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The absolute best AI coding extensions for VS Code in 2025

By / Last updated on September 15, 2025

AI tools inside VS Code have gone way way beyond simple autocompletion.

Today you can chat with an assistant, get multi-file edits, generate tests, and even run commands straight from natural language prompts.

These are the very best AI coding extensions that will transform how you develop software forever.

1. Gemini Code Assist

Google’s Gemini Code Assist brings the Gemini model into VS Code. It stands out for its documentation awareness and Google ecosystem ties.

Why it’s great:

  • Answers come with citations so you can see which docs were referenced.
  • It can do code reviews, generate unit tests, and help debug.
  • Works across app code and infrastructure (think Terraform, gcloud CLI, etc.).

Great for: Anyone working heavily in Google Cloud, Firebase, or Android, or who values transparent, sourced answers.

2. GitHub Copilot

GitHub Copilot is the “classic” AI coding assistant — but it’s evolved far beyond just inline suggestions. With the main Copilot extension and Copilot Chat, you get a fully integrated agent inside VS Code.

Just see how easy it is:

Why it’s great:

  • Agent and Edit modes let Copilot actually implement tasks across your files and iterate until the code works.
  • Next Edit Suggestions predict your next likely change and can propose it automatically.
  • Workspace-aware chat lets you ask questions about your codebase, apply edits inline, or run slash commands for refactoring.

Great for: Developers who want deep VS Code integration and a polished, “just works” AI experience.

3. Tabnine

Tabnine is all about privacy, control, and customization. It offers a fast AI coding experience without sending your proprietary code to third parties.

Look how we use it rapidly create tests for our code:

Effortless code replacement:

Why it’s great:

  • Privacy first: can run self-hosted or in your VPC, and it doesn’t train on your code.
  • Custom models: enterprises can train Tabnine on their own codebases.
  • Versatile assistant: generates, explains, and refactors code and tests across many languages.

Great for: Teams with strict data policies or anyone who wants an AI coding assistant they can fully control.

4. Amazon Q for VS Code

Amazon Q is AWS’s take on an “agentic” coding assistant — it can read files, generate diffs, and run commands all from natural language prompts.

Why it’s great:

  • Multi-step agent mode writes code, docs, and tests while updating you on its progress.
  • MCP support means you can plug in extra tools and context to extend what it can do.
  • Inline chat and suggestions feel native to VS Code.

Great for: AWS developers who want more than autocomplete — a true assistant that can execute tasks in your environment.

5. Windsurf Plugin (Codeium)

Some of you don’t know that Windsurf was actually Codeium before — originally just a nice VS Code extension — before becoming a full-fledged beast of an IDE.

After Windsurf came out they renamed it to this — Windsurf Plugin.

The Windsurf Plugin delivers lightning-fast completions and chat inside VS Code, plus a generous free tier.

Why it’s great:

  • Unlimited free single- and multi-line completions right out of the box.
  • Integrated chat for refactoring, explaining, or translating code.
  • Links with the standalone Windsurf Editor for even more features.

Great for: Anyone who wants a fast, no-hassle AI coding experience.

6. Blackbox AI

Blackbox AI is one of the most popular AI coding agents in the Marketplace, designed to keep you in flow while it helps with code, docs, and debugging.

Why it’s great:

  • Agent-style workflow: run commands, select files, switch models, and even connect to MCP servers for extra tools.
  • Real-time code assistance: completions, documentation lookups, and debugging suggestions that feel native to VS Code.
  • Understands your project: conversations and edits can reference the broader codebase, not just a single file.
  • Quick start: install and start using it without a complicated setup.

Great for: Developers who want a free, quick-to-try AI agent inside VS Code that can go beyond autocomplete and interact with their workspace.

How to choose?

Best by area:

  • Deep integration & agents: GitHub Copilot, Amazon Q, or Blackbox AI.
  • Doc-aware answers with citations: Gemini Code Assist.
  • Strict privacy and custom models: Tabnine.
  • Fast and free: Windsurf Plugin.

Also consider your stack and your priorities.

  • On AWS? Amazon Q makes sense.
  • All-in on Google Cloud? Gemini is your friend.
  • Need privacy? Tabnine is your best bet.
  • Want the smoothest VS Code integration? Copilot.
  • Want to try AI coding with no cost barrier? Windsurf Plugin.

If you’re not sure where to start, pick one, try it for a real project, and see how it fits your workflow. The best AI coding tool is the one that actually helps you ship code faster — without getting in your way.

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The secret code Google uses to monitor everything you do online

By / Last updated on September 13, 2025

Google now has at least 3 ways to track your search clicks and visits that they hide from you.

Have you ever tried to copy a URL directly from Google Search?

When I did that a few months ago, I unexpectedly got something like this from my clipboard.

Plain text
https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjUmK2Tk-eCAxXtV0EAHX3jCyoQFnoECAkQAQ&url=https%3A%2F%2Fcodingbeautydev.com%2Fblog%2Fvscode-tips-tricks&usg=AOvVaw0xw4tT2wWNUxkHWf90XadI&opi=89978449

I curiously visited the page and guess what? It took me straight to the original URL.

This cryptic URL turned out to be a middleman that would redirect you to the actual page.

But what for?

After some investigation, I discovered that this was how Google Search had been recording our clicks and tracking every single visited page.

They set custom data- attributes and a mousedown event on each link in the search results page:

HTML
<a jsname="UWckNb"
   href="https://codingbeautydev.com/blog/vscode-tips-tricks"
   data-jsarwt="1"
   data-usg="AOvVaw0xw4tT2wWNUxkHWf90XadI"
   data-ved="2ahUKEwjUmK2Tk-eCAxXtV0EAHX3jCyoQFnoECAkQAQ">
</a>

A JavaScript function would change the href to a new URL with several parameters including the original URL, as soon as you start clicking on it.

JavaScript
import express from 'express';

const app = express();

app.get('/url', (req, res) => {
  // Record click and stuff...
  res.redirect(req.query);
});

app.listen(3000);

So even though the browser would show the actual URL at the bottom-left on hover, once you clicked on it to copy, the href would change instantly.

Why mousedown over click? Probably because there won’t be a click event when users open the link in a new tab, which is something that happens quite often.

And so after right-clicking to copy like I did, mousedown would fire and the href would change, which would even update that preview URL at the bottom-left.

The new www.google.com/url page would log the visit and move out of the way so fast you’d barely notice it — unless your internet moves at snail speed.

They use this data for tools like Google Analytics and Search Console so site owners can improve the quality of their search results and pages by analyzing click-rate — something probably also using as a Search ranking factor. Not to mention recording clicks on Search ads to rake all the billions of yearly ad revenue.

Google Search Console. Source: Search Console Discover report now includes Chrome data

But Google got smarter.

They realized this URL tracking method had a serious issue for a certain group. For their users with slower internet speeds, the annoying redirect technique added a non-trivial amount of delay to the request and increased bounce rate.

So they did something new.

Now, instead of that cryptic www.google.com/url stuff, you get… the same exact URL?

With the <a> ping attribute, they have now successfully moved their tracking behind the scenes.

The ping attribute specifies one or more URLs that will be notified when the user visits the link. When a user opens the link, the browser asynchronously sends a short HTTP POST request to the URLs in ping.

The keyword here is asynchronously — www.google.com/url quietly records the click in the background without ever notifying the user, avoiding the redirect and keeping the user experience clean.

Browsers don’t visually indicate the ping attribute in any way to the user — a specification violation.

When the ping attribute is present, user agents should clearly indicate to the user that following the hyperlink will also cause secondary requests to be sent in the background, possibly including listing the actual target URLs.

HTML Standard (whatwg.org)

Not to mention a privacy concern, which is why browsers like Firefox refuse to enable this feature by default.

In Firefox Google sticks with the mousedown event approach:

There are many reasons not to disable JavaScript in 2023, but even if you do, Google will simply replace the href with a direct link to www.google.com/url.

HTML
<a href="/url?sa=t&source=web&rct=j&url=https://codingbeautydev.com/blog/vscode-tips-tricks...">
  10 essential VS Code tips and tricks for greater productivity
</a>

So, there’s really no built-in way to avoid this mostly invisible tracking.

Even the analytics are highly beneficial for Google and site owners in improving result relevancy and site quality, as users we should be aware of the existence and implications of these tracking methods.

As technology becomes more integrated into our lives, we will increasingly have to choose between privacy and convenience and ask ourselves whether the trade-offs are worth it.

5 unbelievable reasons why we code

By / Last updated on September 11, 2025

Too often we treat coding like a grind: features, deadlines, output.

But even with AI agents doing much of the typing these days, coding remains a craft, a discipline of logic and creation.

It’s an incredible activity in and of itself, a way of thinking and shaping systems.

Beneath the automation there’s still the thrill of solving, making, and mastering complexity.

1. To create — bringing thoughts into reality

Coding is also an act of creation.

Like an artist with paint or a sculptor with clay, we developers craft something from nothing but logic and imagination.

Whether it’s a sleek app, an immersive video game, a generative art project, or the massive algorithm for a tiny feature our users take for granted — programming transforms intangible ideas into tangible systems.

It’s a medium where creativity meets precision. We code because we have visions of how things could be—and coding is the fastest way to make them real.

2. To summon our cognitive powers

Some non-developers don’t realize that programming is something we actually find enjoyable.

Programming stretches and stimulates our minds.

It demands pattern recognition, abstract reasoning, and the ability to hold multiple layers of logic in working memory. Each bug forces us to think deeper.

Each new paradigm—functional, object-oriented, reactive—expands the boundaries of our thought. Coding challenges our cognitive powers in a way few other activities do. It’s not just a job skill; it’s mental training for problem-solving in its purest form.

3. To amplify the power of our thoughts — leverage

We don’t code just for efficiency.

We code because it gives us something almost mythic: the ability to amplify a single person’s power exponentially.

A well-written program can run millions of times, across millions of devices, without ever tiring.

It can become a force multiplier for entire industries or communities.

Through code, we wield something like magic—commands that ripple outward, transforming the world far beyond our immediate reach. This is more than leverage; it’s an engine of exponential influence.

4. To unite logic toward a common objective

Programming is the art of uniting fragments of logic into a coherent whole. Each function, variable, and rule is a small shard of thought.

Alone, they’re inert.

Together, arranged in precise order, they form living systems—machines that act, decide, and respond.

Coding is the discipline of organizing logic, of weaving countless moving parts into a single purposeful flow.

It’s like conducting an orchestra of instructions where every instrument must play in perfect timing to achieve the intended result.

5. To solve real-world problems — Impact at scale

And yes of course, coding is a tool for impact — the biggest reason it became so important.

It turns raw human intention into functioning systems that touch lives. Every payment app, medical algorithm, or disaster-response tool begins as lines of code solving a concrete problem.

We code because we want to influence reality—whether it’s automating a mundane process, reducing human error, or scaling up something that can only exist in digital form.

Through code, a single person can affect thousands, even millions, at once. This isn’t just problem-solving; it’s world-shaping.

We code to solve, to create, to grow, to amplify, and to orchestrate. It’s a blend of imagination, logic, rigor, and ambition. In every program lies a fragment of a person’s mind, extended outward into the machine and, through the machine, into the world.

In the end coding is about more than computers. It’s about us—our drive to understand, to build, to challenge ourselves, and to shape reality itself.

This new IDE from Amazon is an absolute game changer

By / Last updated on September 9, 2025

Woah Amazon’s new Kiro IDE is absolutely HUGE.

And if you think this is just another Cursor or Copilot competitor then you are dead wrong on the spot…

This is a revolutionary approach to how AI coding assistants are supposed to be… This is real software development.

Development based on real GOALS — not just randomly prompting an agent here and there.

No more blind stateless changes — everything is grounded on real specs, requirements, and goals 👇

Amazon Kiro understands that you’re not just coding for coding sake — you have actual targets in mind.

Targets it can even define for you — in an incredibly detailed and comprehensive way:

Look — it can even make unbelievably sophisticated designs for you based on your requirements 👇

I told you — this is REAL software development.

This is just one of the incredibly innovative Kiro features that no other IDE has.

And guess what — It’s based on VS Code — switching is so ridiculously easy — you can even keep your VS Code settings and most extensions.

Goal-first thinking, agentic automation, and deep integration with tools developers already use.

Two big ideas

Kiro is based on two big ideas it implements in an unprecedented way:

Spec-driven development

This is very similar to what Windsurf tried to do with their recent Markdown planning mode update:

You don’t start with code. You start with intent — written in natural language or diagrams.

These specs live alongside your codebase, guiding it as the project evolves. Kiro continuously uses them to generate and align features, update documentation, track architectural intent, and catch inconsistencies.

Background hooks

This one is absolutely insane — how come no one ever thought of this until now?

Hooks — automated agents that run in the background. As you code, they quietly:

  • Generate and update docs
  • Write and maintain tests
  • Flag technical debt
  • Improve structure and naming
  • Ensure the implementation matches your specs

This isn’t just a chat window on the side. This is an always-on assistant that sees the entire project and works with you on every save.

Under the hood

Code OSS Core

Kiro is built on Code OSS — the same open-source engine behind VS Code. Your extensions, keybindings, and theme carry over seamlessly. Zero learning curve.

MCP Integration

It supports the Model Context Protocol, allowing Kiro to call external agents and tools through a shared memory layer. This sets it up for a future of multi-agent collaboration that’s already taking shape.

Model Support

Kiro runs on Claude Sonnet 4.0 by default, with fallback to Claude 3.7. Support for other models, like Gemini, is on the roadmap — and the architecture is designed to be model-flexible.

Massive demand already

Kiro is in free preview right now — but massive demand has already forced AWS to cap usage and implement a waitlist.

A full pricing structure is on the way — something like:

  • Free: 50 interactions/month
  • Pro: $19/month for 1,000 interactions
  • Pro+: $39/month for 3,000 interactions

Signups are open, but usage is currently restricted to early testers.

Better

If you’ve used Cursor or Windsurf, you already know how powerful it is to have agentic workflows built directly into your IDE.

Kiro builds on that foundation — but shifts from reactive prompting to proactive structure. It doesn’t just assist your coding. It tries to own the meta-work: the tests you skip, the docs you forget, the loose ends that add up over time.

That’s where Kiro stakes its claim — not just as a smart code editor, but as an operating system for full-stack development discipline.

Don’t ignore this

Kiro is still early, but it’s not experimental in spirit. It’s built with a clear vision:

  • Bring AI into every layer of the software kdevelopment process
  • Anchor work around intent, not just implementation
  • Support fast prototyping and scalable production with equal seriousness

For solo builders and teams alike Kiro is most definitely worth keeping an eye on.

Not just for what it does now, but for what it signals about where modern development is headed.

I vibe coded a super-powered AI app in 5 minutes with Google’s Nano Banana

By / Last updated on September 7, 2025

Google just released their incredible Nano Banana model and it’s been wild these past few days.

The major game changer and my favorite feature is the stunning image editing ability.

Which is why many people have been calling it the Photoshop killer.

And for us devs this just opened up a massive world of opportunity to build the most amazing image-focused apps.

I’m gonna show you how we can so easily create such an app in just like 5 minutes with the awesome power of coding agents.

Before deciding what you want to build you have the Google AI Studio to help you play around with Nano Banana — and all the other Google image models.

With the Studio you can easily check how good the model is for your use case.

Test and refine prompts until they give you exactly what you’re looking for

Unleash your creativity without limits.

So let’s say we’re creating an app to bring a grayscale image to life with color.

Users upload any image in grayscale and they get a beautiful colorized image — giggling and all excited to make it their wallpaper and tattoo it on their back.

Before image models like Nano Banana this would have a lot less straightforward — using specialized Python libraries to process the image through multiple stages and stuff.

But now all it takes is just 3 super simple words of prompting.

Let’s even say 1 word cause i bet it would work with just “colorize”.

Yes:

So just one word is all it takes now with Nano Banana.

So imagine how easy the app is going to be to make — the core engine is already fully taken care of by AI.

With vibe coding and AI agents the rest is just so easy.

We don’t even need any framework like React or god forbid Next.js — just basic HTML, CSS, and JS will do — especially since we won’t be writing a single atom of the code ourselves.

First we just use the “Get code” button in the Studio to get the JavaScript code version — let’s us use our ridiculously simple prompt in a real server.

This is another brilliant perk of using Google AI Studio — easily get the boilerplate code to use any prompt for any AI model.

Creating the actual server is just so easy now:

Look I just said:

“create an express server with a /processImage route to colorize an uploaded grayscale image using this code:”

And then I pasted the code from the Studio.

And that was that.

You see first of all the Cascade agent created a clear todo list so it knows exactly what it’s doing — yeah sadly we humans don’t have a monopoly on todo lists anymore…

And then BOOM — every single task with its sub-tasks and sub-sub-tasks — thoroughly conquered and vanquished in a matter of minutes.

At the end of the day:

Every single file and code here came from the coding agent.

Wow the agent even added code to remind me to use my GEMINI_API_KEY — something I actually forgot.

Getting an API key is super easy — just use Get API key -> Create API key in the Studio.

Even more incredible — it generated the entire client-side code for me.

I only asked and expected just the server side server with routes and all — but it went the extra mile and did everything.

All done:

So I uploaded the grayscale city view from earlier:

And in a few seconds:

In just 5 minutes — or maybe even less — I created this incredible colorizing app from absolutely nowhere.

This is the insane power AI gives you.

No, AI will NOT kill your coding brain

By / Last updated on September 7, 2025

A common narrative among the AI-hating devs.

They claim that using AI tools like ChatGPT or GitHub Copilot is a crutch that will ultimately “rot” your brain.

That relying on AI to write code will lead to a generation of programmers who can’t think for themselves.

But this perspective is misguided and fundamentally misunderstands the real value of a programmer in today’s world.

It’s like saying Intellisense makes you ignorant of basic APIs. Or a making the same case against classic StackOverflow copy-and-paste.

The truth is AI doesn’t diminish our mental faculties; it frees us to operate at a higher, more creative level.

A vast amount of programming work isn’t about groundbreaking innovation—it’s about repetition.

How many times has an authentication screen been built?

How many search functionalities or “Create, Read, Update, Delete” (CRUD) cycles have been coded from scratch?

These are the low-level, predictable tasks that make up the bulk of many projects. They are essential but rarely require deep, creative problem-solving. AI is exceptionally good at handling these predictable, boilerplate tasks, allowing developers to skip the tedious work and focus on what truly matters.

The real value and creativity in software development don’t come from writing another for-loop or manually crafting a function to validate an email address.

Instead, they come from the higher-level architectural decisions and the conceptual design of a system.

A developer’s mind is truly engaged when they’re figuring out how different components will interact, how to optimize a system for scale, or how to design an intuitive user experience. This is where innovation happens.

AI and vibe coding elevate you to this level, handling the grunt work so you can dedicate your mental energy to solving the bigger, more complex problems.

Means vs end

And yes coding can be a rewarding and mentally stimulating hobby — but for most solo developers and large organizations it’s just a means to an end.

People aren’t coding for the sole purpose of “developing their brains.”

They’re coding to build a product, launch a business, or bring an innovative idea to life.

For a devpreneur with a groundbreaking app idea, the goal is to build the app, not to spend weeks manually writing low-level code that an AI could generate in seconds.

Similarly for a company, the goal is to ship a product, not to maximize the number of lines of code its engineers write by hand. If a tool can drastically accelerate this process and help them achieve their goals faster, why wouldn’t they use it?

Fear

The “AI rots your brain” argument often stems from a place of fear—the fear that AI will replace developers.

Many of the developers who fear AI are simply afraid of losing their value and getting replaced.

So they tell themselves it’s just hype and everything will be fine. They cling to the idea that their manual labor is the source of their worth.

But the truth is, the most valuable work is the kind that AI frees us up to do — whether it even has anything to do with coding or not. Whether it makes money or not.

Ultimately the goal is to build things that matter and have a fulfilling existence.

AI is a powerful tool that helps us do just that, faster and more effectively. It frees us from the mundane and allows us to focus on the truly creative and impactful aspects of software development. It doesn’t kill your coding brain; it just changes what you use your brain for. And that’s a good thing.

Google just ruined Android development forever

By / Last updated on September 3, 2025

Wow is Google really doing this to Android?

This is just horrible.

They want to take away the freedom we’ve always had with Android and APKs.

They want to have tight control over all the apps we can install on our Android phones.

So much for “open-source”. The one major advantage it always had over iOS.

As a dev who occasionally makes apps just for myself I was even recently thinking of switching to Android just because of this.

For over a decade it’s been the open alternative to Apple’s walled garden.

Letting you install apps from the web and decide what software you trusted without corporate gatekeeping.

All that is going straight down the toilet in a matter of months.

This can’t be happening

Starting in 2026 Google will begin blocking app installs from third-party sources unless the developer verifies their identity through Google’s systems.

That includes apps distributed via websites, alternative stores, or even shared directly between friends.

Starting in a few countries and then expanding globally in 2027 and beyond.

On paper, this isn’t about banning sideloading. Google insists sideloading is still “fundamental to Android.” But in practice, this is a shift from “your device, your choice” to “your device, Google’s terms.”

This isn’t an isolated case. We’ve seen this playbook before.

Google’s Manifest V3 changes in Chrome drastically limited the power of ad blockers and privacy extensions—under the guise of security and performance. Developers were forced to comply with new APIs that neutered their functionality, while Google’s own advertising stack remained untouched.

Now we’re watching the same logic creep into Android.

Claim security. Lock it down. Funnel developers into Google-controlled verification systems.

What began in the browser is now reaching the OS.

Tight control

There’s also a deeper undertone here: retribution.

Google recently lost a high-profile antitrust case against Epic Games, one that challenged Google Play’s monopoly over Android app distribution. The ruling confirmed what many already believed: that Google was making it unfairly hard to compete with the Play Store.

This new sideloading restriction looks suspiciously like a response. If Google can’t force developers into the Play Store economically, it can still do it technically—by requiring identity verification for sideloading and tightening the noose around “alternative” installs.

It’s not about user safety. It’s about regaining leverage.

For “security purposes”

Google justifies the new policy by citing malware concerns. They claim that apps installed from outside Play are “50 times more likely” to be harmful.

But that stat is misleading. Many users sideload trusted open-source apps, emulators, beta tools, or regional content that Play doesn’t allow.

How about just showing a big bold warning — like they already do?

This policy doesn’t stop verified malicious actors from tricking non-tech-savvy users. It only makes life harder for legitimate developers and power users.

Haven’t we had several case apps that Google allowed in the Play Store

It’s like banning tools because some people misuse them.

Who loses?

  • Indie devs who distribute apps on GitHub, F-Droid, or their own websites.
  • Privacy advocates using de-Googled Android forks.
  • Global users in regions with censorship or unreliable Play Store access.
  • And ultimately, all Android users who value the idea that they—not Google—control what runs on their phone.

Tightening control

This change doesn’t stand alone. It’s part of a slow march:

  • Play Integrity APIs are becoming mandatory to access app features.
  • Older APKs targeting pre-Android 7 are blocked by default.
  • Device attestation is increasingly required to use modern apps.
  • Google Play Services continues to tighten its grip over “certified” devices—nearly all Android phones globally.

Individually, these changes feel technical or benign. But together, they’re reshaping Android into a closed system wrapped in open-source PR.

Don’t be fooled

Google claims you can still sideload. Technically, yes—but only if the developer has been approved by Google.

That’s not freedom. That’s conditional freedom.

Just like Manifest V3 weakened privacy in Chrome, this move weakens independence in Android. And just like Apple’s ecosystem, it locks users into corporate gatekeeping—bit by bit, update by update.

This isn’t about safety. It’s about control, monetization, and reasserting dominance after a legal and reputational setback.

We must push back—because if Google succeeds here, it won’t stop. This is a stress test of how much user freedom can be taken without revolt.

And if we fail to resist, Android will become Apple—with extra steps.

Amazing MCP servers for every aspect of software development

By / Last updated on September 1, 2025

MCP is changing everything for software development…

But many devs are still very far from using it to its true potential.

There are several MCP servers out there to massively extend your coding agent’s abilities and dramatically transform your dev experience.

Real docs on demand, control your entire cloud infrastructure, automate browsers, and much more.

1. Improve code accuracy: Context7

Version-aware code docs on demand

Say goodbye to hallucinated code examples.

Key Features:

  • Fetches real documentation from official sources, tailored to your exact framework and version.
  • Works with prompts like: use context7 for next.js@14.
  • Available in both STDIO and remote HTTP/SSE modes.
  • Compatible with Claude Desktop, Cursor, Windsurf, and more.

Use it for: Auto-fetching precise docs and examples while you build—no tab-switching required.

Get Context7: LINK

2. Manage cloud services: Google Cloud MCP

Natural language cloud control.

Manage your GCP projects like you’re talking to an engineer.

Key Features:

  • Inspect and operate on GCP resources using natural language.
  • Supports: Compute, Cloud Functions, Run, SQL, BigQuery, GKE, Billing, Logging, and more.
  • Local credentials only (secure by default).
  • Custom run-gcp-code tool for advanced API calls.

Use it for: Debugging infra, checking costs, or exploring your cloud setup in chat—securely.

Get Google Cloud MCP: LINK

3. Interact with databases: Supabase MCP

Turn your agent into a Supabase-native teammate—with safety rails.

Key Features:

  • Granular permissions: read-only mode, scoped to specific projects.
  • Tools for SQL queries, migrations, logs, functions, storage, and branching.
  • Type-safe output from your DB schema.
  • Integrated with Claude, Cursor, VS Code, Windsurf, and more.

Use it for: Daily dev, schema exploration, and shipping faster—without giving the AI total access.

Get Supabase MCP: LINK

4. Identity management and security: Auth0 MCP

Securely manage your Auth0 tenant with AI.

Key Features:

  • Supports creating apps, managing users, deploying Actions, inspecting logs, and more.
  • Built-in support for tool-level allowlisting and read-only mode.
  • Hardened auth with device flow, plus DEBUG tool for troubleshooting.
  • Production-ready with security-first design.

Use it for: Handling Auth0 without clicking through a dashboard—while keeping things safe and scoped.

Get Auth0 MCP: LINK

5. Browser automation – Puppeteer MCP

Control a live browser session from your AI IDE.

Key Features:

  • Automate clicks, typing, navigation, JS execution, screenshots.
  • Can attach to existing Chrome sessions.
  • Built with TypeScript and modeled after Anthropic’s puppeteer server.
  • Still experimental, but already functional.

Use it for: Demos, scrapers, or showing agents how your site actually behaves.

Get Puppeteer MCP: LINK

6. CI/CD and DevOps: GitHub MCP

Bring your GitHub repos directly into your AI IDE for issue triage, PR workflows, and CI/CD debugging.

Key Features:

  • Runs in local mode or via hosted OAuth.
  • Granular controls — enable only repos, issues, pull requests, or actions you need.
  • Read-only toggle for safety.
  • Integrates with Dependabot, CodeQL, and GitHub Actions workflows.
  • Works seamlessly with Claude Desktop, Cursor, Windsurf, and other MCP clients.

Use it for: Streamlining repo management with AI-powered issue triage, PR summaries, and CI/CD diagnostics in one place.

Get GitHub MCP: LINK

7. Monitoring & Testing — Sentry MCP

See a bug → analyze it → fix it — all in one flow, inside your AI IDE.

Key Features:

  • Analyze Sentry issues, stack traces, and debugging context.
  • List and manage projects, orgs, and DSNs via prompt.
  • Use Sentry Seer to auto-suggest fixes for production issues.
  • Supports remote hosting via the official Sentry endpoint or local setup.
  • Works across Claude, Cursor, Windsurf, and other MCP clients.

Use it for: Debugging and fixing real issues without leaving your AI chat window.

Get Sentry MCP: LINK

Vibe coding jobs are booming and programmers are in denial

By / Last updated on August 29, 2025

It’s happening.

Vibe coding jobs are becoming a reality — and these aren’t little paying jobs either.

Look at this — a vibe coding job listing on Indeed paying up to $220,000 per year.

This is the real deal.

Many of you laughing at vibe coding and AI-assisted coding in general — now see for yourself.

More and more companies are seeing vibe coding as the real deal.

Of course many developers are still in denial.

Developers who keep ignoring AI are going to eventually find themselves left behind.

Because what vibe coding really means is that developers are finally being allowed to focus. No more spinning your wheels on boilerplate.

No more spending hours trying to scaffold out yet another UI flow that’s 90% the same as last week’s. No more pretending documentation is exciting.

AI does the boring stuff. You do the real work — thinking clearly, setting direction, maintaining the mission of the project.

The tools are here. Cursor. Windsurf. Claude Code. They let you shape a whole app without opening Stack Overflow once. You flow. You prompt. You build. You debug at the speed of thought.

And businesses are catching on. They’re not just hiring developers who can memorize syntax and write boilerplate from scratch. They’re hiring developers who can design systems, think fast, move faster — and collaborate with AI like it’s second nature.

That vibe coder you’re laughing at? They’re now outputting 10x the features per sprint, spending half the time sipping coffee and planning product-market fit, while the AI handles the grind.

It’s no longer “do you use AI when coding?” The question now is: how well do you prompt? How fluid is your interaction with a coding agent? Can you build and ship products faster than the average dev team — on your own?

We’re talking developers who can:

  • Build an MVP in a weekend using only natural language + refactors
  • Design UIs visually and prompt the backend logic to match
  • Jump between different stacks without having to “learn” them from scratch

They don’t memorize. They orchestrate. That’s the new skill set.

And vibe coding doesn’t kill the developer. It amplifies the real ones. The strategic thinkers. The system architects. The fast learners. The ones who know how to move ideas into product — not just line-by-line into code.

So yeah. If you’re laughing now you’ll probably be crying later.

The wave is already here. Some devs are riding it.

Others? Still stuck complaining in Reddit thread about how terrible AI is for “corrupting” software dev.

Good luck with that.

We’re building the future, with our minds. One prompt at a time.

These AI agent tricks drastically improve coding accuracy

By / Last updated on August 27, 2025

AI coding agents are unbelievable as there are — but there are still tons of powerful techniques that will greatly maximize the value you get from them.

Use these tips to save you hours and drastically improve the accuracy and predictability of your coding agents.

1. Keep files short and modular

Too-long files are one of the biggest reasons for syntax errors from agent edits.

Break your code into small, self-contained files — like 200 lines. This helps the agent:

  • Grasp intent and logic quickly.
  • Avoid incorrect assumptions or side effects.
  • Produce accurate edits.

Short files also simplify reviews. When you can scan a diff in seconds, you catch mistakes before they reach production.

2. Customize the agent with system prompts

System prompts are crucial for guiding the AI’s behavior and ensuring it understands your intentions.

Before you even start coding, take the time to craft clear and concise system prompts.

Specify the desired coding style, architectural patterns, and any constraints or conventions your project follows.

Like for me I’m not a fan of how Windsurf likes generating code with comments — especially those verbose doc comments before a function.

So I’d set a system prompt like “don’t include any comments in your generated code”.

Or what if you use Yarn or PNPM in your JS projects? Coding agents typically prioritize npm by default.

So you add “always use Yarn for NPM package installations“.

On Windsurf you can set system prompts for Cascade with Global Rules in global_rules.md

3. Use MCP to drastically improve context and capability

Connect the agent to live project data—database schemas, documentation, API specs—via Model Context Protocol (MCP) servers. Grounded context reduces hallucinations and ensures generated changes fit your actual environment.

Without MCP integration, you’re missing serious performance gains. Give the agent all the context it needs to maximize accuracy and run actions on the various services across your system without you ever having to switch from your IDE.

4. Switch models when one fails

Different models can excel at different tasks.

If the agent repeats mistakes or gives off-base suggestions, try swapping models instead of endless retries.

A new model with the same prompt often yields fresh, better results.

Also a great tactic for overcoming stubborn errors.

5. Verify every change (to the line)

AI edits can look polished yet contain tiny changes you didn’t ask for — like undoing a recent change you made. Windsurf is especially fond of this.

Never accept changes blindly:

  • Review diffs thoroughly.
  • Run your test suite.
  • Inspect critical logic paths.

Even if Windsurf applies edits smoothly, validate them before merging. Your oversight transforms a powerful assistant into a safe collaborator.

6. “Reflect this change across the entire codebase”

Sometimes you tell the agent to make changes that can affect multiple files and projects — like renaming an API route in your server code that you use in your client code.

Telling it to “reflect the change you made across the entire codebase” is a powerful way to ensure that it does exactly that — making sure that every update that needs to happen from that change happens.

7. Revert, don’t retry

It’s tempting to try and “fix” the AI’s incorrect output by continually providing more context or slightly altering your prompt.

Or just saying “It still doesn’t work”.

But if an AI agent generates code that is fundamentally wrong or off-track, the most efficient approach is often to revert the changes entirely and rephrase your original prompt or approach the problem from a different angle.

Trying to incrementally correct a flawed AI output can lead to a tangled mess of half-baked solutions.

A clean slate and a fresh, precise prompt will almost always yield better results than iterative corrections.

AI coding agents are force multipliers—especially when you wield them with precision. Master these habits, and you’ll turn your agent from a novelty into a serious edge.