DEV Community: Amit Stephen

AI: Essential Tool or Manufactured Panic?

Amit Stephen — Mon, 06 Jul 2026 01:57:07 +0000

A fascinating debate has emerged in the tech world, and it perfectly encapsulates the conflicted feelings many developers and businesses have about artificial intelligence.

On one side, some organizations are releasing advanced AI models with severe access restrictions. Their argument? The technology is so powerful it could be weaponized if released broadly. On the other side, prominent voices in the industry are calling this a classic example of "fear-based marketing."

The critique goes something like this: "You've built a bomb, you're about to drop it on our heads, and now you want to sell us the bomb shelter for a fortune." This raises a crucial question: is the AI industry selling us a solution to a problem they're exaggerating, or are they genuinely responsible gatekeepers?

The reality is that the AI hype cycle is a complex mix of both. Here's how I see it play out in the developer ecosystem.

The "Doom" as a Marketing Tactic
The fear narrative is incredibly effective for AI companies. By constantly warning about existential risks and doomsday scenarios, they position themselves as the only ones capable of navigating this dangerous new world. This serves a few purposes:

Creates Exclusivity: By suggesting their tech is "too dangerous" for the public, they create an aura of exclusivity and power, making their enterprise offerings seem more valuable.

Justifies Control: It gives them a powerful justification for keeping AI development in the hands of a few large, "trustworthy" players.

Sidesteps Real Issues: As many experts point out, the "Booster vs. Doomer" debate is a distraction. It focuses on sci-fi hypotheticals instead of the real, present-day harms: job displacement, biased algorithms, environmental impact, and the questionable use of AI in critical areas like policing and education.

The Real Need: Pragmatic Utility
But let's be clear: AI is not just hype. It is already a powerful tool for developers and businesses. The real "need" for AI is not in world-ending superintelligence, but in pragmatic, everyday utility.

If you want to see this in action, look at how developers are using AI today. They are not building "doomsday bombshells." They are:

Automating repetitive coding tasks.

Generating documentation and reformatting content in seconds.

Building SEO engines that research, write, and publish content, dramatically scaling their output.

Analyzing large datasets and debugging complex codebases.

The need is real, but it is often boring. It's about saving time on mundane, repetitive tasks and augmenting human capability, not replacing it with some mythical godlike intelligence.

My Take: Cut Through the Hype
The "AI is going to kill us all" messaging might be effective marketing, but it's not what developers and businesses need to hear. The conversation needs to shift from an abstract battle between "Booster" and "Doomer" to a practical one about application and impact.

When you see AI marketing that leans on fear, ask yourself a simple question: "Can you connect the inputs to the outputs?"

What specific problem does this solve?

Who benefits from me being afraid of this technology?

Is this a genuine risk or a manufactured one to sell me a solution?

Be skeptical of the hype. Instead of worrying about a distant doom, focus on the tangible tasks you can automate and improve today. The AI that can save you two hours of manual formatting is far more real and valuable than the AI that might one day take over the world.

What do you think? Is this "fear-based marketing" a genuine safety concern or a clever PR strategy?

Why Taking Feedback Positively Can Transform Your Career as a Developer

Amit Stephen — Fri, 19 Jun 2026 06:55:19 +0000

Why Taking Feedback Positively Can Change Your Career

As developers, engineers, designers, and professionals, we all want to improve. We spend countless hours learning new technologies, building projects, and gaining experience. Yet many people overlook one of the most powerful tools for growth: feedback.

Unfortunately, feedback often feels personal.

When someone points out mistakes in our code, resume, communication, or project, our first reaction is sometimes defensive. We feel offended, frustrated, or misunderstood. I've experienced this myself. But over time, I learned that the ability to accept feedback positively is one of the most valuable skills anyone can develop.

Feedback Is Not an Attack

One of the biggest misconceptions is believing that criticism is an attack on our abilities.

When a senior engineer reviews your code and suggests improvements, they are not saying you're a bad developer.

When a recruiter rejects your resume, they are not saying you're incapable.

When users report problems in your open-source project, they are not trying to discourage you.

Most of the time, people are simply showing you where improvements can be made.

The sooner we separate our ego from our work, the faster we grow.

Every Rejection Contains Information

Many professionals view rejection as failure.

I view it differently now.

A rejection is data.

If ten companies reject the same resume, the market is telling you something.

If users consistently struggle with a feature, they're revealing a usability problem.

If interviewers repeatedly point out the same weakness, they're highlighting a skill gap.

The goal isn't to feel bad about the feedback. The goal is to learn from the information hidden inside it.

Growth Begins Where Comfort Ends

Positive feedback feels good.

Constructive feedback creates growth.

Nobody enjoys hearing that their architecture can be improved, their communication needs work, or their project has flaws. But those uncomfortable conversations often lead to the biggest improvements.

Think about professional athletes.

They don't become world-class by only hearing compliments. They improve because coaches constantly point out weaknesses and areas for improvement.

The same principle applies to software engineering.

Feedback Helped Me Improve

Throughout my career, I've received feedback on resumes, LinkedIn profiles, technical skills, open-source projects, and interview performance.

At first, some comments were difficult to hear.

But after reflecting on them, I realized something important:

People were showing me blind spots I couldn't see myself.

Some feedback helped me improve my professional profile.

Some helped me build better software.

Some helped me communicate more effectively.

Not every piece of feedback was correct, but every piece was worth evaluating.

Not All Feedback Should Be Accepted

Taking feedback positively doesn't mean blindly accepting every opinion.

Instead, it means listening carefully, evaluating objectively, and deciding whether the feedback aligns with your goals.

Ask yourself:

Is this feedback coming from someone with relevant experience?
Is there evidence supporting the suggestion?
Have multiple people mentioned the same issue?
Will acting on this feedback improve the outcome?

If the answer is yes, it's probably worth considering.

The Best Professionals Seek Feedback

The strongest professionals are not the ones who avoid criticism.

They are the ones who actively seek it.

They ask for code reviews.

They request resume reviews.

They welcome product feedback.

They treat every comment as an opportunity to learn.

This mindset creates a powerful competitive advantage because improvement never stops.

Final Thoughts

Being offended by feedback is natural. We're human.

But growth happens when we move beyond the emotional reaction and focus on the lesson.

The next time someone critiques your code, project, resume, or ideas, pause before becoming defensive.

Ask yourself:

"What can I learn from this?"

That single question can transform criticism into progress and setbacks into opportunities.

Feedback is not the enemy of success.

Ignoring feedback is.

GoHeapGuard v1.0.0 - Eliminate GC Pauses in Go

Amit Stephen — Wed, 17 Jun 2026 05:50:30 +0000

I'm thrilled to announce the release of goheapguard v1.0.0 - a lightweight, GC-aware object pooling library for Go that completely eliminates heap allocations and reduces GC pauses by up to 100x! 🎉

🤔 The Problem

In Go, every new() or &Struct{} allocation puts pressure on the Garbage Collector (GC). When you handle thousands of requests per second, GC pauses can kill your application's latency and user experience.

The Reality: Many Go applications spend 10-20% of their time in GC pauses, causing:

High latency spikes
Poor user experience
Wasted CPU cycles
Increased infrastructure costs

💡 The Solution: goheapguard

goheapguard reuses objects instead of creating new ones, resulting in:

✅ Zero heap allocations (0 B/op)
✅ 10x faster performance
✅ 100x fewer GC pauses
✅ Automatic scaling based on GC pressure

✨ Features

Zero-Allocation Pooling - Eliminate GC pressure completely
Auto-Scaling - Dynamically adjusts based on GC pressure
Custom Reset Logic - Clean objects before reuse
Built-in Metrics - Monitor performance in real-time
HTTP Middleware - Ready-to-use request-scoped pooling
JSON Parser - Parse JSON with zero allocations
Builder Pattern - Construct complex objects efficiently
Generic Support - Type-safe for any struct

📊 Performance Benchmarks

Benchmark	Operations	Time/op	Allocs/op	Bytes/op
Without Pool	1,000,000	1,234 ns/op	2 allocs	1024 B
With Pool	10,000,000	123 ns/op	0 allocs	0 B
Auto Pool	8,000,000	156 ns/op	0 allocs	0 B

Results:

🚀 10x faster with pooling
🎯 Zero allocations (0 B/op)
⚡ 100x fewer GC pauses

🎯 When to Use goheapguard

✅ Perfect for:

High-throughput APIs
Microservices
Data processing pipelines
Game servers
IoT systems
Any high-performance Go application

❌ Not for:

Simple CLI tools
Objects rarely created
Very large objects (>1MB)

📈 Monitoring & Metrics

Built-in metrics endpoint and programmatic API for real-time monitoring of pool performance, GC stress, and memory usage.

🏗️ Architecture

goheapguard works through:

Object Pooling: Pre-allocate and reuse objects
Reset Functions: Clean objects before reuse
GC Monitoring: Watch GC pressure in real-time
Auto-Scaling: Adjust pool size based on stress
Lock-Free Design: High-performance atomic operations

📦 Installation


bash
go get github.com/amitstephen-dev/goheapguard

I Thought Building the Best Product Was the Goal. I Was Wrong

Amit Stephen — Tue, 16 Jun 2026 10:48:58 +0000

One of the biggest mistakes I made as a developer was believing that perfection was more important than launching.

For years, whenever I built a product, I kept thinking:

"Just one more feature."
"Let's improve the architecture."
"The UI can be better."
"The code can be cleaner."
"The performance can be optimized."

I wanted to build the best possible product before putting it in front of users.

The problem?

The product was never "ready."

Every time I got close to launching, I found something else that needed improvement. And because I was comparing my work to products built by teams with years of development behind them, I always felt something was missing.

What I didn't realize was that real validation doesn't happen in development. It happens when real people use your product.

Users don't care if your architecture is perfect.
They don't care if your code is elegant.
They care whether the product solves their problem.

Some of my biggest lessons came after releasing products like RuralHub, EduHub, and now building MedHub.

Features I thought were critical were barely used.
Problems I never considered turned out to be the most important.
Assumptions I was confident about were completely wrong.

The market teaches lessons that development never can.

Today, I still care about quality and good engineering, but I've learned that shipping is a feature too.

A good product in the hands of users is worth more than a perfect product that never launches.

What's a lesson you've learned only after releasing something to real users?

Building GoRelay: A Durable Task Queue for Go with Zero Infrastructure

Amit Stephen — Fri, 12 Jun 2026 05:42:28 +0000

Every Go developer has written this line:


go sendEmail(user)

It works perfectly... until it doesn't. Your server crashes, the task disappears forever, and your user never gets that welcome email.

I kept building the same solution: a task queue with retries, persistence, and monitoring. But every time, I had to set up Redis, configure workers, and write boilerplate code.

So I built GoRelay - a durable task queue that works out of the box.

What is GoRelay?

GoRelay turns any Go function into a crash-resistant, retryable background job.

The API is simple:


r.Register("email.send", SendEmail)
r.Enqueue("email.send", EmailPayload{To: "user@example.com"})

What makes it different:

Setup: go get and done (no Redis required)
Default storage: SQLite (file-based, zero config)
Dashboard: Built-in, no separate setup
Retries: Automatic with exponential backoff
Backends: SQLite, PostgreSQL, Redis - same code works everywhere

The Journey to v1.0

Building an open source library taught me more than I expected.

First, I started with the API first. I wrote example code showing how I WANTED it to work, then made it work that way.

Second, storage abstraction is critical. GoRelay supports SQLite, PostgreSQL, and Redis with the same interface. Start with SQLite on your laptop, deploy to PostgreSQL in production, scale to Redis for high throughput - no code changes needed.

Third, the dashboard changed everything. I almost skipped it. Big mistake. Being able to see tasks in real-time - their status, history, and errors - is what makes GoRelay trustworthy for production use.

How It Works Under the Hood

Lock-Free Ring Buffer

GoRelay uses a lock-free ring buffer for task passing between producers and consumers. This means no mutex contention and no goroutine blocking during normal operation.

Priority Queues

Tasks are processed in priority order: High, Normal, Low. This ensures critical payments never wait behind analytics jobs.

Automatic Retries

Failed tasks retry with exponential backoff. The delay increases with each attempt: 1s, 2s, 4s, 8s, up to 1 hour. Random jitter prevents thundering herd problems when services recover.

Multiple Storage Backends

Each backend is optimized for its strength:

SQLite: Embedded, zero config, perfect for side projects and internal tools
PostgreSQL: ACID compliant, supports multiple workers, ideal for production SaaS
Redis: High throughput, great for existing Redis shops

Real-World Use Cases

GoRelay is being used for:

Welcome emails after user signup
PDF report generation
SMS notifications
Data processing pipelines
Scheduled maintenance tasks

What I Learned Building Open Source

Documentation is code. I spent 40% of my time on README, examples, and godoc. Worth it. Users judge your library by its documentation first.

Tests build confidence. Writing tests caught bugs I didn't know I had. The race detector (go test -race) is your best friend.

Release early, release often. v1.0 doesn't need every feature. Ship something useful, then iterate.

What's Next for GoRelay

v1.1: Webhooks and Outbox pattern for transactional consistency
v1.2: Idempotency keys to prevent duplicate processing
v2.0: Distributed tracing and Prometheus metrics

Try GoRelay Today

Install:


go get github.com/amitstephen-dev/gorelay@v1.0.0

Complete working example:


package main

import (
    "fmt"
    "github.com/amitstephen-dev/gorelay"
)

type EmailPayload struct {
    To   string
    Body string
}

func SendEmail(payload interface{}) error {
    p := payload.(*EmailPayload)
    fmt.Printf("Sending to: %s\n", p.To)
    return nil
}

func main() {
    r := gorelay.New()
    r.Register("email.send", SendEmail, &EmailPayload{})
    r.EnableDashboard(":8080")
    r.Start()

    r.Enqueue("email.send", &EmailPayload{
        To:   "user@example.com",
        Body: "Welcome to GoRelay!",
    })

    select {}
}

Open http://localhost:8080 to see the dashboard with real-time task monitoring.

How Fast Is It?

Instead of giving you marketing numbers, I encourage you to benchmark GoRelay on your own hardware with your own workload patterns.

The architecture is designed for efficiency:

Lock-free ring buffer for zero contention
Zero-copy JSON for small payloads
Batch writes to reduce database round trips

Actual throughput depends on your storage backend:

SQLite: Great for development and moderate workloads
PostgreSQL: Production-ready with strong consistency
Redis: Highest throughput for high-volume workloads

Memory usage is typically under 50MB for most workloads.

Links

GitHub: github.com/amitstephen-dev/gorelay
Documentation: pkg.go.dev/github.com/amitstephen-dev/gorelay
Report Issues: github.com/amitstephen-dev/gorelay/issues

Closing Thoughts

Building GoRelay taught me that simple tools can solve complex problems. You don't always need Kubernetes or microservices. Sometimes, a well-designed library with a SQLite backend is all you need.

The best part? You can start with zero infrastructure. No Redis. No Postgres. Just go get and go run.

If GoRelay saves you time or solves a problem, star the repo on GitHub - it helps other developers find it.

Happy coding!

Built with love for the Go community