AI-assisted testing, code review, validation, and test-fix iteration

Why dynamic workflows exist, the three failure modes they fix, the six patterns, and how the harness runs. Beginner-friendly.

AI didn't make me a 10x developer

It removed hours of boring work.

Now I use it to:
• Design APIs
• Generate boilerplate
• Review code
• Find edge cases
• Write tests
• Create documentation

The biggest productivity gain isn't coding.

It's reducing context switching.

How are you using AI in development?

Let me save you some time upfront: I’m not going to tell you it changed my life.

A month ago, I wasn’t even looking for a new AI coding tool. I already had a workflow that worked. Claude.ai for code reviews, Axios for API calls, VS Code for everything else. Then I kept seeing developers talk about Claude Code — the terminal-based version, the one that reads your entire codebase automatically.

Some said it was the best coding assistant available. Others said it wasn’t worth the price. Most reviews were either suspiciously positive or completely dismissive.

So I stopped reading opinions and started testing.

For 30 days, I used Claude Code on a real production project. Not a side project. Not a tutorial app. A form-heavy medical examination system built for a state government — complex conditional logic, multiple examination form components, Java DTO integrations, file upload flows, and zero tolerance for bugs.

Copilot code review now supports repository-level `AGENTS.md` files, and it’s easier to request a review from Copilot on draft pull requests with the Request button. These changes are all generally available.

You can now add an `AGENTS.md` file at the root of your repository to help shape Copilot code review feedback. If your repository already has an `AGENTS.md` file, Copilot code review will now utilize that context automatically as part of its workflow. This makes it easier to get reviews that better reflect your repository’s conventions and expectations.

You can already request Copilot code review on draft pull requests to get a first pass on your draft before even publishing your pull request. Now, the Request button shows up next to Copilot on draft pull requests. This makes that workflow easier by letting you request Copilot directly from the reviewer picker without needing to search for Copilot first.

On the Conversation tab of your pull request, Copilot code review events documented in the timeline can get noisy. We’ve collapsed certain Copilot code review timeline events together to help declutter your conversation tab, allowing you to find what matters, quickly.

AI as a tool rather than an authority

Would you treat a serious illness without seeing a doctor, relying only on whatever your favorite AI model suggested? Would you let AI take over your child's education?

Probably not.

So why are you willing to hand over your entire codebase to it?

Asked claude code to verify features in a moderately large codebase. The capability is insane, so is the token usage.

I've been using AI for code reviews for over a year. In that time I've learned one uncomfortable truth:

Most developers are using AI wrong for code reviews.

They paste code and ask "is this good?" They get back a wall of generic feedback that could apply to literally any codebase. It feels useful for about 10 seconds, then you realize nothing actionable came out of it.

The problem isn't the AI. It's the prompt.

After hundreds of iterations, I've identified the patterns that separate a mediocre AI code review from one that actually finds bugs, catches security holes, and suggests fixes a senior engineer would be proud of.

Here's what I learned — and the exact prompts I now use daily.

Released May 28, the Claude Opus 4.7 upgrade beats its predecessor, GPT-5.5, and Gemini 3.1 Pro across almost all benchmarks. Mythos 1 and Sonnet 4.8 could be next.

The 7 AI coding skills I use every single day.

(All free to download):

If you spend any time in AI circles online, it's easy to come away thinking you need hundreds of skills, dozens of plugins, and an ever-growing stack of MCP servers to be productive with coding agents.

I've come to believe the opposite.

The engineers I see shipping the most consistent, high-quality work tend to use a small number of well-designed skills that map to the workflows they repeat every day. Planning, implementing, reviewing. That's most of the job.

I've spent the last couple of years building, breaking, and rebuilding my own toolkit. It's settled into just a few skills that I genuinely use every day across professional projects, and that I'd happily defend as the only ones most engineers need.

I just put together a full video walking through all seven, with live demos in Codex (though they work fine in Claude Code or any other agent).

I show how I use each one, why it earns its place, and the pattern underneath them that I think matters more than the list itself.

https://lnkd.in/e_r62kya

Every skill is free and linked in the description so you can grab them and try them yourself.

If you've got a skill you swear by that you think I'm missing, let me know in the comments.

The best part of working in public is the steady stream of better ideas coming back from people who've solved problems I haven't noticed yet.

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A practical look at Anthropic’s agentic coding tool — what it actually does, how it changed my workflow, and whether it’s worth your time.