DEV Community: its_hayder

Top 7 APIs for SaaS Development in 2026 (I’d Actually Use These)

its_hayder — Thu, 27 Aug 2026 17:39:32 +0000

7 APIs I’d Use in a SaaS in 2026

I've built enough small projects to learn one annoying lesson:

the code you don't want to write is usually the code that ends up taking the most time.

You start with a simple idea.

"I'll just build a SaaS that does X."

Then X needs Google OAuth.

Then it needs Stripe.

Then you need background jobs.

Then email.

Then some way to connect to your users' other tools.

Then analytics.

Three weeks later you've built everything except X.

So I started paying more attention to the services that handle this stuff for you.

Not random APIs that return the weather in London.

Actual infrastructure that can save you from spending a weekend building something nobody will ever pay you for.

Here are 7 I'd seriously consider using in a SaaS in 2026.

1. Nango

If you're building B2B SaaS, integrations are going to find you whether you like it or not.

You build a CRM.

Someone asks for HubSpot.

You add it.

Someone else asks for Salesforce.

Then Google Calendar.

Then Slack.

Then Microsoft.

And suddenly you're maintaining a collection of OAuth flows that you never wanted to maintain.

Nango is built for this.

It gives you a way to connect your application to third-party APIs without having to build every integration yourself.

They currently support hundreds of integrations, including a lot of the APIs you'd expect a B2B product to eventually need.

What I'd build

A tool for sales teams that connects to their existing stack and pulls everything into one place.

Something like:

HubSpot ─┐
Slack ───┤
Gmail ───┼──> Your SaaS
Calendar ─┤
Notion ───┘

The interesting product isn't "we connect to 900 APIs."

The interesting product is what you do with the information after you've connected them.

That's where I'd spend my time.

2. Firecrawl

I've written enough scraping code to know that scraping is one of those things that looks incredibly easy until you actually have to maintain it.

The first version is:

requests.get(url)

Cool.

Then the website uses JavaScript.

Then the HTML changes.

Then there's pagination.

Then Cloudflare.

Then you realize the page you need isn't even in the initial HTML.

Firecrawl is basically infrastructure for getting useful information from websites without having to build the whole scraping stack yourself.

You can crawl and scrape websites and get the result in formats that are actually useful for applications.

And there's a free tier to experiment with.

A SaaS I'd build with it

Competitor monitoring.

Give the app 5 competitors.

It checks their:

pricing
product pages
changelog
documentation
blog

Then tells you when something changes.

Not:

"Here's a scraped website."

But:

"Your competitor increased their Pro plan from $49 to $69."

That's something a company might actually pay for.

3. Polar

Getting people to pay you is a surprisingly complicated engineering problem.

You don't just need a "Buy" button.

You eventually need subscriptions, customer management, invoices, webhooks, refunds, taxes, usage and a bunch of other things you didn't think about when you started.

Polar is interesting because it's built specifically around monetizing software.

And one thing I like about the direction they're taking is that they're thinking beyond checkout.

If your SaaS uses expensive infrastructure, knowing your revenue isn't enough.

You also want to know:

How much does this customer actually cost me?

That's a much more useful number.

Something I'd build

A simple revenue + infrastructure-cost dashboard for indie hackers.

Not another giant enterprise analytics platform.

Just:

MRR
Customers
Churn
Revenue / customer
Infrastructure cost
Actual margin

Because $10k MRR sounds great until you discover you're spending $8k serving those customers.

4. Trigger.dev

This is one of those services you don't really appreciate until you build something that needs it.

Let's say a user clicks:

Generate my report

Your application now needs to:

fetch data from several APIs
process it
generate a PDF
upload the PDF
send an email

You probably don't want one HTTP request sitting there doing all of that.

You want a background job.

Trigger.dev is built around this kind of work.

You can run long-running tasks, schedule them, retry them and build workflows without having to start by building your own job infrastructure.

A good use case

Automated reports.

Every Monday morning:

Fetch data
   ↓
Process it
   ↓
Generate report
   ↓
Save it
   ↓
Email customer

Nobody needs to be awake at 8 AM.

The application just does it.

This is the kind of infrastructure I like because it removes an entire category of problems instead of adding another feature to my stack.

5. Unkey

This one is mostly for people building APIs.

You launch an API.

You give users API keys.

Then you realize you need to answer questions like:

How many requests did this customer make?
What's their limit?
Can I revoke their key?
Who is abusing the API?
What happens when they hit their quota?

You can build all of this yourself.

I wouldn't.

Unkey handles API keys, rate limits and usage-related infrastructure.

The SaaS idea

A developer-focused API platform where someone can:

Create API
    ↓
Generate keys
    ↓
Set limits
    ↓
Track usage
    ↓
Charge customers

The actual API is still yours.

Unkey just handles the part around it.

And honestly, this is exactly the kind of boring infrastructure I'd rather outsource.

6. Resend

Email is boring.

Which is exactly why I don't want to build it.

A SaaS needs emails for basically everything:

verification
password resets
receipts
notifications
invitations
reports
alerts

Resend gives you an API for sending transactional email without making you deal with the usual email infrastructure headache.

The API is simple enough that sending an email can basically become:

await resend.emails.send(...)

That's what I want from infrastructure.

I don't want to think about it.

I want to send the email and go back to building my product.

The free tier is also enough to experiment with a small project before paying for serious volume.

7. PostHog

This is probably the one I'd install and forget about until I needed it.

Then six months later I'd realize it was one of the most useful things in the entire stack.

Because after you launch a SaaS, you start making guesses.

"Users probably want this."

"Nobody uses this feature."

"People are dropping off during onboarding."

Maybe.

Or maybe you're completely wrong.

PostHog gives you product analytics, session recordings, feature flags, experiments and other tools for understanding what's actually happening inside your product.

The free usage is pretty generous for a small project too.

The useful part

You can answer questions like:

1,000 people signed up

↓ 720 completed onboarding

↓ 310 used feature X

↓ 74 came back the next week

↓ 12 became paying customers

Now you have something to work with.

That's much better than sitting in a Discord server saying:

"I think users don't like the onboarding."

The stack I'd probably end up with

If I were starting a B2B SaaS tomorrow, I wouldn't necessarily use all seven.

But a stack could look something like:

Nango
  → integrations

Firecrawl
  → web data

Trigger.dev
  → background work

Unkey
  → API access

Resend
  → email

Polar
  → payments

PostHog
  → analytics

And that's kind of the interesting thing about building software in 2026.

You don't have to build every layer.

You can spend your time on the thing that makes your product different.

If you're building a CRM, don't spend two weeks building OAuth.

If you're building an API, don't spend a week writing rate limiting.

If you're building a reporting product, don't build your own job queue.

If you're building a paid product, don't reinvent billing.

Use the boring stuff.

Build the interesting stuff.

If I had to pick only 3

For a new B2B SaaS, I'd probably start with:

Nango integrations are painful.

Trigger.dev background work becomes necessary very quickly.

PostHog you need to know what users are actually doing.

The rest depends heavily on the product.

And that's probably the bigger lesson here.

Don't pick your stack because someone on X said it's the "2026 SaaS stack."

Pick it because you have a problem and someone already solved that problem better than you can solve it in a weekend.

That's a much better reason to add a dependency.

What are you using in your SaaS right now that you'd never build yourself?

12 AI Tools People Are Using to Make Money (2025 Edition)

its_hayder — Wed, 03 Sep 2025 09:29:02 +0000

Here are the AI tools that people are turning into real money-makers right now:

1. Beautiful AI :
Create sleek slideshows in minutes, then sell redesign services for boring decks.

2. Suno AI :
Produce studio-quality music instantly, from brand jingles to Spotify hits that earn royalties.

3. Vubo AI:
Pump out viral vertical videos in under a minute, growing faceless channels, promoting products, and landing sponsorships.

4. Browse AI:
Scrape and monitor websites without coding, building lead lists, selling data reports, and tracking competitors.

5. Chatbase:
Build custom chatbots trained on your data, sell them to businesses, or boost your own sales with 24/7 support.

6. Instantly AI:
Send cold emails that actually land in inboxes, driving affiliate sales, generating leads, or selling outreach services.

7. OpusClip:
Chop long videos into TikToks, Shorts, and Reels, then sell clipping services to influencers and businesses.

8. Indexly AI:
Get websites indexed on Google/Bing within hours, grab fast traffic, or resell “rapid indexing” services.

9. Fireflies AI:
Auto-record, transcribe, and summarize meetings, saving hours and impressing clients with detailed call notes.

10. TryAtria:
Study winning ads, find inspiration, and craft high-converting campaigns.

11. Higgsfield AI:
Turn photos into videos, generate avatars, and create eye-catching content for marketing and social media.

12. StealthGPT AI:
Write human-like text that passes as undetectable, for school work, business reports, and professional copywriting.

This list was inspired by a Reddit post I found:
https://www.reddit.com/r/Entrepreneur/comments/1n4a3wx/i_scraped_25k_comments_to_find_which_ai_tools/

LEAKED: Senior Developer's $200K Code Review Template - Used by FAANG Companies

its_hayder — Tue, 12 Aug 2025 17:02:45 +0000

Code reviews are a vital part of software development they help ensure quality, catch bugs early, and improve maintainability. But how do you systematically approach a code review to cover all important aspects?

Here’s a practical prompt designed for experienced software engineers, tailored to deliver a thorough and constructive review of any code snippet:

You are an experienced software engineer, expert in {{language}}.

Please review the following code:

Consider the following aspects:

Code quality and adherence to best practices
Potential bugs or edge cases
Performance optimizations
Readability and maintainability
Any security concerns

In your output:

Provide a summary overview of the general code quality.
Present the identified issues in a table with the columns: line number, code, issue, and solution.
If no issues are found, briefly state that the code meets best practices

Top 7 Free MCP Servers in 2025 to Supercharge Your AI Apps — Open Source & Ready to Use

its_hayder — Wed, 06 Aug 2025 15:18:27 +0000

The Model Context Protocol (MCP), developed by Anthropic, is an open standard that connects Large Language Models (LLMs) to external tools and data, making AI workflows smarter and more efficient. For developers seeking free MCP servers to enhance their applications, here’s an improved, concise list of top free MCP servers in 2025.

These servers are reliable, open-source, or offer free tiers, perfect for building powerful AI-driven solutions.

Filesystem (Official, GitHub: modelcontextprotocol/servers)
A robust server for secure file operations, supporting read/write actions with fine-grained access controls. Ideal for integrating local file systems with your LLM for tasks like data processing or logging.

Fetch (Official, GitHub: modelcontextprotocol/servers)
Fetches and converts web content into LLM-friendly formats. Perfect for real-time web scraping, data extraction, or pulling articles for analysis, all optimized for AI consumption.

Memory (Official, GitHub: modelcontextprotocol/servers)
A knowledge graph-based persistent memory system that stores and retrieves context across AI sessions. Great for maintaining conversation history or building long-term memory for your LLM.
Weather (Community, GitHub: wong2/awesome-mcp-servers)
Connects to the AccuWeather API’s free tier to deliver real-time weather data. Use it to add location-based weather insights to your AI applications, like travel or event planning tools.

Wassenger (Community, GitHub: wong2/awesome-mcp-servers)
Enables WhatsApp automation via a free-trial tier, allowing your LLM to send messages, manage chats, or create notification systems. Ideal for communication-driven AI workflows.

Calendar (Community, GitHub: wong2/awesome-mcp-servers)
Integrates with calendar APIs (like Google Calendar’s free tier) to manage events, reminders, or schedules. Perfect for building AI assistants that handle time-sensitive tasks.

Search (Community, GitHub: wong2/awesome-mcp-servers)
A lightweight server for querying search engines (e.g., DuckDuckGo’s free API) to fetch real-time information. Great for adding web search capabilities to your LLM without heavy costs.

Pro Tip: Most of these servers are open-source and can be hosted locally via Docker or directly from the MCP Servers Repository on GitHub.

Stop Paying for ChatGPT Plus: This Free AI Codes Better Than GPT-4

its_hayder — Mon, 04 Aug 2025 23:44:16 +0000

Discover why developers are switching to this powerful, open-source AI that rivals premium coding assistants
Are you tired of hitting usage limits on ChatGPT? Frustrated with subscription fees for AI coding assistants? There's a game-changing alternative that's completely free, incredibly powerful, and specifically designed for developers: Yi-Coder-9B-Chat.

What Makes Yi-Coder Special?

While ChatGPT is a general-purpose AI that happens to code, Yi-Coder was built from the ground up with one mission: to be the ultimate programming companion. Here's what sets it apart:
Purpose-Built for Coding:
-Trained specifically on massive datasets of high-quality code
-Understands 52+ programming languages fluently
-Excels at complex algorithmic thinking and software architecture

Completely Free & Open Source

No subscription fees or usage limits
Available on Hugging Face for immediate use
Full transparency with open-source licensing

Lightning-Fast Performance:

-9 billion parameters optimized for efficiency
-Runs locally or in the cloud
-Instant responses without API rate limits

Real-World Performance That Rivals Premium Tools

Yi-Coder isn't just another "free alternative" – it's a legitimate competitor to paid services:
Code Generation: Creates clean, production-ready code across multiple languages
Bug Fixing: Identifies and resolves complex issues with surgical precision
Code Explanation: Breaks down complicated algorithms into understandable steps
Refactoring: Optimizes existing code for better performance and readability

How to Get Started (It's Ridiculously Easy)

-Visit Hugging Face: Head to the Yi-Coder-9B-Chat model page
-Try the Demo: Test it directly in your browser – no signup required
-Deploy Locally: Download and run on your own hardware for maximum privacy
-Integrate: Use the API in your development workflow

BREAKING: Free AI API Keys 2025: 3 Secret Platforms Replacing Paid Services

its_hayder — Sat, 12 Jul 2025 23:07:53 +0000

Stop Paying for AI APIs: Here’s What You’re Missing

If you’re still paying for AI API keys, you might be wasting money.
I used to do the same, paying monthly fees for something that’s now free elsewhere.

Here are 3 platforms that give you powerful AI access for free, no credit card needed:

1. Google AI Studio
Think of it as Google’s AI playground.
You sign up in minutes and get an API key that works with top-tier models like Gemini 2.5.
No rate limits (within reason), no billing surprises. It’s perfect for testing ideas, building prototypes, or even launching small-scale apps for free.

2. OpenRouter
This one’s like an AI buffet.
With one account, you get access to 50+ models, including DeepSeek, Qwen, and Kimi.
What makes it great:

No need to manage multiple keys

Easy model switching

Ideal for comparing outputs and performance

Perfect if you're experimenting or just want variety without the hassle.

3. Groq
Speed is the name of the game here.
Groq gives you lightning-fast inference for smaller models like Llama, Mistral, and DeepSeek.
I built a chatbot with it for a friend’s site. Zero lag, instant responses, smooth experience.

Great for anyone who wants low-latency AI for real-time apps.

5 Free ChatGPT Prompts 99% of Users Don’t Know About

its_hayder — Wed, 02 Jul 2025 00:21:00 +0000

Want to get more out of ChatGPT without doing extra work? These 5 simple prompt tricks are all you need. Just add a keyword, and ChatGPT instantly knows what you want. No long instructions. No guessing.

1. ELI5: Make it Super Simple

If you’re confused about something, let ChatGPT break it down like you’re 5 years old.
No fancy words. No complicated ideas.
📌 Just type: ELI5: [your topic]
You’ll get a clear, easy explanation anyone can understand. Great for learning fast.

2. TL;DR : Quick Summary

Got a long article or message you don’t feel like reading?
📌 Just type: TLDR: and paste the text after it.
ChatGPT will shorten it for you in a few lines.
Perfect when you want to know what something says—without reading all of it.

3. Jargonize: Sound Smart & Professional

Want your writing to sound more formal or technical?
📌 Use: Jargonize: before your sentence.
ChatGPT will turn regular words into something that sounds more expert or polished.
Great for work emails, LinkedIn posts, reports, or presentations.

4. Humanize: Make it Sound Real

Tired of replies that feel robotic or awkward?
📌 Just type: Humanize: before your prompt.
ChatGPT will rewrite it to sound more friendly, natural, and like a real person talking.
Bonus: It skips overused words like “innovative” or “game-changer.”

5. Feynman: Truly Understand Hard Stuff

Want to deeply understand a topic not just skim it?
Use the Feynman Technique, which works like this:

Ask for a super simple explanation (ELI5:)
Look at what you still don’t understand
Ask for more clarity or simpler examples
Repeat until it makes sense It helps you turn big, confusing ideas into stuff you can actually explain to others.

WARNING: These 6 AI Tools Will Replace 90% of Jobs in 2025 - Use Them Before It's Too Late

its_hayder — Fri, 27 Jun 2025 17:51:54 +0000

Stop wasting time these mind-blowing AI tools are actually changing the game.
If you're not using them, you're already behind.

Artificial intelligence isn’t coming. It's here. Whether you're a content creator, developer, student, or startup founder, these next-gen AI tools will blow your mind and make you wonder how you ever lived without them.

Here are 6 viral-worthy AI tools that are flying under the radar for now.

1. Vidu AI — Text-to-Video Like Never Before

Turn simple prompts into Hollywood-level video.
From creators to marketers, Vidu AI makes professional-grade video production accessible to everyone. Just type, upload, and watch it build stunning visuals in seconds.

2. FishAudio — Clone Any Voice in Seconds

Music. Effects. TTS. All AI-generated.
FishAudio gives you instant access to voice cloning, studio-grade audio, and sound design tools no DAW or mic needed.

3. Skywork Super Agents — AI That Writes Full Presentations For You

Turn a prompt into polished documents, data-rich slides, or Excel sheets… in minutes.
Skywork’s Super Agents leverage its DeepResearch engine—ranked #1 on the GAIA benchmark to generate well‑researched presentations with source‑citations, design polish, and visual consistency

4. Midscene — Open-Source AI Operator for Web & Mobile

Automate testing, interaction, and app workflows with ease.
Midscene is a powerful open-source AI operator that handles everything from UI testing to app automation. Built for devs who want smart, multimodal agents to interact with their web or mobile apps.

5. Replit AI — Build Full Apps From Prompts

"I want a weather app" → Done.
Replit’s AI Assistant writes your code, debugs, and even generates entire apps. It’s perfect for learners, solo hackers, and prototypers.

6. Suna AI — Your Personal Open-Source Agent

Tell it to search, click, download, organize anything.
Suna is an open-source generalist agent that automates your boring digital tasks. Think browser automation, crawling, and file management all from one chat.

How to Write AI Prompts That Actually Work: 4 Game-Changing Tips

its_hayder — Fri, 13 Jun 2025 10:05:30 +0000

1. Start with a Clear Goal

This is the “what do you want?” part. It sounds simple, but I used to just throw in half-baked questions and hope for gold. Spoiler alert: didn’t work. Now I start every prompt with a single, clear objective. For example, instead of saying:
“Can you help me find hikes?”
I write:

“I want a list of the best medium-length hikes within two hours of San Francisco that are lesser-known and offer a cool and unique adventure.”
Boom. Now the AI knows exactly what I want.

2. Specify the Return Format

This part was a game-changer for me. You need to tell the AI how you want the information delivered. For example, I might say:
“For each hike, include the name, starting address, ending address, hike distance, drive time, hike duration, and what makes it unique. Return the top 3.”
That’s like giving the AI a blueprint—it’s not guessing, it’s following your structure.

3. Set Warnings or Guardrails

Accuracy matters. Especially if you're sharing this info with someone else. That’s why I also write little reminders like:
“Make sure the name of the trail is correct, that it exists, and that the time is accurate.”
These act as safety checks and keep the AI from hallucinating or giving bad info (which can totally happen).

4. Include Context—Even If It Feels Like Oversharing

This was the part I used to skip and it’s where the magic happens. The more personal context you give, the more tailored and human the AI’s response feels.
In my case, I wrote a whole paragraph explaining how my girlfriend and I love hiking, that we’ve done all the major SF trails, and that we’re craving something new because she’s leaving for LA soon and we want to make this weekend count.
I even mentioned how much I love hikes that end with a good breakfast. I thought I was just rambling, but it made a huge difference. The AI came back with hikes that felt like they got me not just random generic trails.

Free ChatGPT Prompt: Turn YouTube Videos Into Study Guides in Minutes

its_hayder — Sun, 01 Jun 2025 09:06:39 +0000

We've all been there you click on a YouTube tutorial to learn something new, but 15 minutes in you're still waiting for the creator to get to the point. Between the "hey guys, don't forget to subscribe" and endless tangents, it feels like you're wasting more time than actually learning.

What if I told you there's a way to skip all that fluff and get straight to the good stuff? This simple trick transforms any YouTube video into a
clean, organized study guide that you can read in under 5 minutes.

The Magic Prompt

Just copy this prompt, paste it into ChatGPT, and add your video transcript:

# YouTube Transcript Teaching Machine

## ROLE: Adaptive Educational Synthesizer

You are an expert educational content processor specialized in transforming raw YouTube transcripts into optimized learning materials using advanced pedagogical frameworks.

## CAPABILITIES

1. **Content Analysis & Extraction**
   - Extract key concepts, facts, theories, and methodologies from transcripts
   - Identify the conceptual hierarchy and knowledge structure
   - Recognize the speaker's teaching approach and methods
   - Filter out irrelevant content, filler words, and repetitions
   - Flag potential inaccuracies or unsupported claims for verification

2. **Educational Restructuring**
   - Organize content following educational best practices
   - Develop clear learning objectives based on content
   - Create logical knowledge progression (foundational → advanced)
   - Identify and clarify potential confusion points
   - Break complex topics into manageable learning units

3. **Learning Style Adaptation**
   - Adapt to different cognitive approaches (analytical, practical, creative)
   - Tailor to various intelligence types (logical, linguistic, spatial, etc.)
   - Adjust for different attention spans and processing speeds
   - Provide alternative explanations for challenging concepts

## PROCESS

1. **Input Analysis**
   - Review the transcript to identify subject, scope, complexity, and structure
   - Determine the educational level and prerequisite knowledge
   - Assess the original teaching approach used in the video
   - Recognize strengths and limitations of the original material
   - Evaluate transcript quality and address any gaps or ambiguities

2. **Learner Profile Integration**
   - Consider the learner's specified needs, goals, and preferences
   - Adapt to their current knowledge level and learning context
   - Optimize for their available study time and resources
   - Account for specific learning challenges if mentioned
   - Align content complexity with cognitive load capabilities

3. **Content Transformation**
   - Reorganize material into a coherent educational structure
   - Simplify complex concepts with analogies and examples
   - Elaborate on unclear or insufficiently explained points
   - Connect new information to established knowledge frameworks
   - Verify factual accuracy and note any claims requiring further investigation

4. **Output Generation**
   - Create primary learning material in the most appropriate format
   - Develop supplementary resources for reinforcement
   - Include metacognitive elements (reflection prompts, self-assessment)
   - Provide guidance for further exploration and application

5. **Quality Assessment**
   - Evaluate the educational effectiveness of the generated materials
   - Identify any remaining gaps or unclear explanations
   - Verify that flagged inaccuracies are properly addressed
   - Ensure all learning objectives are adequately covered

## TRANSCRIPT QUALITY HANDLING

When working with transcripts of varying quality:

1. **For High-Quality Transcripts**: Proceed with standard process, focusing on educational optimization.

2. **For Incomplete Transcripts**: 
   - Identify knowledge gaps and note them explicitly
   - Suggest supplementary resources for missing information
   - Maintain coherence by logically connecting available content

3. **For Technical/Complex Transcripts**:
   - Break down complex terminology with additional explanations
   - Use simplified analogies and visual representations
   - Provide a glossary of technical terms
   - Create progressive complexity levels for different learner capabilities

4. **For Potentially Inaccurate Content**:
   - Flag claims that appear questionable or unsubstantiated
   - Note when statements conflict with established knowledge
   - Suggest verification sources when appropriate
   - Distinguish between established facts and speaker opinions

## OUTPUT STRUCTURE

1. **Learning Objectives** - What you'll learn from this material
2. **Key Concepts** - Essential ideas presented with clear explanations
3. **Concept Map** - ASCII Visual representation of how ideas connect
4. **Detailed Breakdown** - Organized explanation of the content
5. **Summary** - Concise review of the most important points
6. **Application** - How to use this knowledge practically
7. **Self-Assessment** - Questions to check understanding

How to Use It
Step 1: Get the transcript here
Step 2: Insert the result in ChatGPT with the prompt above

The FREE Cursor Alternative That Builds Entire Websites For You (1-Minute Setup)

its_hayder — Sun, 18 May 2025 18:07:38 +0000

You don't need to spend money on Cursor anymore. Instead, here are three simple tools to create your own AI coding assistant one that can help you build full websites or mobile apps without writing a single line of code.

First, download the VS Code app from their official site. It’s an open-source code editor developed by Microsoft, and it’s actually the same base software that Cursor is built upon.

Next, inside VS Code, install the cline AI extension. This tool functions a lot like Cursor’s Agent Mode it’s an AI-powered coding assistant right inside your editor.

Lastly, head over to Google's AI Studio and claim your free API key. This gives you access to Google’s newest AI models that can write and assist with your code.
Once you’ve installed cline, you’ll see a new icon. Click it:

Paste your API key into cline, and that’s it you’ve essentially built your own AI coding tool.
Give it a try and see how much it can help.

LEAKED: 6,500+ Secret AI System Prompts from Top Companies - Engineering Gold Revealed on GitHub

its_hayder — Sun, 11 May 2025 20:28:32 +0000

Someone just leaked a massive list of system prompts used by some of the biggest names in AI Cursor, manus, Bolt, Lovable, and more. Over 6,500 lines of actual prompts that these tools use behind the scenes.

These are the kinds of things companies normally hide, charge for, or gate behind fancy pricing plans and now they’re sitting publicly on a GitHub repo.

Why this is actually crazy?
This isn’t fluff. These are real examples from tools used by thousands of developers and teams. If you’re into:

Building AI apps
Prompt engineering
Studying how top tools are designed

…this is a goldmine.

You’ll see how real products structure their prompts, how they chain instructions, and how they get the most out of models. It’s like getting to peek into the blueprints of several successful AI startups at once.

this is the link of the GitHub repo
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools