand how it could transform your app-building experience.

TiDB Serverless vs Amazon RDS: The Ultimate Cloud Database Showdown

Chris Sean 🪐 — Thu, 13 Mar 2025 23:56:38 +0000

Introduction

If you’ve ever found yourself scrambling to keep a database from melting under unexpected load, you know how crucial a solid, hassle-free backend can be. With so many cloud database services on the market, it’s tough to pinpoint which one will keep your app agile. Let’s break down how TiDB Serverless measures up against Amazon RDS and see which approach might fit your needs best.

Scalability

Amazon RDS Scalability

Amazon RDS, while definitely a step up from running your own MySQL, isn’t fully serverless. You still need to pick an instance size. If you undershoot, you’ll be doing some manual resizing (and restarting the instance), which means downtime; if you overshoot, you pay for horsepower you don’t use. While you can add read replicas to handle extra read traffic, every write still flows through a single primary node, which can become a bottleneck under heavy concurrency. Unlike TiDB, RDS doesn’t scale down to zero, so you might end up paying for a big instance even if your workload is sporadic.

TiDB Serverless Scalability

TiDB Serverless is built to be as hands-off as possible. You can start with minimal resources, letting the system autonomously ramp up capacity whenever traffic spikes or analytics workloads grow heavier. TiDB’s distributed design scales both reads and writes, ensuring there’s no single node bottleneck. TiDB handles distributed transactions at scale and automatically scales back down when your workload drops.

Note: TiDB Serverless supports single-region deployments. For multi-region setups, consider TiDB Dedicated.

Reliability

TiDB Serverless Reliability

TiDB Serverless is built on a distributed, cloud-native foundation, meaning redundancy and failover are intrinsic. It offers automated failover and maintains strong ACID guarantees via Multi-Version Concurrency Control (MVCC). TiDB also supports online schema changes without locking tables, essential for continuous uptime.

Amazon RDS Reliability

Amazon RDS reliability involves manual setups and additional fees. Multi-AZ deployments or read replicas provide redundancy but come at higher costs. Failover isn't instant, and global deployments require complex solutions like Aurora Global Database or cross-region replicas. While robust, RDS often demands a more hands-on approach.

Developer-Friendly Features

TiDB Serverless

TiDB Serverless provides built-in AI features, including vector search and an AI-assisted SQL editor. Database branching allows isolated testing and development, merging changes similar to Git workflows. Being fully open source, TiDB offers greater flexibility and community engagement.

Amazon RDS

Amazon RDS simplifies database management within AWS, integrating smoothly with services like IAM and CloudWatch. However, it lacks built-in AI or advanced query capabilities. Achieving similar functionality often involves integrating additional AWS services or third-party solutions. Schema changes may still require careful orchestration or downtime.

What Sets Them Apart?

TiDB Serverless

TiDB Serverless was designed from the ground up as a distributed SQL database, naturally supporting horizontal scaling, distributed concurrency, and real-time analytics via HTAP (with TiFlash integration). It supports scale-to-zero and online schema changes (DDL) without downtime.

Amazon RDS

Amazon RDS shines through deep integration within AWS. It provides familiarity with traditional SQL engines like MySQL or Postgres, backed by AWS’s robust infrastructure and ecosystem. Ideal for teams heavily invested in AWS, RDS offers standardized provisioning with predictable resource management.

Cost Comparison

TiDB Serverless Pricing

TiDB Serverless operates on a pay-as-you-go SQL-level model, billing for actual resource usage. It’s cost-effective for fluctuating workloads and offers complete cost transparency, scaling down during idle periods. The free tier makes it accessible for experimentation.

Amazon RDS Pricing

Amazon RDS pricing is based on provisioned resources (instance size, storage, and region) with fixed hourly rates regardless of utilization. Costs increase with Multi-AZ, read replicas, or cross-region replication setups. It’s suitable for predictable workloads but less flexible during variable demands.

Key Takeaways

The core differences revolve around scalability, reliability, and developer features. TiDB Serverless offers automatic horizontal scaling, built-in AI features, and online schema changes without downtime. RDS emphasizes AWS integration and familiar management but involves manual scaling and less built-in innovation.

Final Thoughts

Both TiDB Serverless and Amazon RDS have distinct advantages. RDS suits stable workloads within AWS ecosystems, providing straightforward managed SQL databases. TiDB Serverless excels with dynamic scaling, global concurrency, built-in AI, and flexible cost control, ideal for modern data-intensive apps.

Conclusion

Today’s databases need to be agile and intelligent. TiDB Serverless meets these needs head-on with distributed architecture, AI capabilities, and dynamic scalability. Amazon RDS remains a reliable AWS-integrated option for traditional SQL workloads. Consider experimenting with TiDB’s free tier to experience its modern capabilities firsthand.

Nine Years in Tech: Lessons and Reflections

Chris Sean 🪐 — Mon, 10 Feb 2025 18:23:27 +0000

I’ve been in the tech industry since 2016. That might not sound like forever, but as I look back, it’s nine solid years of coding, exploring, failing, winning, and feeling like an imposter more times than I can count. If you’d asked me at the start if I’d still be here—especially after the self-doubt I had as a junior developer—I would have laughed. Yet here I am, making more money than I ever dreamed, sometimes close to “Netflix money” without actually working at Netflix. It’s wild.

That doesn’t mean there weren’t bumps. Imposter syndrome? Had it for more than half my career. Doubts? Tons. But I pushed through, tried new things, changed jobs, learned from mistakes, and kept going. After nearly a decade, I want to share a few big takeaways—both the good and the bad.

1) The YouTube vs. Coding Dilemma

For all the success I’ve had, there’s a part of me that wonders what would’ve happened if I’d spent the countless hours I invested into YouTube purely on coding. I don’t regret making YouTube videos—I’ve enjoyed it, it’s brought me opportunities, and I’ve met incredible people through it. But if I’m brutally honest, that was hundreds or even thousands of hours that could have been spent deepening my coding expertise.

In hindsight, I might have chosen to split my time differently. Still, I believe in doing what you love. If creating online content makes you happy, do it—but don’t lose sight of your main career goals. There’s a balance between building a personal brand or side hustle and focusing on your core craft. If you’re serious about becoming a top-tier programmer, make sure you’re consistently leveling up your skills.

2) Front End or Back End? Do What You Love

When I started, everyone insisted that back end was where the big money was. They said, “Learn Python, learn Node.js, master databases. That’s where you’ll really shine.” So I did. And it worked—I make a great living, I’ve tackled challenging backend projects, and I do appreciate how critical backend development is.

But guess what? I still love the front end more. It comes naturally to me. There’s something about seeing an immediate visual result that’s really rewarding. For a long time, I let others’ opinions steer me away from the front end, thinking that was somehow “less prestigious.” It’s not. I know brilliant front-end developers who make just as much—or more—than a lot of backend folks. The secret is skill, not job title.

So if I could go back, I’d tell myself not to sweat other people’s opinions. If you’re fascinated by UI/UX and front-end frameworks, go for it. If you love building intricate APIs, do it. The money and opportunities will come when you excel at what you genuinely enjoy.

3) Live Below Your Means (Seriously)

Coming from a background where I didn’t have much, I was hungry to enjoy life once I started earning “real” money. My first tech job paid $45K in California, which was hardly enough to scrape by. But when I eventually hit $70K, $90K, and beyond, I thought, “I deserve a nicer apartment, a better car, maybe some cool gadgets.”

Before I knew it, half my paycheck went to rent, another chunk to a car payment, and I wasn’t saving or investing. That was a missed opportunity. If I’d put that money into Tesla, NVIDIA, or even just a simple index fund, who knows how far ahead I’d be now?

No matter how much you make, you’ll always find ways to spend it. That’s why it’s crucial to be intentional. Sure, treat yourself occasionally—but don’t get caught in the trap of upgrading your lifestyle with every raise. The faster you learn to invest and live below your means, the quicker you’ll reach financial freedom.

4) Don’t Let Fear Limit You

Early in my career, there were a bunch of things I avoided because I was afraid: AI, tricky algorithms, open-source contributions. The idea of diving into something brand-new seemed overwhelming, and I’d tell myself I wasn’t smart enough or didn’t have enough time.

What I’ve learned is that the only true way to move forward is to push through that fear. If AI interests you, take an online course—even a free one from Harvard or Stanford on YouTube. If you struggle with coding challenges, do LeetCode or HackerRank, no matter how annoying they can be. If you’ve never contributed to open source, pick a small project that excites you and add a feature or fix a bug. The worst that can happen? Someone corrects your code or you realize you need more practice. That’s how you grow.

5) It’s Never Enough (So Learn Contentment)

When I was making $45K, I dreamed of hitting $70K. Then $90K. Then $160K. Then $200K. Even when I made close to $400K last year, there was a part of me that said, “What’s next? Why not more?” Ambition is healthy—it pushes you forward. But if you never slow down to appreciate how far you’ve come, you’ll constantly feel inadequate.

That’s why contentment is huge. You can and should keep striving, especially in a fast-paced industry like tech. But make sure you notice when you’re actually in a good spot. Maybe you’ve found a supportive team and a role you love. Or maybe you have enough to live comfortably. Don’t get stuck on a hamster wheel of “never enough.”

Final Thoughts

Nine years in tech flew by. I’ve learned that money can grow exponentially, but it still doesn’t buy complete satisfaction. I’ve discovered that a career path doesn’t have to be defined by other people’s opinions—you can make frontend or backend or full-stack or even DevOps your own. And I’ve realized that fear is often just a sign that you’re about to learn something new.

If you’re early in your journey (or even years into it), I hope these reflections help you navigate your path. There’s so much opportunity in tech if you’re willing to keep learning and take a few risks. Thanks for reading, and I’ll see you in the next post!

Migrate from PlanetScale to TiDB Serverless in Minutes: A Developer’s Guide

Chris Sean 🪐 — Wed, 29 Jan 2025 21:34:40 +0000

If you’re here, you’re probably curious about moving a database from PlanetScale over to TiDB Serverless—or maybe you’re just exploring new database options. In any case, I’ll walk you through the why and how of this migration. We’ll talk about differences between PlanetScale and TiDB, then dive straight into the steps to get your data moved over with minimal fuss. If you’ve got questions or get stuck, drop a comment or join our community. Let’s get into it.

Why Migrate from PlanetScale to TiDB Serverless?

So, why even consider moving away from PlanetScale? Here are a few reasons I’ve heard from folks:

Cost – PlanetScale’s new billing tiers might not fit everyone’s budget. For example, if you’re using a PS-40 cluster for your main production branch ($99 per month) and two PS-20 clusters for additional branches ($59 each), your total cost would be $217 per month. In contrast, TiDB Serverless starts at $0 per month, offering 25 GB of row storage, 25 GB of column storage, and 250 million Request Units (RUs) free per month for each organization. Beyond that, it’s $0.20 per GB of storage and $0.10 per million RUs. This pay-as-you-go model allows you to scale costs directly with your usage, often resulting in significant savings.
MySQL Compatibility – TiDB Serverless is fully MySQL-compatible, ensuring your existing SQL queries and tools will work with minimal changes. A notable example is Foreign Keys, which are not natively supported in PlanetScale. While PlanetScale does offer a workaround for foreign key constraints, TiDB Serverless provides full native support, allowing you to enforce referential integrity seamlessly between tables.
Distributed & Scalable – TiDB Serverless handles read and write scaling behind the scenes—no single primary node to bottleneck. This can make life a lot easier when traffic surges.
Online DDL – If you hate scheduling maintenance windows for schema changes, TiDB lets you do that online.
Rich Dev Features – Vector search, branching (like Git for databases), and more. Perfect if you’re building AI or advanced analytics.

But enough about reasons—let’s actually do it. I’ll show you how to migrate step-by-step, using a small example database.

Migration Overview

Migrating from PlanetScale to TiDB Serverless basically boils down to two big steps:

Dump your PlanetScale data to your local machine.
Import that dump into TiDB Serverless. We’ll also do a little optional verification, like checking table counts, just to make sure everything came over. Let’s start with dumping your PlanetScale data.

Dumping Data from PlanetScale

Retrieve Connection Info
- In your PlanetScale dashboard, at the top right corner click “Connect”.

If needed, generate a new password.

Copy the MySQL CLI connection string.

For example: mysql -h aws.connect.psdb.cloud -D mydb -u - --ssl-mode=VERIFY_IDENTITY --ssl-ca=/etc/ssl/cert.pem

Verify Existing Data
- Paste that string into your terminal.
- Run SHOW TABLES; in your PlanetScale shell.

Optionally, do a few SELECT COUNT(*) checks to confirm row counts in each table. This is good to compare later.

Next we need to install the pscale CLI
- On macOS, you might do brew install planetscale/tap/pscale.

For Windows or Linux, check PlanetScale’s docs for installation steps.

Dump Your Database
- Use the command pscale database dump your-db-name --org your-org --branch main-branch (adjust org and branch names accordingly).

This creates SQL files locally. You’ll see something like *-schema.sql and *.numbers.sql for data inserts. That’s all for the dump. Once you’ve got those SQL files on your machine, we’re ready to move on.

Creating a TiDB Serverless Cluster

Navigate to TiDB Serverless Console
- Head to tidbcloud.com and sign in (or sign up if it’s your first time).

Click “Create Cluster” and pick TiDB Serverless.

Choose a Region & Name
- Select a region close to your users or your own location.
- Name your cluster something memorable, like my-planet2tidb-cluster.
- Wait a few seconds for the cluster to be created.
Generate Connection Credentials
- Click “Connect,” then “Generate Password.”

Switch to “Connect With MySQL CLI” to get a MySQL connection string.

Importing Data into TiDB Serverless

Now it’s time to feed our PlanetScale dump into TiDB.
CD into the correct folder

Schema Creation
- Your dump folder has *-schema.sql files.
- You can loop over them in your terminal with a shell command. For example: for file in ./*-schema.sql; do mysql --host xxx.tidbcloud.com --port 4000 \ --user your-user --password='your-pass' < "$file" done
- Replace xxx.tidbcloud.com, port, and credentials with your actual TiDB Serverless connection string.

During this process, you might encounter an error related to the unsupported utf8mb4_0900_ai_ci collation. See below:

Here’s why it happens and how to fix it before proceeding:

Why does this happen?

PlanetScale uses MySQL 8.0, which supports the utf8mb4_0900_ai_ci collation.
TiDB (as of now) does not support this collation. Instead, it supports other utf8mb4 collations such as utf8mb4_general_ci. ## The Solution
You need to modify the *-schema.sql files to replace the unsupported utf8mb4_0900_ai_ci collation with a supported one, such as utf8mb4_general_ci. Step 1: Modify the Schema Files Run the following for loop in your terminal to automatically replace the collation in all *-schema.sql files:

This loops through all *-schema.sql files and replaces every occurrence of utf8mb4_0900_ai_ci with utf8mb4_general_ci.

If you encountered the error and applied the fix by modifying the files, you need to re-run the command to insert the data into TiDB. Use the following:

If the sed command you’re using is encountering compatibility issues with your system (likely macOS or a non-GNU version of sed). Here’s what you need to do next:

Fix the sed issue
1. The sed error is due to using an incompatible version. On macOS, sed -i requires an argument for the backup extension. Here’s the corrected command:
  1. for file in ./*-schema.sql; do sed -i '' 's/utf8mb4_0900_ai_ci/utf8mb4_general_ci/g' "$file" Done
2. If this still fails, install GNU sed using homebrew
  1. brew install gnu-sed
3. Then replace sed with gsed in your script:
  1. for file in ./*-schema.sql; do gsed -i 's/utf8mb4_0900_ai_ci/utf8mb4_general_ci/g' "$file" done
4. Insert the data and verify the schema import
Similar process for the data files named something like *.numbers.sql:
1. for file in ./*.00001.sql; do mysql --comments -u '32Z4oGrkgk78qLp.root' -h gateway01.us-west-2.prod.aws.tidbcloud.com -P 4000 -D 'test' --ssl-mode=VERIFY_IDENTITY --ssl-ca=/etc/ssl/cert.pem -p'vVsi9OSNzFwWRfdy' < "$file" done

Verify Next we will want to verify the data and you can do that by running this string, but this time without the loop:

  - Connect to your TiDB cluster directly:
mysql --host xxx.tidbcloud.com --port 4000 \
--user your-user --password='your-pass'

Run SHOW TABLES; and check row counts again to ensure all data matches what you saw on PlanetScale.

Wrap-up and Additional Tips

That’s literally it. Your PlanetScale data is now sitting happily in TiDB Serverless. A couple of pro tips before we go:

Enjoy the cost savings: TiDB Serverless can scale down to zero, meaning if your traffic dies off, you’re not paying for idle capacity. This is a big deal for dev/test environments or smaller projects.
Try out advanced TiDB features like vector search or online DDL. If you’re building AI-driven apps, vector columns let you store embeddings right next to your relational data. And if you like living on the edge, online schema changes are a life-saver if you need to update your tables mid-traffic.

Conclusion

And that’s a wrap. We successfully migrated data from PlanetScale to TiDB Serverless, step by step, without too much hassle. Whether you’re looking for free usage tiers, more flexible scalability, or advanced features like AI-ready queries, TiDB Serverless could be an excellent fit. If you run into any issues or have follow-up questions, drop them in the comments below or hit up our community forum. Thanks for watching, and happy building!

Bootcamp students interview

Chris Sean 🪐 — Wed, 17 May 2023 04:45:31 +0000

Interview #1: Chris Sean Interviews Paula (Bootcamp Graduate)
Puala
Chris: [00:00:00] Paula, it is really nice to, uh, it's really nice to meet with you. It's really nice to just talk to someone who actually attended a coding boot camp, to be honest. Right. I, I've been doing these kind of videos for about seven years now, and so I've met with a lot of people who went to coding boot camps who have negative experience, positive experience.
Chris: And so what's interesting though we'll be talking to you is that you actually got a job through quoting bootcamp. Is that correct?
Paula: Uh, yeah. After my, my bootcamp six months with, after my graduation,
Chris: yes. Okay. That is pretty impressive. So, okay. For people who don't know you, right, what is the, what is it?
Chris: What is it that you do now? What is it that you do now in tech? What's your job?
Paula: So right now my title is data analyst.
Chris: I do have a few questions. Then, knowing that you got a job through bootcamp, which is encouraging because actually I know quite a few people who didn't. Right. And so for someone who went to your bootcamp before, before you went to your bootcamp, what did you expect from it?
Chris: Like, what were you expecting before you even
Paula: attended? I [00:01:00] think I had high expectations. I, I expected to be ready. Right. I expected that once I was done with the bootcamp, I'll know everything I needed to get a job. And not that I, that I. Upset or upset about the results. It's just that I, I had to change my mindset during the bootcamp to understand that that was, Tired of my path.
Paula: Mm-hmm. And not the whole thing. Yeah. I like
Chris: to think of the, another emotions, the anxiety you probably felt before, like j I mean, for example, before I'm an attack, I'm self-taught, but ironically the one coding bootcamp I wanted to go to was Coding Dojo. But I didn't have the money. I didn't have the credit cause I was living paycheck to paycheck.
Chris: Excel. I was, my, my credit score was terrible. Uh, and I couldn't attend. Right. But at the same time, I really wanted to go to, To that bootcamp. So like what, what were your emotions before joining? Like were you nervous and what were you, what like were you thinking it's too expensive because it is pretty expensive?
Chris: Right. I
Paula: think I was a, a good student in terms of, I did my research, I [00:02:00] watched tons of YouTube videos. I talked to people and I was trying to understand what would be the best for me. And I think in that sense, uh, I, I, I don't think I was. Nervous or anything. It's just, uh, I knew that the bootcamp would give me the structure that I needed because I mean, I'm, I cannot be, I'm not a person that can teach because I, I don't have that structure.
Paula: I don't have that discipline. I just jumped from here to there and, uh, uh, so I was just excited that someone was going to tell me what to do, and I think that that was like, The best part of it. There was someone there every day checking on what I, I was doing, how I was doing, and what I have to do next.
Paula: And uh, I was excited for that. I needed that.
Chris: So then why did you go to bootcamp? Was it mainly because of that you needed that [00:03:00] accountability? You needed someone to really push you. If you go
Paula: online or if you go like on LinkedIn or if you go on YouTube, I know, and you start reading what people say that what you need to become a data analyst or data scientist, you, you can go crazy.
Paula: Like there's so much stuff out there and people say, this is better. That is better. You should learn this first. You should learn that first. And so some of my friends that, I had two friends that went to boot camps and they were like, that's why you should go to a boot camp, because they are going to put that into a curriculum.
Paula: They are going to put that in a order that makes sense. And you're gonna learn, you're gonna, you know, building blocks, you're gonna learn in the order that you should, or that at least is gonna be easier for you. So I think that was my point. I needed someone to help me figure out what I, where to start.
Chris: Yeah. I, I guess [00:04:00] another thing you're trying to get at is focus learning, right? When, I mean, I'm still learning, but when I didn't have a job, when I was teaching myself online reading books, you name it, I think my biggest problem was I just tried to learn everything. Right. And there was no one really guiding exactly what to learn first, what to learn next, which is why I do my channel to help people now.
Chris: And so then, now, now you went to the boating bootcamp. How hard was it? What, what, what, what, what course did you take? Was it the part-time bootcamp? Was it full? Oh, that smile right there that shows everything. Was it, did you take the part-time bootcamp? Was it full-time? Were
Paula: you working at the same time?
Paula: Time? I did a part, yeah, I did a part-time. So, uh, just a tiny bit of background. I wanted to change careers. I mean, somehow mm-hmm. At that. Mm-hmm. At some point I didn't really know what I wanted to do, so I even thought about going back to school and getting my teaching credential mm-hmm. And become like a science teacher.
Paula: But that would, uh, I would need to leave my job [00:05:00] and I, I could not leave my job to do that. Is that because you
Chris: have a family too? So, I'm sorry. Do you have a family? Is that why you couldn't leave your
Paula: job? Yeah. Yeah. Like I, I, I have, uh, is my husband and I, we are paying mortgage, so I couldn't like just tell him, Hey, take care of everything and now I'm gonna Good luck.
Paula: Yeah, good luck. So I had to find something that I could do while working and so I took the part-time and I really, yeah, it was hard, but I really appreciate that at the very beginning of the bootcamp before. Even before we started, uh, coding though, Joe came with like this messages and emails and a kind of a sketch of a plan where you need to realize, you know, really prepare.
Paula: Like, Hey, I'm going to just devote this amount of hours per day. This is how much of my weekend I'm gonna put into this. Who is gonna take care of the food? Who is gonna take care of the house? Who is gonna, [00:06:00] you know, because it is, it is, uh, When you get there, you kind of like, uh, come on. But now, once you start, you're like, yeah, I actually need that plan, because that was the deal at home.
Paula: Like I told my husband, Hey, I, I'm doing this, but for us, and I need you to kind of take over some things because otherwise I won't be able to go through this. So it was harder, was overwhelming, but uh, but I mean, it's, if you want to finish in that amount of time, that's what it takes, right?
Chris: Yeah, definitely.
Chris: I mean, The the amount of focus that you had to do and so I'm Kirsten like working at the same time doing Coding Bootcamp at Coding Dojo at the same time. How many hours a day would you say you have to put into it? Or let's, yeah, let's, yeah. An average per week probably, yeah, it's part-time, but really how many hours did you have to put into really keep up with the program?
Chris: You know, after
Paula: hours? Yeah. I think Monday to Friday I was putting at least two and a half [00:07:00] hours every day. A weekend
Chris: after a
Paula: shift of work. Yeah, yeah, yeah, yeah. And then on the weekends I would put another, at least four hours each day, so eight hours of my weekend if I didn't have a test or, or something.
Paula: Because there were weekends where we had like a. Test to be done by the end of the weekend and mm-hmm Then I would put at least 10, 12 hours just to finish whatever I had to finish.
Chris: Thinking about that then do you think just anyone can do bootcamp then? Like does it need to be a particular kind of person that goes to, uh, that goes through it, right?
Chris: Like for example, you went to Coding Dojo, like what kind of person can go through that? I'll tell you this. I can't do school. Right. Uh, um, I dropped out of I think three or not four different colleges for a reason because I just never did my homework. Right. I'm gonna fail. I don't care. Uh, I can't do it, but so like what I, I mean, okay.
Chris: Maybe not me, so, but other than me, like what kind of person do you [00:08:00] think, or what kind of mindset do you think a person needs to have if they really go through with it? Because it's not easy from what you shared. They
Paula: say that at the beginning and people say around, if you go on Reddit or. It's khaki.
Paula: It's cheesy, but it is too. You get what you put in. So if you are thinking that you're just gonna sign up and things are gonna just happen. Yeah. That's not how I work. And yeah. So you need to have that mindset that, yeah. Uh, if I don't dedicate the time, if I don't put in the hours, if I don't do the homework, uh, because I guess you could get by just doing the minimum, you know, uh, sounds like me, but I mean, you pick Yeah, but I, yes, but that's what you're gonna get at the end too.
Paula: You know you're gonna end. Mm-hmm. Because I mean, I, I think I was. Very dedicated. I, I, I did everything they asked me to do, and I will [00:09:00] try to redo. And, uh, and even that, if I go back now and try to do some of the things I learned, I, I probably need a refresh. Mm-hmm. You know, so if you don't actually do the work and repeatedly, you know, do the homework and.
Paula: Then two weeks later, you're gonna have just put your money on the trash. So you need to vet your money, vet your time, and if you want the results you need to. To put the work
Chris: and, and, and I'm assuming you did the remote class, right? Since it's part-time? Um, yeah, I think only remote. I'm not too sure, but, um, mine was fully remote.
Chris: Yeah. Okay. Okay. Fully remote. And so then you looking through Zoom, right? I joined a remote class. Was it yesterday? Yesterday. And you know, you see people in the class, right? Did you see people no longer by the time you finished the last class of your bootcamp, do you see some people no longer there? Some people give up, yes.
Chris: You did? Yes. I'm curious how many, like, let's
Paula: just. I actually had a count of it. I think we You had a count day. Yeah. [00:10:00] Yeah. Cause uh, we had people coming from the, you know, the, the, like they were hold held back. Right? Yeah. So people, so added people from the, another cohort mm-hmm. That they didn't pass. And we had people from our cohort that stayed behind.
Paula: Yeah. Or dropped out. I dunno what happened to them. Uh, but I remember that out of the 25 that it started, I think, I'm not, you know, a hundred percent sure the numbers, but if I remember, yeah, I guesstimate it's fine. At the end, only 15 were like the same. 10 dropped out and 10 dropped out. There were new people, uh, or held back, I dunno.
Paula: Yeah. Um, and new people, uh, came in. Uh, so from a different cohort? Yeah, because we had like four modules. So every module some people were staying behind or
Chris: dropping out. I, I mean, and the reason I ask is because it's not easy. I'd probably, if I did go to coding bootcamp, I [00:11:00] probably would've been one of those people because I just don't do all of homework.
Chris: I neither really push myself. Right. Um, motivate my own self, um, you know, I've heard from people, right? People have said there are some negative things about Coding Dojo. I'm not sure if you heard of anything of that before signing up or you have. And so hearing all those things are those things like what have you, is there anything that you heard that wasn't true and et cetera?
Chris: And, and cuz I just wanna make it as transparent as possible right? If people are gonna sign up for
Paula: Coding Dojo. Yeah. I think the only thing I heard, uh, and I can't compare to any other bootcamp cuz I mm-hmm. Didn't take other bootcamp. Yeah. Uh, was, uh, Some boot camps, they have a very restrict entering, uh, process.
Chris: Like prerequisites. You have to know. Let's say, um, for your example, it would probably be sql. You have to know SQL ball. Yeah. I don't, I don't think you to know Python for analysts.
Paula: Yeah, the analysts. Okay. So some, some, so some bootcamps will do that. Like, and it's very hard. There was a bootcamp that I [00:12:00] thought about it and I was just scared of the taking the test cuz it sounded like a very like, um, Holding Dojo.
Paula: The only thing I heard before was that, that they, their, uh, selection for, you know, to start was not as vigorous. And that sometimes would make your cohort have, have people in your cohort that would be just behind and would kind of like make the whole process a little longer. Slower. Yeah. Yeah. And I think I, I noticed some people in my cohort that I was like, I don't think you took the test or if you did like, yeah, I don't know how you made it, you know?
Chris: Yeah. They probably chat g p T to help you with the test.
Paula: Yeah. Something like that. So I was like, uh, and I mean something, I, I mined my own business. I did what, you know, I had to do. But I can see some people being [00:13:00] annoyed by that because, you know, sometimes you, the teachers explain, explaining something super important or you know, and then you have these people like, oh, I'm sorry, can you go over that again?
Paula: And you're like, really? Like, she just explained this and Yeah. Yeah. But I mean, I guess you can find that anyway. Yeah.
Chris: I mean, everyone has different ways that they learn. Some people are slower than others. Right. Um, I, for myself personally, um, I have dyslexia. Right. I, and, um, uh, uh, I was in special ed. I rode, I rode a short yellow bus, right?
Chris: I was one of those kids. I'm a proud special ed student, right? Um, and so for me personally, uh, I, I didn't realize I had dyslexia until last year, and which makes sense because I remember for the longest time when I look at documentation, um, it would drive me crazy because I can't, it was so hard for me to understand what I read after, read it over and over again.
Chris: Now that I know I have it, now I know how to. Fight it. And actually I'm much better now. Unfortunately, only six years after I got sick. I'm in my seven year now. Right. Unfortunately. So that was really difficult for me. Now, [00:14:00] um, what are your cons? I'm curious then, right? What are some cons to going kuda, kobu
Paula: camp?
Paula: I think the, well, it's a lot of money, right? So how much should you pay for your trip of school? I think it was, 8,585.
Chris: Oh, I thought it was $16,000. Okay, so 8,500. Did you get like a discount or anything?
Paula: I got, uh, 1000. Okay. Uh, 1000. Uh, nice discount for, for being a female in writing and they say about females in the field.
Paula: Uh, okay. But what I would say, yeah, it's the money. Right. So I guess that would be, that's the biggest cost. The money. It's expensive. Cause if you can't, yeah. If you can't. Teach yourself, then go for it. You know, find some, some sort of structure or if you have a friend, I don't know. Mm-hmm. I think there are ways to, to, uh, so I would say that is a big con and I think sometimes you can fool yourself.
Paula: Like I said, I, I expected that once I [00:15:00] was done, I would be, Hundred percent ready. So, okay, this is the 8,500 that I'm investing and I'll be a data scientist. Yeah. And you're gonna learn pretty quick that that's not crazy. You, you need to keep investing on your education,
Chris: not just during coding, not just during the bootcamp.
Chris: After bootcamp.
Paula: Yeah. I didn't do a, a bootcamp after what I did was, uh, I did some, you know, Udemy, Udacity, Coursera. Uh, some of those, their platforms by myself just to learn different tools or to get a little deeper into some of the tools that I learned during the bootcamp. So I think the, the cause is, uh, the shock once you're done with it and you're like, oh my God, I don't know anything yet.
Paula: It had a lot still to learn. So you felt
Chris: that even after, right after coding bootcamp, man, you, is that, is that what you're talking about? Yeah. Yeah. And, and I'm glad you mentioned [00:16:00] that. Sorry, my dog. I'm not sure if you can see him. He, yeah, I can, he's very needy because I, I have family actually who went to college, they got their computer science degree and they still can't get a job.
Chris: And, and I know why, because they only depended on what they learned. They only depended on what they learned in college to get them the job. No way. And I, and would you agree? It's the same thing with, um, with the bootcamp where it's not just taking in and learning only depending on what you learn to bootcamp, but you have to put in more effort after to learn more.
Chris: Totally. And even when you're done to Kony Bootcamp, and, and I can say as well as, uh, someone who works in tech, right? I'm working in a data engineering field. I was a JavaScript developer first. The amount of learning how to do in the beginning of when I got my, this job a year and a half ago to learn Python, to learn what a data warehouse is, and you know what those are now, data lake.
Chris: Um, what is, um, you know, working with these tools that turn data into grass and et cetera. I'm like, what is all this? Learn, what is SQL Have to learn? Sequel, I have to learn post, [00:17:00] scratch, you name it. Right? And so learning all these different skills, and I'm that, that's already six years in in my career. I had to start learning all that.
Chris: You never stop learning, but the moment you really do stop investing in yourself, um, would you agree that then your, your career, your future in this career is not as like, secure or you just loses value eventually in the future?
Paula: Yeah, totally. I, and the, what you mention about college is like, like I went to college for chemistry and yeah, I, I, after four years I was like, I don't know anything, you know?
Paula: And with the bootcamp, it was the same feeling like I got out and I was like, I know a lot of things. But I'm far from knowing everything I need. Yes. To get a job very far
Chris: from it, even now.
Paula: Yeah, totally. I, I just got this job and. Like I said, they are like, oh, we don't use Tableau. That, that's what we had a little bit during Tableau, the camp.
Paula: Mm-hmm. We don't use Python for visualization. We use Power bi. I was like, okay, so now I'm gonna learn Power bi or, or is that
Chris: Melane Meta? Metadatabase Metadatabase,
Paula: right? [00:18:00] Yeah. It's for, uh, they use Power BI as a for report and data visualization. So I, I was like, okay, then I'll, I'll learn that. Yeah. So I mean, you're gonna be learning and I think.
Paula: For every job is gonna be like that. No matter where I start, it's gonna be something new that I'll have to learn just to adjust for that. Oh
Chris: yeah. 100% for every job. I mean, everything you know now is not gonna be relevant at the next job you might have to learn a new technology. Right. And so, and you said, so you said it took you six months, by the way, the fact you got a job even in six months.
Chris: Congratulations. That's impressive. Thank you. Because I know people who went to boot camp and couldn't, couldn't get a job at all. Right. Um, for those people who couldn't get a job, would you say it's mainly because they didn't put enough effort, right? Mm-hmm. What do you mean? Okay, so people put a lot of effort and still can't get a job, but like, You know, what, what is it that helped you get a job in as low as six
Paula: months?
Paula: I think, uh, for me, so they have a career service as at, at [00:19:00] coding ojo, and I appreciate them. Uh, But I had two people from the field that gave me two very nice advice and I'll share here with you now. Yeah. One I applied for this pharmaceutical cuz I thought, you know, they didn't data on the list. I'm from the, the field.
Paula: Mm-hmm. Pharmacy in, uh, chemistry. I emailed her, she posted like a LinkedIn, Hey, I'm looking for blah, blah, blah. And I said, Hey, I'm interested. And then she saw my profile, she text me back, she said, Hey, you are not a candidate. But I'm willing to talk to you. And I was like, oh, that's
Chris: awesome. Wait, you know, let's wait.
Chris: Hold on. A recruit, wait, a, a hiring manager or a recruiter said that to you? Yeah.
Paula: Was this on LinkedIn? Yeah. Yeah. So it was a, on a, it, it's called Women and Data Science. Okay, nice. Nice. And she posted there and she, you know, she, she said, she said that You are not a candidate, but I, I wanna talk to you. And I say, yeah, that would be so helpful.
Paula: So, because when I said I'm interested, I said, Hey, I'm interested and if I'm not a [00:20:00] candidate, I would love to talk about your processing. Right. So she did that and then she said, I'm going to be honest with you because I, at that time, I was doing a w s course cuz everyone was talking about a w s. So I was like, okay, let me do that.
Paula: And she was like, you know, I, I don't wanna be me but you, I think you're wasting your time doing AWS because you don't even, I was just about to experience. Yeah. You don't even have experience with the basic stuff, you know? Yeah. Nobody's gonna hire you to be a AWS engineer if you don't have nothing on your background.
Paula: And she said, go back, do some Google analytics on Coursera. Do some like the basic. And she said, and apply for data analyst job, not data scientists. You're not gonna learn. Oh, so you took
Chris: the data scientists, um, course at clinical
Paula: job. Okay. Okay. Yeah. I did the data scientist and she was like, this is, I don't think you're going to, you're gonna spend a lot of effort trying to get a job as a data [00:21:00] scientist.
Paula: And I think you should try data analysts. Mm. I said they're not the same thing, but that's how recruiters see it. They see it, but they didn't, this being this first step. So that was the first, uh, change of mine that I have to take. And then, uh, and then the second guy told me, Hey, you should start applying for small companies around you.
Paula: Mm-hmm. Stop applying like a hundred times a day to this big tax. You know, they're not gonna get you. Uh, I said to say, maybe you're lucky and someone will see you and get
Chris: you. I only one person who did that, only one person, and that same job, started paying $400,000 a year, maybe three years down the line.
Chris: That's only happened to one person. I know.
Paula: Yeah. Like winning the lottery. So he was like, look for small companies around you, you know, uh, apply very specifically, like change your curriculum as you apply for the small companies. See what they want. [00:22:00] Maybe email or the hr, say something. Say that you live close by, that you can swing by if they want to, to talk to you like.
Paula: Not officially. It
Chris: makes so much sense going for a data analyst role despite having more technical skills as a data scientist, right? Or let's say data engineer, you name it, uh, it makes more sense. Gain that first step into the field, right? And then who says you can't go into data engineering after that?
Chris: Or data scientists, right? Who says you can't. Now you have that professional experience in tech. So that, that was very smart and, and that, that makes total sense. I'm so happy that you got that advice. What was your job first and what was your life like before getting a tech
Paula: then? I was also helping with, you know, sales, uh, customers.
Paula: We, I was doing more like the E-com so more like Google Analytics and that kind of, that kind of data. And how was
Chris: life like? Was it pretty hard living, like struggling right. Um, before getting to your first job as data analyst? Well, I
Paula: live in California. I think it's hard to say that we struggled
Chris: here. You look like you live in [00:23:00] Orange County.
Chris: Is that Orange County?
Paula: It, uh, after Orange County's Ventura County is the next one. Okay. Okay.
Chris: Okay. Hey, I was close enough. Yeah. Nice, nice. I I I used to in Orange County. And so like, if, if you don't mind, like what were you making, you don't have to share what you're making now, but what were you making before tech?
Chris: Your last job before being a data analyst?
Paula: I was so it, I was making 65. Uh, wow.
Chris: That's amazing, first of all. Okay. Okay. Sorry, I didn't mean to interrupt you. That just blew my mind. Well,
Paula: here, here, and I say that, but I mean, I'm, I'm 36. I came here, I was 28. I, I mean, I didn't start with 65. I think I start with 40 and then I got to 65.
Paula: Yeah. Okay. And then I got, and then this year it was funny, I, I, I asked for a raise and I got to 70. Mm-hmm. And then I found my new job as a data analyst and does that pay much better? And I actually got, Oh, sorry. No, I actually got a pay cut,
Chris: which that's Which is totally fine though, right? Because Yeah, totally.
Chris: I see it a lot because the analysts I know now make [00:24:00] like around 130, 140 K a year, and then you use industry as transition to a more technical field, like data scientist, data j, name it. Right? And that might take a year or two, if not a little longer, because it's so worth it though.
Paula: No, I was gonna say, I, I, it was the, the, the best pay cut I could ever get because I know it's gonna leave me somewhere, you know?
Paula: That is gonna make me, three years from now, I'll be laughing at it. Can I
Chris: ask you one last question, or do you have to go now? No, I'm fine.
Paula: Okay. Okay, cool, cool.
Chris: Yeah. Looking back then, right, and this is a very important question. Was it worth it when you look at it going through coding bootcamp? Right. Going through that, uh, how do you feel about that now when you look back at your situation?
Paula: I feel like I, my only regret is now I have done it earlier. Ooh. Oh, wish I had, yeah. I, I, I wish I had done this four or five years ago. Would it have been Coding
Chris: Dojo again?
Paula: Probably. I mean, I interview. With four boot camps. I called them and I made me, I had, yeah, I, I really tried to know what I was putting my money, [00:25:00] so I talked to four
Chris: boot camps.
Chris: That's why you made good money. You're so smart. Oh my gosh. I like that.
Paula: And they were very nice at, you know, meeting with me over, uh, the phone or Zoom or whatever and answering me all my questions. And that's why I picked them because, you know, I, and I compare other things too, but, um, Yeah, I, I mean, if I had the same.
Paula: Four interviews back then probably would be. Yeah, I think it was, I would say it would be them.
Chris: I'm so happy for you. Um, this is exciting. Oh, I love these, doing these interviews. Okay, cool. Is there anything else you wanna share with anyone who listens to this in the future and et cetera? Right. Um, the only snippets of this will be in, in the video, but anything you wanna share in particular?
Paula: No, I think just repeating the, you know, your work's not done. Once you're done with your bootcamp, just keep it, you know, you have to, keeping up to dating and looking for the tools you. You believe you're not strong enough. Mm-hmm. And I mean, nothing wrong with [00:26:00] shooting for the stars, but maybe shoot around, you know, some, a little shoot for the moon around
Chris: you too.
Chris: Shoot for the moon. Keep for the moon, right? Yeah. Uh, if not, just the atmosphere a little lower, so. No, I agree. I agree. I understand. Okay. Awesome. Paula. Um, if, do you want anyone to follow you anywhere in socials? Is there anywhere if anyone wants to message you about questions or anything and that they can contact you?
Chris: If not all good. Let's put this part out.
Paula: Yeah. No, it's, uh, I actually, I have me now. I'm gonna be your competition now. Just joking. Okay. Oh,
Paula: I have recorded a few videos about this journey. I just need to edit them and put them out on, uh, on YouTube. So, yeah, I don't know. They, it should be up there at, at some point. Yes, do it. You know
Chris: what, just email it to me and I'll make sure I put the link description so people can check you out too.
Chris: Awesome. It'll
Paula: be
Chris: great. Yeah. Cool. Perfect. All right, Paula, well, I'll let you get back to work or eat your lunch first. So seriously, thank you so much for being on air.

Interview #2: Chris Sean Interviews Mandy (Bootcamp Graduate)

Mandy Full Edit
Chris: [00:00:00] Everyone, welcome to another podcast. In this episode, I have Mandy Sack. Wait, by the way, Mandy Sack, your name sounds so cool. Yeah, thank you. It, it really does. Mandy Sax. Oh, you picked it yourself. Okay. That's an impressive, no,
Mandy: I'm just kidding. Mandy. Mandy is a nickname. It's not my legal name. So the first part, I didn't actually pick myself, but,
Chris: so for everyone who doesn't know this is Mandy.
Chris: And what's really interesting about Mandy is that Mandy went to a coding bootcamp, right? And you graduated from that bootcamp. And now you work in tech. And so this is really interesting and in this particular interview, I really wanna dive into your life before bootcamp, right? Mm-hmm. Now you're in it and then you work in tech, how your life has changed because everyone wants to go through that journey.
Chris: Everyone who wants to go in tech, most of the people I know aren't having that great of a life. And what I mean by that, you know, they're kind of struggling financially or they're not, but the living, they wanna do better in life, right? And so I do know you work in tech now. I do know that you went to a coding bootcamp, right?
Chris: In particular Coding Dojo. [00:01:00] Mm-hmm. But before we even dive into the coding bootcamp, how was your life before that?
Mandy: Yeah, so before this I had an entire other career. Um, I graduated from college with not even a tech, it was technically stem, but I graduated from college with a bachelor in a major event no one else has.
Mandy: It was very special to my college, but essentially my major was doing M R I and nuclear medicine. So not even, I mean, we use computers, but. Nuclear medicine. Yes. So like, um, that's legal. Yeah. Yeah. So PET scans, have you heard of PET scans before? Uh,
Chris: no, but I guess I will. No PET scans.
Mandy: So it's, uh, I won't, I won't go too much into detail, but nuclear medicine is basically using, um, medicine that have nuclear, like radioactive elements to it, but it's actually very safe and they're used a lot for a lot of, um, kind of testing for.
Mandy: Cancer patients or even, even like heart, [00:02:00] like heart function, it does a lot of function versus, you know, MRI X-rays and CT scans are gonna be more just like your body, your anatomy, kind of looking at that way. Yeah. And, uh, a whole career. Does that paywall, like,
Chris: I'm curious, right? Like,
Mandy: Um, there's a cap. I will say that I'm making more right now in an entry level position than I probably would've, like, I wouldn't have made this amount until probably another three years from now if I was still in the same career.
Mandy: And I've been here for over a year now. Man, if I, I mean, money isn't everything as we know. Work-life balance, it's helpful, is super important. It's definitely helpful. But I find that what's very important is non-monetary things, such as work-life balance. Yes. Um, mental health, uh, stress. Just like your, your physicality.
Mandy: Mm-hmm. How you're coming to work. And that was something that come, the pandemic was very difficult [00:03:00] as someone who was still going to work, you know, every day
Chris: in person. And the pay wasn't the best. It was, it was decent. I, I'm assuming it's better than average, right? Yeah. Average salary is like 50, 60 K a year now, I think.
Chris: I don't know. Yeah. Right. So it's better than that, but not good enough. And is that why you decided to Yeah. Go into tech.
Mandy: It was, it really was more of the, I kind of had that. Come, come the Jesus moment if we're gonna say that. Where I just, I just was, was in there. I was working and just in the middle of my shift I just was like, I don't think I can do this the rest of my life.
Mandy: I just kind of had like a moment where I was like, man, like I'm already, I like my wrists are already hurting. Like my, you know, I already feel the sands of time ticking away here. Uh, I can't imagine. So there's no better time than now. That's essentially what I thought. There's no better time than now.
Mandy: Like, let's just get into it. Let's make that
Chris: jump. And it's interesting you bring that up because I, before tech, I remember and I didn't make much. I made around, and I lived in Irvine, [00:04:00] California. Expensive as hell to live there. Mm-hmm. Making around 28 to $32,000 a year. Right. I couldn't afford a apartment, I had to rent a room.
Chris: It was really a closet. Yeah. And I remember accepting, this is gonna be my life forever. I'm never meant to succeed in anything. And it is, I feel so hopeless. Right, but who would've known that? Just not, not around the door. It's like a million doors you have to run through. Right? Yeah. There's that life in tech that could potentially change your life.
Chris: Right. So like, just, just trying to like relate with you because I didn't know. I kind of, I mean, I relate like that feeling of, all right, I can't, I don't wanna do this forever. It can't be this forever. Mm-hmm. This, that's terrible. Mm-hmm. Right. So that's cool. So then you decided to try to go to tech and you started looking around, I'm stealing, right?
Chris: So did you think bootcamp was the only way? Did you try to do the self-taught route?
Mandy: So I. I'm not a patient person. Let's just go with that. So the idea of going to school, getting a master's in some of these things, cuz I, I [00:05:00] look at the job postings of course and some people are asking for a master's, but you're gonna get honestly the same skills, if not better skills.
Mandy: Like you're gonna get more hands on training at a bootcamp than you would going into a master's. Cuz Master's gonna really hone in on that Theory and theory is great. But theory doesn't help you to do your
Chris: job? No, no. I mean, in, in the, at the companies I worked at, unless you're in, um, machine learning, right?
Chris: They want people for doctorate, you name it, double doctorates, whatever, um, uh, no one really cared if you had a Master's or not. I mean, yeah, a degree helps. It always helps, but it's not always, you know, it's not always everything. That's interesting. Okay. So then you chose bootcamp. You didn't wanna do self-taught.
Chris: Yep.
Mandy: No, I, I, I am pretty disciplined, but I also like to have access to people who have more experience because if you do self-taught, you can watch a million YouTube videos, but if you just aren't figuring it out, it's really nice to have access to somebody who [00:06:00] has done this a million times and can explain it a different way and can work with you hands on.
Mandy: That's the part I liked. I liked that they can jump into a Zoom room with you and. Help you through your issues yourself. Cause if you, I mean, we love Stack Overflow, but Stack Overflow can only get you
Chris: so far GBTs here. Oh, no. GBTs here. Uh, yeah, that's true. GBT four, GBT 10 will be around probably next year.
Chris: But, uh, you know, yeah, no, definitely. I, I agree and that makes sense, right. For me, I, I want to self-taught route, but I think I survived a self-taught route because I got lucky. No, it luck. Yeah. And. You know, I, and a lot of effort, but getting a job in three months isn't normal, especially when I don't know Jake Quarry.
Chris: Mm-hmm. JavaScript, css, all I knew was H T L. So, uh, yeah, I kind of got lucky. And then boom, I am where I am today. Right. Because of that. And so, but if it wasn't for that, if it took me a year, if not longer to get a job, I probably would've given up because I would've felt so lost. Yeah. So, [00:07:00] And, and I couldn't go.
Chris: I tried, actually, coding Dojo was a bootcamp I wanted to go to seven years ago. I couldn't afford it. I didn't have the credit for a loan. You name it. Right? Yeah. Yeah. So it's so interesting that I'm interviewing people who attended and so and so, but yeah, so if I, if I didn't do it in the year, I would've given up because I had no guidance or direction.
Chris: Hence why I did my YouTube channel. Mm-hmm. To help people and give them the guidance direction I hope I had. Right. So coding dor then you just chose Coding Dojo, you didn't look at other coding boot camps. How did that happen? Did it, did they send you I did look at coding. Oh, they did? Okay.
Mandy: No. Yeah, I, I looked at multiple, again, I mentioned I'm not a patient person.
Mandy: Um, so they had the shortest one. Theirs was 12 weeks at the time. It's no longer 12 weeks because they've added more to their curriculum, but at the time it was 12 weeks, but they were covering everything that the other ones were. So in my mind, I was like, yo, I'm getting everything I can get into my career faster.
Mandy: And it's cheaper, so it kind of, it's cheaper than college. Added everything together. I was like, let's go.
Chris: How much, how much cheaper in college? How, how much was [00:08:00] it for you when you went to the coding bootcamp? So
Mandy: I believe they had a scholarship opportunity as well, um, for people that were starting a new career.
Mandy: And as well, I think I'm, I hope I'm not confusing it with another one, but there also was like a women's scholarship as well, so. I think at the time it was around $5,000, so it went down to 4,000 for me. I know the prices have changed since then,
Chris: but you were, so you were still working full-time in the medical field while going to a part-time Coney bootcamp is that.
Mandy: How so? It's actually more dramatic than, more dramatic. We're gonna get into that. So it's more dramatic. Oh, sip. Oh God. At the time, um, I tried to actually, the, the start of the bootcamp was overlapping. My mother needed brain surgery, so I was gonna go on leave and I was gonna help take care of her. And so it was gonna overlap so that, um, [00:09:00] when I was gonna be on leave, I'd also be getting through the bulk of the bootcamp.
Mandy: And then what actually happened is my mom unfortunately had complications of her surgery. She was in a coma for two weeks. She was in rehab for a month. So I was doing this camp while including bootcamp camp part-time. Yeah, but driving to the hospital, I was coding on my little laptop, like in a ho I c u room.
Mandy: Uh, and it was, it was stressful. So when people, I've been in other interviews before where they're like, what was the first couple weeks like? And I'm like, I have no idea. I don't remember. It's a blur. I made it. But, uh, it was, it was a very stressful time and, The best part was I, well, maybe not the best part, but I communicated with the instructor.
Mandy: I said, Hey, you know, here's my situation. And they were so understanding, like they're, they weren't gonna, you know, push me aside or feel like, you know, well, she's not turning in her work. I mean, I turned it all in time, but, but they were very empathetic and they understood my [00:10:00] situation and they. You know, were there for me.
Mandy: They said, if you need extra time, let me know. Communicate with me. So they, they understood understanding that there are lives outside of this. We're not just, you know, a, a money to them or anything like that.
Chris: Yeah, no, I mean, that's huge. That's important. I mean, life happens, right? Yeah. But I can only imagine the thought process.
Chris: And, and I think despite going through that, the, the determination to keep going, So I, I'm, I'm a weakling. Yeah. Right. I think that's what, you know, uh, I if, if something like that happened, hey, I'm out, whatever, take my money, I'll come back next year. Right, right. And so the determination to keep going through that, what, what pushed you to keep going then?
Chris: Because you could have, right? I mean, $5,000 for bootcamp is Yeah, definitely could've. I mean, it is a lot. So, sorry. That's a lot for a lot of people, right. So like, yeah. What, what pushed you to keep going through that whole process?
Mandy: I. I think it's [00:11:00] just my, myself, I've kind of always been that way. Um, gosh, I don't mean to be so negative, but like my senior year of college as well, I lost my father.
Mandy: So that was something where I, I lost him, but that same semester, I got a 4.0. Couldn't tell you how. Same thing. It's like I just, when when I'm put in these very hard times, I just push through and that's just kind of how I'm built, I guess. But when the going gets tough, I try three times harder. And it, it might be a coping mechanism maybe, but uh, yeah, I think it's myself.
Mandy: It's knowing that, you know, even my mother, like how she was like, When they want you to succeed. So my mom would probably be upset if I stopped. She would say, why did you do that? You know, like, you should, you should still work hard. Like, I know you really want to get into that new career. Um, so it's just really, I pu I pushed myself for sure.
Mandy: [00:12:00] I'm, I'm my number one critic. Everyone's their number one critic, but I'm also my number one motivator
Chris: that is, ugh. All right. I'm not gonna shed a tear. Uh, that's just it. It's so brave you to be honest. Right. And I'm sure you've heard this a lot already. Thanks. But I also know how hard it is to code. Um, yeah.
Chris: First of all, the situation. Dad and g porno, you're an alien. Like you're not human. That's insane. Like what I mean by that, just I, I, I'm so, I'm, I'm emotional person and I know that. Right. Um, and, and so like I know I couldn't do that. Right. And then now, The only parent you have left going through that situation and then you still pushing through to learn how to code.
Chris: And what I'm trying to say is I know how difficult it is and knowing what course you took. Yeah. It's not for the development, it's data science. You know that. I mean, okay. Both of them are hard. People are gonna kill me now. Right. They're both d difficult, but back in from my experience,
Mandy: oh, coding is another language.
Mandy: It's hard to learn a [00:13:00] language
Chris: and so. You chose the coding bootcamp because you chose Coding Doja. Right. And, and we, I know we went a tangent, but it is mm-hmm. It's just, it's nice to hear your story before all of this. So then I'm curious, right. Yeah. Why did you choose that bootcamp? Why this bootcamp?
Chris: Particular Because they, the part-time, it's part-time and it's cheaper. Mm-hmm. $6,000, 5,000, whatever it cost. How
Mandy: come there's, yeah, there's a lot that goes into it. Money. Money's always gonna be important. It was, it was cheaper. Like if you're doing, you know, price per, per, per day or per week, maybe it is just as expensive if you're thinking it from that point of view.
Mandy: To the other ones in the market. Um, but it was faster. I was ready for a new career yesterday. Like I wasn't trying to take my time. Um, but I also wanted that support. They had the support, they had homework. I'm a proponent of homework. That's the only way you're gonna learn is if you do.
Chris: I'm sure you probably heard [00:14:00] negative things about bootcamp prior to Coney Bootcamp during, even after.
Chris: Um, Are there any, is there anything that you've heard about a coding bootcamp and that wasn't true or things you did hear that did end up becoming a reality that you saw for yourself?
Mandy: Um, so I, I might've been like a earmuffs person. I didn't hear that many bad things, but I think once I got out and I graduated from it, I noticed there is kind of like a.
Mandy: Maybe like a bad reputation. Like it's just like, oh, well they didn't care enough to go to real, real school in quotations or, um, you know, they're just chugging out people. So it is really hard. I will say, I'll be honest, like to assert yourself as someone who doesn't have that degree to back 'em up. Um, To be like, I'm just as good as the other people who have that master's or I know just as much, uh, you really, you really do have to either assert yourself or you just gotta know people.
Mandy: You gotta network. I know it's hard for us [00:15:00] introverts out there, uh, really don't like the networking piece, but that's kind of how it is nowadays.
Chris: No, I agree with that too. Right. Um, to be honest, you're trying to do in a couple weeks, if not a couple months, what people took four years, maybe six years to do.
Chris: Right, right. Not just out to people interviewing. You probably have a CS degree or whatever degree with anything. Mm-hmm. Right. So I think the mistake that people make is thinking bootcamp is enough. It's never going to be just enough. It's a guidance, it's a track that you can follow, yet people could tutor you.
Chris: Yes. But if you only stick to, and I, and please correct me if I'm wrong, cuz I never went to bootcamp, but I, I believe if you only, even if this applies to even college, if you only apply to what you learn in college, um, to your, your technical skills or coding bootcamp, it won't get you far enough. You have to actually go, I think you have to go above and beyond.
Chris: Number one, tech is competitive. There's a reason that I make multiple six figures. Right. And we'll make more right people trying to take me away from my current job because it's competitive as hell. And [00:16:00] you think they're just gonna give that money to anyone else? Mm-hmm. Right? Uh, to just you. So you have to go back and beyond,
Mandy: I, I'll just say walk watching other people.
Mandy: You can do the bare minimum, you can do what it takes just to get through the bootcamp, but I guarantee you're not gonna be prepared. You're not gonna be prepared. You need to take it to the next level. You need to do the extra reading. Like you, you have to, you get, I know it's so cliche, but you do get what you put in.
Mandy: If you're not putting in the extra effort, then you know, I. Best of luck. That's all I'm gonna say. Uh, and besides that too, it, it did take me actually five months to start my new job. I'll, I'll say probably, and I applied to like over 500
Chris: jobs to get a new job. Post-graduation. Yeah. Got five months,
Mandy: yeah.
Mandy: After graduating to bootcamp. So it took a lot of time, a lot of applications out of that, I think I got maybe. Three or four interviews? Uh, not a [00:17:00] lot. Not a lot for that 500. And I was applying to stuff that, I mean, some of 'em, you applied the ones that wanted a master's, but I was like, I'm gonna ignore that.
Mandy: Everything else I have covered. Um, but I wasn't applying to any senior. I, it was all entry level positions. I wasn't going above what I thought I could do. Um, but I'm gonna agree with you. I think that the boot camps and education just in general is a foundation. That's the foundation. It gets you started, it gets you that information.
Mandy: But on the job is really where you're gonna get true skills and where you're really gonna take off your, your knowledge and your skills.
Chris: Oh. What you learn in a job in just one or two months is more what you learn in entire bootcamp, right? Uh, yeah, a hundred percent. It is insane. It, it is it life. I mean, work experience wins every time, right?
Chris: And so I, I agree. And so, okay. Now going back then, right through your, your process, because there are a lot of people right now who are, I don't know if we're in a recession anymore. It feels like it, it's only people are losing their jobs right now in tech. I least in tech. [00:18:00] And so people are are curious about gonna bootcamp or not.
Chris: Right. Go self-taught route. And so how was your experience then going through a bootcamp? Right. Like, okay. I like what you said so far. You said you can't just put in the bare minimum. You get what you, you know, you, you get out what you put into it. I agree a hundred percent. Um, but how was that experience, right, for you personally?
Chris: Um, from the day-to-day course? I'm assuming it was all online on Zoom or something. So how was that experience for you?
Mandy: Yeah. It was all online. Um, they had two live classes. This bootcamp specifically had two live classes a week. So I think mine was Monday, Wednesday, or Tuesday, Thursday, I forget. But two live classes.
Mandy: Um, you had your homework that was due every week. You had, um, what if you don't do your homework? Kind of like a test. Yeah, like an exam. Uh, you don't move on to the next. Wow. You gotta do your homework. You got to do your, you don't move on to the next, to the next section. Yeah. Okay. That's good. That makes sense.
Mandy: Yeah. And then So it's required. Yeah, it's required. Okay.
Chris: Boot camp's not for me. All right. What, what, what else? Yeah. Oh, [00:19:00] shoot.
Mandy: Uh, yeah, you'd have, you can have exams after each section that's just gonna test your knowledge. So they really, I mean, you probably noticed you can get away with things via copy paste.
Mandy: You can, I'm judging, that's what I mean by the bare minimum. Like you. Yeah, chat. G p t might, might, uh, might kill the boot camps. We'll see. No one's actually gonna know how to do anything themselves. It's just all chat G p T. But, um, yeah, a a lot of homework, the exams, uh, the live courses. And then you, we had TAs and I even became a TA right after graduation.
Mandy: Nice too. Just like while I was waiting for my, they paid for that, my full-time job.
Chris: Yeah. I guess they pay. Yeah. So,
Mandy: Hmm. They pay you to be Oh, yeah. Yeah. It was paid. It was paid ta. Yeah, because it was after you graduated. It wasn't like how it is in school where they're like working on their PhD or something.
Mandy: Like you were your own contractor. Um, and so you had access to TAs too. So while you were doing homework, if you got stuck, like one of [00:20:00] them could help you out. The instructors, if they were free, could help you out. Um, I will say, even though it was part-time, uh, it, it's. Hard if you are working a full-time job, like even the part-time ones, it's really hard to balance that cuz part-time, if you think of it like what part-time is is 20 to 30 hours a week still.
Mandy: So it's, it's its own job for sure. It,
Chris: it's, and I think that's what kind of weeds out the people who want it and people who don't. Right. People who just want everything to be given to you and people who are willing to work for it. And, and, and I kind of applied that to like working out, because now I'm finally losing weight, thank God.
Chris: Um, I've always worked out whenever I felt like, only when I felt like it. Now I'm gonna set schedule. I count all my cal, like I measure everything. Like it's, it's funny, but now I'm losing like a lot of weight, like, like 10 pounds a week now. Right. And, but like, The reason I wasn't losing weight before when I tried to do this in the past is because I wasn't willing to put in that extra effort to like really count, [00:21:00] measure everything.
Chris: Mm-hmm. Really makes you push yourself when you work out. The consistency of that. Even when I travel before work and I travel a lot, um, but because I, I don't want to die and I wanna live past 40. Right. And so I'm determined like crazy and, and if I wasn't, I'd continue like being lazy and getting a lot of weight.
Chris: Right. And that's not good for me. And, and, and that applies to everything else. Mm-hmm. Especially I think in coding, because we make so much money, you cannot fake your way into a, a tech job. You have to really be willing to like really go 20%. Wow. Okay.
Mandy: Yeah. And I know this is, this is kind of mean, but that is one thing is.
Mandy: I know that people like to be optimistic and say, you know, anyone can do this. But to be honest, I, I don't think that's actually true. There is a certain level of kind of computer skill and insight and just kind of, kind of critical thinking that you have to have. And some people have it and some people [00:22:00] unfortunately don't.
Mandy: Um, so I think you do have to be kind of honest with yourself. Before jumping into any of these careers and know is this, is this something that I can actually, you know, do? Like, is this something, am I gonna be able, because it's not just take it to the next level in your bootcamp or in your education, you're gonna have to do that every single day.
Mandy: You're always gonna have to think of new ways to approach things of, you know, creative solutions or, Kind of pulling from other techniques, from other kind of fields to do what you need to do. I
Chris: agree in a way where, yes, it's not for everyone, but I, I do think that when it comes to the critical thinking part, that can be learned why that was me.
Chris: Right? So about me, I say this in every video because I'm so proud of it. I was in special ed, I'm slow as hell. I have dyslexia. Um, but I was in special ed because my brain, I was born in six months rather than nine. So it took me, [00:23:00] Longer to develop my brain. Mm-hmm. Much longer. I mean, that's men in general, but for me, unfortunately, it was longer than usual.
Chris: Right. And, and, and so, and, and I think for me personally, it took me time to learn all, all of that. And, and I think what didn't help was knowing, okay, I was in special ed. Okay. I, I dropped outta these colleges. Okay. I suck at everything. And I, I definitely think it's a confidence factor or people who can guide you, but yeah.
Chris: Yeah. I think that's it. It could be, I think it could be learned, but more than anything though, If you're not willing to put an effort when you don't understand something, you just give up if you're not willing to really push through. Yes, because it gets hard. Oh my God. When I was, I mean, I, I am a developed African now, but when I was a software engineer, it is hard.
Chris: I have a, a friend here at my current job, and he's a senior sophomore engineer. He came in Twilio. He's insane, and he was required to solve a problem. He knows nothing about. The only way he can solve it was buy book and read the entire book. I'm like, dang. So every night, during the day, on the [00:24:00] weekends, he's reading this entire book to learn something he doesn't know nothing about.
Chris: So he can fix that problem. Right. That's not easy. And I don't think just anyone can do that because I even, I don't want to do that. No way. I don't wanna do that. But, uh, no, that's just right. I don't do that. Right. So it's, it's totally different. Right. Um, so yeah, I definitely do agree with that part. And so,
Mandy: No.
Mandy: Yeah, you're, you're right. I, I think there is an intention piece as well. You have to want to, want to do it. I think critical thinking is a want as well. You have to want to think about it critically. Cuz I, I have some people I work with where they just say, oh, this is how it is. It's not working how it is.
Mandy: And they're just like, guess it doesn't work. Like they don't want to, they don't want to. Look into it or think of it a different way if you don't know, like maybe you don't have that knowledge piece yet, but you want to look into it more. I think that's critical thinking. If you, if you want to learn more about it, like you have that intention, you're thinking there is a way to do this.
Mandy: I just don't know. [00:25:00]
Chris: Still done talking about this for some people who are interested and want to attend a bootcamp. What should they be prepared for, right? Mm-hmm. What do you want to maybe warn them about but also maybe art and also be ready for, you know, this is gonna be great in some different aspect?
Mandy: Uh, that's a great question. So I would say be ready to not know, and sometimes that's okay. Because like you said, it's, you're on a, you're on an accelerated pathway. If it's the stuff that in like week two, three, cuz all this stuff at least in mind, builds upon each other. If it's week two and three that you're having a hard time grasping on, that's a problem.
Mandy: But if it's week like 11 out of 12 that you're having difficulty grasping, that's probably fine. Like that's, you've had all this information mush in your head in the last 10 weeks. So like it's okay not to understand something the first time you hear it. [00:26:00] And as long as you have that foundation in the beginning, you'll figure it out one day, I promise it might be a couple months later when you're finally in the field, you're working and all of a sudden you're like, oh my gosh, I understand convolutional neural networks now, just like while I was in school.
Mandy: No idea. I'm just getting through. But, uh, It'll hit you. It'll hit
Chris: you. Would you? Or if you, you know what? If you were to start over, if you were to start over, would you do it again? Yeah,
Mandy: I would do it again. Okay. Especially because the reason I have my job today is because one of the TAs. Got me this job.
Mandy: So I created that. What, like I said, it's like built in networking. Like I, I did my above and beyond I cr I developed a relationship naturally. I didn't have to go on LinkedIn and stalk somebody and say, Hey, I see you're doing X, Y, Z, I wanna do X, Y, z. I didn't have to do any of that. I naturally made a relationship.
Mandy: She saw me [00:27:00] struggling. She was like, Why aren't you employed yet? And she said, let me pull some strings. Let me see what I can do. And honestly, that's, that's more beneficial than I feel like anything. It's developing those relationships and even your fellow co like cohort mates. So maybe one of them gets a job first.
Mandy: They see an opening on their team. They say, Hey buddy, are you still working for a job? Like, let me see what I can do. Let me get you in. They, if they hired that guy right. Then they're obviously fine with boot camps. They're fine. So there you go. You, you just continue on the chain of helping each other.
Mandy: Yeah, and we need more of that.
Chris: Networking is everything. I have a friend who was gonna apply to another job. I told him, don't work there. I wanted him to work in my company. Alright. He was a, a support engineer, not a, like a software engineer yet. And so I just asked for his resume. I want, I'm just curious, lemme see your resume.
Chris: And I applied to, at my company for him yet, no [00:28:00] idea. And then the recruiter reached out to him, he said, Hey, thanks for applying, you want to interview you? Um, right. And, and, but what I'm trying to say is, I think network is everything but Ian, for the introvert like you, you made friends. Right. And that helped you win, get a job five months after bootcamp.
Chris: Yep. So you didn't find a coding bootcamp then through Coding Dojo? It was through networking. Um, was there anything wrong on coding Dojo's and Right? Was there some, did the, did they not look long enough? How did that at the time,
Mandy: like the, yeah, like I said, when I went through was different than today. So back then they didn't have any career services.
Mandy: So now they do. Oh, it was, I think even like two cycles after me. They had it, but I didn't have that. So that was just something where, you know, at the time I didn't have the support. It was kinda like good luck. Um, so yeah, just a lot of LinkedIn, LinkedIn job searches, [00:29:00] and I, I also really wanted that work from home life.
Mandy: And as, as you can see, I'm working from home. I got my dog next to me over there. Uh, that's the best. It's a game
Chris: changer. It's in those five months in before getting a job. How are those emotions? You are, you are working full-time still. Your mom was sick. Um, I'm assuming still sick cuz we can't visit that long during that process.
Chris: Right. Um, you're trying to push through that five months. No job. Five months, I'm assuming over a thousand applications, if not thousands. I don't know. Right. Um, especially during that time. There were, there were a lot of jobs at
Mandy: that time. There were a lot of jobs. That's one thing too, that I am a little bit more cautious maybe about the boot camps at the moment because the layoffs, um, unfortunately the new people are usually the first ones, and so I am, I am kind of a little cautious just about entering the workforce right now.
Mandy: I do agree with you. I think, I think things are gonna slowly get better, but we just don't know when that is. [00:30:00] Um, but if I'm thinking back, so go back to your original question. I went on a tangent, but I think I got my job offer in, so I graduated in October of 2021 to do the timeline. Um, and I got my job offer, I think mid-February 22.
Mandy: And then my job didn't start until March. Of 22, end of March 22. So given that it kind of was like more like four months before a job offer occurred, but um, also because of Covid, the background checks were so backlogged that they were like, we can't start you because Oh wow, that's interesting.
Mandy: Background checks are taken six weeks to come back. Yeah. So, yeah, it was a weird time. It was. And then
Chris: those four months, then were, were you nervous that No, like month number one comes by? Month number two, number three. Like, were you worried, were you stressed out? Like, why is no one hiring me? What were your thoughts?
Chris: Were [00:31:00] you thinking, did you have, I'm assuming we didn't. I'm sure everyone does. What did I waste my time? Right, with the bootcamp?
Mandy: Definitely stressed out. Um, yeah, like you said, first month or two, no big deal. You know, sometimes this time take time. You know, I have no experience basically. So like it's, it's not like.
Mandy: My first career where I had, you know, being in a medical field, we had clinicals. So we did have experience kind of working on the job. We had built those relationships. I said, I'm in a new world here. Uh, I understand it's gonna take a bit for the industry to trust me or to really like break into it. Um, yeah, come, come Mum three, mum four.
Mandy: Definitely like, man, what did I do? Did I just uproot and ruin my life? Um, you have those thoughts cuz I did actually even quit my job. I got a little bit excited. I quit my job. I had like a part-time job on the side, but it was just like I said, you quit your job after
Chris: coding bootcamp. [00:32:00]
Mandy: I, I did, but that was because of actually during it, technically just, just the stress.
Mandy: That job was so stressful, so toxic. I said, I gotta get outta here for me, um, I kept like a couple, like, like a, they call it PRN in the medical field and it's like a pickup shift job. So I kept one of those. So I had a job. I wasn't completely unemployed, but, um, yeah, I was like, oh man, what did I just do to myself?
Mandy: Uh, and. Thankfully it worked out, but I would not suggest quitting your job before securing a new job. That that would be my advice to other people. Even if it's toxic, that's
Chris: okay. That's one thing I can criticize about you right there. Yeah. Don't do that. Yeah. That was no, but yeah. Oh, then that was have been stressful then
Mandy: because I had savings.
Mandy: Right. I wouldn't, I wouldn't have done it unless I had savings. I said I have savings for the next six months. Even if I can't get a job, I've, okay. Okay. Over two jobs on the side, like I, but two months I made sure left. Yeah. So it was getting, it was getting close there. [00:33:00]
Chris: Yeah. Yeah. I could, I, I could only imagine looking at that backing count.
Chris: Right. Um, I mean, I'm sure a lot of people feel that now with the layoffs, so. Okay. And you know what, we didn't even go over, so you went through the data science cl track in Coding Dojo. Does that mean you were trying to be a data scientist? Data engineer? Data analyst? What was your original intention or what was your original goal during bootcamp?
Chris: What was the job you were looking for?
Mandy: So that's actually another reason why I picked this one as well. I went to an open house and I spoke with one of the instructors, and I asked her, I said, why should I do your bootcamp? Why should I do a data science one versus a data analytics one? Because we're cheaper.
Mandy: I'm just, I'm just blunting to the point like that. Yeah, no, she said, so data science, she's like, data science will cover more. You have more options. You could go all these different routes, data analytics, you're gonna get. That's. You can do data analytics. That's it. Um, so I'm working as kind of a data, data analytics slash engineer capacity [00:34:00] at the moment.
Mandy: Um, so I haven't broken into the data science aspect yet, but No worries. Because I chose data science, it kind of opened up a lot of avenues for me and,
Chris: and, and the front end field. Right. And I'm kind of glad I don't work as a front end developer no more. It is extremely competitive. And when I say extremely competitive, there's just more people learning it, right?
Chris: I, I, I would, let's say if we're making up a number four to one, you know, like. Let's just say a thousand people applying to one job for a data scientist, probably 4,000 people applying to one job for a fund developed position. Right? It is. That's what everyone tends to go through because that's just more popular in internet right now.
Chris: Right. Um, and so I'm really glad I work in data space. So right now you work as a data analyst slash engineer you said. Mm-hmm. Um, and before that then, I'm curious bef I want to dive into that. Well, we only have a couple minutes left. Sure. But how did it feel to get that job offer? You worked your ass off.
Chris: You
Mandy: quit your job, [00:35:00] especially at the company I'm at Uhhuh. Yeah, especially
Chris: at the company you're at. Oh, you said you work for a big four company.
Mandy: It was, yeah, big four financials. So I didn't even, I'm not a financial person. I didn't go to school for finance, so I didn't really know it was a big deal. I like had Googled it and I was just like, all right, it's a job.
Mandy: Like I can't be picky right now. Like they're gonna pay me money. Um, and they even offered me more than I asked for, which I was, isn't that the best? Cool with That was all right. Yeah. That's amazing. Yeah. I was like, okay, that's
Chris: the best. Wow. That
Mandy: felt nice. Now, of course I'm like you. I'm like, okay, when's my race?
Mandy: Yes. When's my raise? I want, oh my gosh. But, uh, just cause I know I can, cause I know, I know they would potentially in theory, but, uh, yeah, it was a great feeling. It was a great feeling knowing, you know, someone. Well, also, it was great to know that someone, you know, my, my previous TA was vouching for me, and that in itself was a great feeling knowing someone vouched for me and that, and if [00:36:00] it's a, a larger
Chris: FinTech company were Yeah, that, that's impressive.
Mandy: So I was, I was pretty happy. I, yeah, I was like, I don't know what I'm gonna do. And honestly, it took. Probably five or six months to actually know what I, what I did. Um, it does take a while. People would say, what do you do for work? I'm like, I don't know. I just,
Chris: I just do, I just show up. I just do, I do stuff look productive.
Chris: Yeah. Just do stuff. Especially when you work from home, it's hard. You have to really show your productive, right? Yeah. Um, how do you feel knowing that in tech? Yeah. Your career is know. I mean, it depends on how much work you wanna put in. Their responsibilities you want is nowhere but up. Uh, that's how it is in tech.
Chris: Literally no. Nowhere but up. Yeah. Unless you just want to go down. Yeah. How does that feel for you then, now that you're working in tech? And I will
Mandy: say, yeah, so this being my second career too, it's not like I, like I bring a lot of soft skills to the table. Like I've already been through a whole career. I know how to assert myself.
Mandy: Yeah. Like, like you know how to have a conversation. Unfortunately, there are some people [00:37:00] coming outta college, they just haven't built that confidence yet. So when they're put in a room with people, they're like, Uh, you know, they, they don't have that experience yet. That's soft skills. That's gonna come over time, just the more you put yourself in those situations.
Mandy: Um, so that was something like already they're just like, all right, dude. Like you learned all, all of the hard skills. Your soft skills are already up to date. Like you're ready to climb the ladder already. And I've been at my job, you know, a little over a year and. Although unfortunately the promotion cycle is very fixed in the financial world, so I, I do have to wait till a certain time to get promotions, but they're already like, yeah, dude, you're ready for a promotion.
Mandy: Like, we just have to unfortunately wait for time to pass. Yeah. That's how it is in, in the financial world for sure. Even, even the first year. Yeah, so, so I think, I think when, this is like your second career and stuff, you're really set up for success because people are gonna see you as more of their peer because you have that life experience.
Mandy: No,
Chris: I, I agree. And I, I think that's what helped me a lot. [00:38:00] Right. I, I am not the most technical person. I know that for a fact. But my soft skills, um, the ability to speak despite me having dyslexia and speaking, and I had a, what do you call it? Speech impediment when I was younger, um, most of my childhood, high school, college.
Chris: Yeah. And now that's my job. I, I'm the main person in my company that travels the world and speaks at these larger conferences, small conferences, you name it. Yeah. Kind of crazy. And, and it really, in what I've learned from my experience up to today is that we set the limit to what we can do. Right. And don't allow yourself to say, you can only do this.
Chris: You can only do that. No, you could do so much more. It really depends on how you're willing to work. And so how has your life changed now post tech? I mean, not post tech, post bootcamp, post medical field. How do you liken your life now? Work-life balance is great. I'm assuming how, I mean you, I'm sure you had great health insurance at the medical field, but how is that now?
Chris: How has your life
Mandy: changed? Yeah. Um, definitely I think, I think the mental health is, is much better. I think just that work from home aspect, um, the flexibility is so much [00:39:00] better because it's not like, it's not like healthcare. Like when you go into healthcare, it's okay, we have, we are open, you know, retail, all that.
Mandy: We are open from these hours. That's when you work versus now it's like, oh, I got a doctor's appointment. They're like, okay, cool. See ya. It's, it's amazing. And I don't have to commute, so we don't have to factor that in. It's just, I leave from my house, I go, I come back to my house. Um, it's, I really like, I mean, I, my dog is not my emotional support dog.
Mandy: I'm her emotional support human. But I love having my little buddy next to me all day, you know, when I have a weird meeting. Yep. She's sweet. She's taking a nap right now.
Chris: My dogs are right behind me this morning. I took a two hour walk. Right. I'm doing this one hour interview right after this. I'm gonna work out.
Chris: It'll be one, one o'clock by the time I'm done working out. Done No work yet. Right. And and, and they're paying. But you'll get it all done today. Well, I did. I got it done yesterday. Yeah. So I'm kind of chilling today and tomorrow, but tech life. [00:40:00] Right, right. Um, I feel that, I feel that and getting paid more than pharmacists and doctors, which is insane.
Chris: Right. So the tech le, and again, you have to work for that though. It wasn't like this for me, my first four years in tech, not at all. Right? So I had to work my ass off and I still do. I do, but just for half the week now. I hope my boss isn't watched this. No. But yeah, so that is amazing though. Oh gosh, Mandy, sax, I'm so happy for you.
Chris: Seriously hearing about your journey where you are today. Um, is there any last words you wanna share if anyone that made it to the end? Any last thing you wanna tell them who are maybe be considering bootcamp or maybe they don't want to do bootcamp? Whatever you wanna say.
Mandy: I would say just it's cliche.
Mandy: Just like if you wanna do it, just do it. You know, Shiloh buff said it said it best in front of the green screen, you know, just do it. Yesterday you said tomorrow. Just do it. You know, you got, you gotta just, just take that leap because if you keep holding yourself back, you're gonna, you're going to be on the other side of [00:41:00] that moment.
Mandy: I had right where I, I had that moment. I said, I can't do this for another 30 years, but you could be on the other side that you could be 30 years done in the line. You look back and you're like, man, I could have done this 30 years ago. And so, you know, just. Yeah, it's never, it's never too late. I mean, I'm, I'm still young.
Mandy: Like I did, I didn't, you are young. Way too long. I don't think, I think I had perfect timing. Yeah, I got the baby face. But, um, that's one thing too that does happen in my workplace because I got the baby face, cuz I have the entry level. You know, sometimes people don't know what they're getting into. Uh, when they talk to me, they're like, oh, look at that little, little thing she just got out of college.
Mandy: No, like, I got a whole, I will, I will tell you what's up. So they're always very shocked when they learn, you know, how much life knowledge I have and how much I'm I. How hard I work and kind of just my, well with all about the world. And also I wanted to comment too, um, just I myself also have a speech [00:42:00] impediment, so I just love that you are like, out here, you've had all that history and you speak for a living, right?
Mandy: Yeah, it's crazy. Um, like I remember being in like theater class in, in high school and my theater teacher like called me out and he was like, You'll never have any, like any chance speaking in front of people or anything because you have, you can't speak words. Right. Right. And just that, that killed me inside and I, I.
Mandy: Went into a shelf for a while, and that's maybe why I, I chose like a career. I did. I chose one that's kind of in the, in the background, and I've gotten over that as I've gotten older. And now, you know, half of my job is, is speaking to clients and speaking to people. And I definitely don't care anymore if, if, uh, You know, it, my speech impediment comes out, you know, it is what it is.
Mandy: But yeah, it's easy. I just wanna thank you for kind of being out here and being yourself. I
Chris: love it. Oh, I appreciate that. Um, definitely wasn't easy, [00:43:00] right? It was a lot of, you know, hiccups in my life too, and I'm very, I am very lucky to be around. I mean, it's a lot of hard work, but also Wow. Uh, I know how many people would do anything to be in a position I'm in today, so I'm not taking for granted.
Chris: Um, one thing I wanna bring up, are you a gamer? Because you, you have the, those are those razor headphones. Got the, you had the gamer chair, gamer headphones? No, they're corer, of course. Okay. It was either that course air course, right? Yep. What game do you play? If
Mandy: you wanna know? So, my real origin too, um, I used to play World of Warcraft hardcore.
Mandy: I was a guild master, like. Four years. Um, no longer. Yeah. Super nerd. Super nerd. Now I'm playing Tune town, so that's kind chill of where, where I've ended
Chris: up. I'm a, I'm currently a holy priest in my guild. That's good. I'm the best healer in the team in the guild. Also, I, I'm a monk, brewmaster 10. Oh, of course.
Chris: But, um, I unplugged my gaming pc, threw it on the couch, right? And I'm like, no. Because the last three months have did nothing. Nothing. And so I had to, I [00:44:00] had to keep up and go back to living life. And so, no, what a Warcraft.
Mandy: It becomes a job. It becomes a job. And that's why I quit as well. It doesn't
Chris: help you in your life.
Mandy: Right? That's why I quit as well. I was like, man, I'm getting so stressed out about this game. Yes, I pay money for like, why? Why am I letting play the,
Chris: I've done longer play. Yeah. The community aspect's amazing. It's amazing. Um, but oh yeah, no, I just, I can't do that no more. Um, yeah. Okay. This was amazing. I know we we're almost at time.
Chris: So, seriously, Mandy, thank you so much. Um, you've been great.

Interview with coding bootcamp graduates.

Chris Sean 🪐 — Wed, 17 May 2023 04:34:48 +0000

Interview #2: Chris Sean Interviews Mandy (Bootcamp Graduate)

How To Become a Web Developer in 6 Months

Chris Sean 🪐 — Fri, 27 Aug 2021 16:18:34 +0000

Do you feel stuck with your dead end job? Do you feel you've been stuck with your job for as long as you can remember? What if you took risks in changing your careers? What if today is the day you make the decision to change your life for the better? Well in today's blog I am sharing how I would become a web developer in 6 months.

When you aim to become a web developer in six months, it doesn't mean you need to be an expert to a junior web developer. Getting a position like this in six months sounds impossible, but it all depends on how hard you're willing to work.
There are many aspiring developers out there who give up before they even start simply because of the below requirements, which include but are not limited to:

● HTML
● CSS
● JavaScript
● SASS
● LESS
● jQuery

And the list can go on and on. When people see these requirements they immediately think they're not qualified because they think they need to master everything to land the job. But that couldn't be farther from the truth.
What companies look for in a junior web developer, they’re not looking for someone who knows everything, because even I myself, who’s been in this industry for 5 doesn’t. What they look at are these three things:

Do you fit the culture?
Do you have potential?
Do you have passion?

If you have all three, the chances of you landing the job will increase significantly. So let’s prove to companies that you won’t only fit the culture, but also how you even have the potential and passion to succeed. Many believe that people are born of potential, but potential is shown through hard work and results.

What to learn in months 1-2: HTML,CSS and JavaScript

First, watch tutorials on how to do HTML,CSS, and JavaScript through YouTube or any medium you have available to you. Expect that you will forget everything that you learn. It’s okay. This is normal.

Your main goal here is to see HTML,CSS and JS works. You’re goal is not to master it. This is because you will never truly understand any of it until you get professional experience.
The amount of time you should be studying is three hours a day. Becoming a developer in a year or six months is not easy

whatsoever. It’s not supposed to be. If it was, anyone would do it. But you’re not just anyone. You want this. You’re willing to do whatever it takes. That’s why you're going to need to dedicate all your time and energy to learning. Even if it means you can only study 1 hour a day. Life happens. Just work around your schedule. You can do it.

What to do in month #3: Build Landing Pages using HTML, CSS and JS

So tutorials have been fun. They truly help build a foundation as a new developer. But, now is the time to stop depending on tutorials. You do not want to end up in tutorial hell (Tutorial Hell is when we finish a tutorial with a sense of learning and knowledge, only to chain another one after the first. Or the second. Or the fifth. And if you dare to try to write code for yourself, you feel overwhelmed. You don't know where to start or even what to do).

Now instead of depending on tutorials, it's time to put what you learned into practice by building landing pages. I suggest building a total of 3 pages to help show potential employers that you are willing to go above and beyond to show your passion for code. Don’t even worry if you forgot all of the code you’ve learned. That’s normal. Now act like a REAL developer and meet your new best friend for help: Google!

Just like developers today, if you run into any problem and feel stuck, just Google it. There will almost always be a solution. Trust me, there is not one developer in the world that doesn't use Google today. The most important thing here is that you have the mindset of not giving up and remain persistent in finding a solution, even if you don't understand what you're doing.

What to do in month #4: APPLY TO JOBS NOW

Now that you have created three landing pages, it's time for you to start applying to jobs everywhere.

Now you might be saying 'Why would I apply so early, I've only been doing this for three months, I need more experience'. That may be true, but by the time you get "more experience", the jobs that are open right now will be gone in a month, if not in a couple of weeks.

Say that you applied to a job thinking that you don't have a chance, but what if they actually get back to you? Just like that you have an interview.

My friend Leighanne is now an intern for a small web developer firm. I’ve been mentoring her for five months. And after only five months of learning code, she got her first job as a web developer. She barely knows javascript yet. But still, they gave her the opportunity simply because of her potential.

I’ve heard so many stories of this happening all around the world all the time.

But, if you don't land the job, guess what? You still get something out of it. You have just gained experience as an interviewee. Now you know what you don’t know. And now you know what you need to know to make sure you can do better next time. This a learning experience. Don't let rejection steal your thunder, it's normal. And you have nothing to lose by applying. JUST APPLY.
Apply for a job with the mentality that there is a chance you will be hired, not vice versa.

As the famous saying goes: "You'll never know unless you try".

Month #5: Learn How To Use GitHub

Whether you're hired at this point in time or not doesn't change the fact that learning how to use GitHub is essential. GitHub is where you can upload your code for the world to see (such as potential employers). You will show them that you know the basics of making commits, pull requests and it will also allow them to see your growth over the last 5 months.

These are things that developers do on a daily basis and multiple times in a day, so learning how to do this, on your own even, is mandatory. So later when you have an interview and the employer finds out that you learned to do all these things, they're going to think "what more if someone with experience teaches him?". The company benefits from hiring you and you landed a job as a developer. Everybody wins.

Month #6: Learn How To Work With Databases

Being a developer means you will eventually work with a database, so you're going to need to learn the basics in things like manipulating data. This may seem intimidating at first. It is. But it is easier than you realize. With consistent effort you can learn things like SQL in a matter of 2-3 weeks.

Now after following this schedule for 6 months, one thing I can assure you, is that future employers will not only see your dedication, but it will push them to the point where they would be stupid to not hire you. Everyone has their own style of learning, so don't stress yourself out if you can't follow this to the letter. As long as you have the drive to become a dev and the mentality to not give up despite what happens, you will make it.

I know people who have become devs in 2 months. I also know people who never gave up and reached their goals in 2 years. So don’t be too hard on yourself. Don’t compare. Remember, Rome wasn't built in a day.

What I Learned After Studying Python For 30 Days

Chris Sean 🪐 — Tue, 24 Aug 2021 19:47:30 +0000

What I learned about myself

For the last 30 days, I have been practicing Python.

You know, like meditating for 30 days straight. Why? Because no one is born knowing how to "think" in a programming language – at least not that I am aware of (if you are please email me). So, like learning any other technology, to become proficient you need to practice. A lot. For most people, this means doing the same thing over and over until it becomes automatic. Like when you learned how to ride your bike or touch type (man do I suck at typing). To practice Python there are numerous online courses, books, blogs & video tutorials; however, my goal was not simply to learn about Python but rather hone my craft as a developer. What I came to realize is that there were certain learning patterns that applied to virtually all technology. So, without further ado here are some things I learned after studying Python (in no particular order):

Everyone Thinks Differently

Everyone thinks differently: It's true – everyone does think differently. Your first language may be one way but not everyone in the world learned it your way. I'm still trying to wrap my head around Python because it doesn't seem to follow a set pattern like other languages (i.e C#). I'm really bad at this; however, practice makes perfect and with time even this will get easier…right?

There are reasons some developers are better than others: A few explanations include preferred learning patterns, active listening skills, level of attentiveness & most importantly desire. This doesn't mean that everyone who is better than you is a bad person. We all have different skillsets and ways of thinking about life but the more I progress in my career the more I realize how much thought and planning goes into some really simple code.

Learn How To Learn

Learning how to learn is more important than learning itself: This has nothing to do with Python but everything to do with being a developer. As you start your career, the number of technologies and frameworks you will encounter will be staggering. For example, it's highly likely that in the next 5 years you may use 20 to 30 different languages (not counting re-implementations). That means learning as many patterns as possible because without them we would all just be trying to solve problems using trial and error – this is bad!

Your brain is a muscle and needs to be exercised! This may sound like a marketing pitch for a new program but it's true. The more you think the better your mind will become at doing so. As developers we need to challenge ourselves, not just with code but mental feats as well; i.e puzzles, riddles or anything else that requires some thought. This will sharpen your mind thereby helping you learn faster and longer.

Learning is as important as experience

Oftentimes, developers know how something works right away but it's not until they start to understand why it all comes together. We tend to think about technology like a hammer (i.e just use it). To be proficient, we need to know what makes up the hammer (i.e understanding the parts) so that when someone asks us to "make" something we can do so with confidence and effectiveness.

Learning is a lifelong journey: Practice may make perfect but don't expect proficiency overnight because that would mean you never get better and even if you did at first, time moves on and things change. For example, if you wanted to learn to dance the Jitterbug then that's what you would do for a while until someone asks you to teach them how or better yet, if someone wants to know how you did something? To become a master at anything, one must dedicate their life to it and Python is no different!

Learning python may not have been my sole intention; however, learning about myself and improving as a developer was. Now that I've started down this path there's no turning back (at least for now).

Skip Any And All Shortcuts

There are no shortcuts: To quote my favorite movie ever "The Last Samurai", "There's a right way to do things and there's a fast way to do things – let me teach you how to do it right." So many developers want results yesterday. I'm not against short cuts, in fact they are needed, but what I am saying is that if you learn through shortcuts alone (tutorial hell) then you will be lacking the necessary fundamentals to advance your craft.

Learning new technologies too quickly can inhibit the growth of a great programmer: As developers, we have infinite opportunities in front of us. This means more languages, frameworks, technologies, techniques, and ways of doing things. While this is exciting the more we learn too quickly the harder it will be to connect all of the dots later on. Take your time to advance through trial-and-error; ask yourself why you are using this technology or approach sooner than later and try not to overthink it.

Learning must begin with fundamentals: Leave the new technology to last. If you do not have a solid foundation, it's like trying to build a house on top of quicksand. The first thing we all need is to understand why and how things work, only then can we think about applying this knowledge in other areas.

Practice Makes Perfect

No one is born knowing how to program, which is why it takes so long for children to learn our native language. However; with practice and repetition the process becomes more fluid and at some point, they no longer think about what or how to say something – it just comes naturally. So after 30 days of nearly non-stop Python, I'm still not a genius (unfortunately) But, I noticed that when it comes to programming languages, they are so much easier for me to grasp now. Plus, the more you practice coding and write down your thoughts the easier it is to remember what went wrong (and right).

When I first started programming, every time things would go wrong I'd get frustrated. Nowadays, if an error occurs I'm never fazed because I know that these are necessary steps along the way. We're all human, so expect to make mistakes. Additionally, I've learned how to learn from them and grow from them.

Making mistakes is part of the learning process: It's okay to make mistakes, everyone does and if someone tells you they haven't then it's most likely a lie. So why do we fear them? We learn from our mistakes by looking back on what went wrong in an attempt to spot patterns or problems that need to be lessened to avoid repeating those mistakes again in the future. Small victories are key: While bigger picture goals (i.e goal-oriented projects) are important, I've found that focusing on smaller ones helps me see how fast I can get results without being overwhelmed (which, we should never be).

I'll admit, my first project taught me more than 30 days of practice combined. However, this doesn't mean it was a bad idea and I'm glad I jumped in headfirst. Smaller projects will get you more accustomed to the development process as well as show you how much improvement you've made over time (or how much you still have left).

You Do Not Need To Be A Genius

You do not need to be a genius to learn Python. I have a feeling that this is one of the most common misconceptions about learning how to code, as it's been my experience that anyone can learn how to do anything with enough practice and guidance.

And even if you learn something at a slower pace there is still nothing wrong with that.

Learn as much as you can about the language (and be critical about it): This was perhaps one of my biggest mistakes, specifically when I started learning code. I would read through tutorials and copy/paste any code samples without fully understanding how or why it worked the way it did. For example, I've often heard comments like "you'll learn that later on" or "That's just how Python works," which may be true or untrue but accepting these excuses will eventually hold you back from truly mastering Python.

Knowing how and why things work is what will help you expand your knowledge of the language. You're not bad at coding simply because you don't know everything, but admitting to yourself that you need to improve (and learn) will keep you moving forward in a positive direction.

Finally, after 30 days of reading & studying Python what was the most important thing that I learned?

Python is a beautiful language

I'm not saying that because it's my favorite…I'm saying that because I truly believe it. I have come to understand and appreciate the beauty of whitespace, as well as the importance of writing self-documenting code and using clear variable names. It's the little things that you'll come to appreciate after spending enough time with a language (and, by extension, develop a love for).

So I urge you all to have fun learning code. Don't be hard on yourself or compare yourselves to others. Just try new things & keep practicing!

Happy Coding! :)

Chris Sean
Developer Relations Engineer @ New Relic.
Check out and sign up for New Relic here :D

Python - The Not So Good Parts

Chris Sean 🪐 — Mon, 23 Aug 2021 16:48:12 +0000

Learning is an ongoing process: Although it's nice to know that there are some things we don't need to worry about when learning Python, they are few and far between. In the beginning, there were so many things I didn't understand that it felt like learning a new language all over again; however, with each passing day, I noticed my skills improving at a rate of knots. This isn't because I spent hours upon hours studying, but rather because I applied what I'd learned every chance I got.

Python can be frustrating:

Python and I didn't get along in the early days. There were several times when I nearly threw my laptop across the room in frustration but I reminded myself that learning a new language is more than just memorizing every single key command or function; it's about understanding how they relate to each other as well as what you can do with them. Frustration is natural, so don't be discouraged by it – embrace it!

If you feel yourself becoming frustrated, stop what you're doing and go do something else. You might come back to that task with an open mind and renewed enthusiasm.

What I find frustrating about Python is that it feels like a "quick-fix" solution to my programming problems. I can often find the answer to my problem with one google search and then apply a few lines of code. This is great during the early stages, but I've found that trying to implement this way of thinking into a larger project can be almost impossible.

Python is space sensitive:

Unlike other languages, Python is very particular about things being written in certain ways aka very space sensitive. This was extremely confusing for me at first, but I quickly learned to pay close attention to what I was typing. If a command or function didn't work the first thing I checked was my spacing.

Spacing is not the only thing that Python is sensitive about. There are actually several rules to follow and they vary from function to function… which can be extremely frustrating when you're trying to apply a function in one line but it refuses to work just because of space!

Python is lean:

While I'm not going to go into detail regarding this topic, I'd like to mention that Python (in case you're not aware) supports multiple versions of itself at the same time. Essentially, this means you could have two or more versions of Python installed on your computer without causing any issues.

For example, I've got both versions 3 and 2 running at the same time – The only difference is whenever I need to use one over the other (like for older projects that require Python2), I'll swap by using a command-line prompt/terminal.

In short, this means you can have the best of both worlds with regard to project support and having access to anything that's relevant at the time.

In Conclusion

Overall, Python isn't a bad language – It's just different to what I was previously used to. It took me a while to get used to its quirks and way of doing things. With time, patience and a little hard work, Python is definitely worth the investment!

If you're interested to learn more about Python I'd recommend taking a look at treehouse which is what I used to help me get my first developer job in 3 months.

Chris Sean
Developer Relations Engineer @ New Relic.
Check out and sign up for New Relic here :D

I Studied Python Everyday For 30 Days

Chris Sean 🪐 — Thu, 29 Jul 2021 05:16:18 +0000

What I learned about myself

For the last 30 days, I've been practicing Python.

You know, like meditating for 30 days straight? Why? Because no one is born knowing how to "think" in a programming language - at least not that I am aware of (if you are please email me). So, like learning any other technology, to become proficient you need to practice. A lot. For most people, this means doing the same thing over and over until it becomes automatic. Like when you learned how to ride your bike or touch type (man do I suck at typing).

To practice Python there are numerous online courses, books, blogs & video tutorials; however, my goal was not simply to learn about Python but rather hone my craft as a developer. What I came to realize is that there were certain learning patterns that applied to virtually all technology. So, without further ado here are some things I learned after studying Python (in no particular order):

Everyone Thinks Differently

It's true - everyone does think differently. Your first language may be one way but not everyone in the world learned it your way. I'm still trying to wrap my head around Python because it doesn't seem to follow a set pattern like other languages (i.e C#). I'm really bad at this; however, practice makes perfect and with time even this will get easier…right?

Learn How To Learn

Learning Is As Important As Experience

Learning python may not have been my sole intention; however, learning about myself and improving as a developer was. Now that I've started down this path there's no turning back (at least for now).

Skip Any And All Shortcuts

To quote my favorite movie ever "The Last Samurai", "There's a right way to do things and there's a fast way to do things - let me teach you how to do it right." So many developers want results yesterday. I'm not against shortcuts, in fact, they are needed, but what I am saying is that if you learn through shortcuts alone (tutorial hell) then you will be lacking the necessary fundamentals to advance your craft.

Take your time to advance through trial-and-error; ask yourself why you are using this technology or approach sooner than later and try not to overthink it.

Practice Makes Perfect

No one is born knowing how to program, which is why it takes so long for children to learn our native language. However; with practice and repetition the process becomes more fluid and at some point, they no longer think about what or how to say something - it just comes naturally. So after 30 days of nearly non-stop Python, I'm still not a genius
(unfortunately). But, I noticed that when it comes to programming languages, they are so much easier for me to grasp now. Plus, the more you practice coding and write down your thoughts the easier it is to remember what went wrong (and right).

Making Mistakes Is Part of Learning

It's okay to make mistakes, everyone does and if someone tells you they haven't then it's most likely a lie. So why do we fear them? We learn from our mistakes by looking back on what went wrong in an attempt to spot patterns or problems that need to be lessened to avoid repeating those mistakes again in the future.

Small victories are key: While bigger picture goals (i.e goal-oriented projects) are important, I've found that focusing on smaller ones helps me see how fast I can get results without being overwhelmed (which, we should never be).

I'll admit, my first project (AI/ML) taught me more than 30 days of practice combined. However, this doesn't mean it was a bad idea and I'm glad I jumped in headfirst. Smaller projects will get you more accustomed to the development process as well as show you how much improvement you've made over time (or how much you still have left).

You Do Not Need To Be A Genius

And even if you learn something at a slower pace there is still nothing wrong with that.

Finally, after 30 days of reading & studying Python what was the most important thing that I learned?

Python Is A Beautiful Language

So I urge you all to have fun learning code. Don't be hard on yourself or compare yourselves to others. Just try new things & keep practicing!

Happy Coding! :)