I’ve been meaning to write this up because it’s been surprisingly repeatable, and I wish someone had described it to me earlier.

Over the last year or so, my development speed relative to my own baseline from ~2019 is easily 20x, sometimes more. Not because I type faster, or because I cut corners, but because I changed how I use AI.

The short version: I don’t use AI inside my editor. I use two AIs in parallel, in the browser, with full context.

Here’s the setup.

I keep two tabs open:

One AI that acts as a "builder". It gets a lot of context and does the heavy lifting.

One AI that acts as a reviewer. It only sees diffs and tries to find mistakes.

That’s it... No plugins, no special tooling. Just browser tabs and a terminal.

The important part is context. Instead of asking for snippets, I paste entire files or modules and explain the goal. I ask the AI to explain the approach first, including tradeoffs, before it writes code. That forces me to stay in control of architecture instead of accepting a blob I don’t understand.

A typical flow looks like this:

Paste several related files (often across languages).

Describe the change I want and ask for an explanation of options. Have a conversation. Pick an approach.

Let the AI implement it across all files. I am involved in the actual code changes, so I'm aware of what's being changed. Sometimes I ask it to generate a few methods and add the new functionality myself. Other times I ask it to regenerate an entire file and then look at the diff.

Copy the diff into the second AI and ask it to look for regressions, missing arguments, or subtle breakage.

Fix whatever it finds.

Ship.

I also interleave long conversations with the AIs about trade-offs etc. It has built up a lot of context about my goals, codebase and what I have built. So I can converse with it at a high level.

The second AI model (ChatGPT 4.5 in my case) catches a lot of things I would otherwise miss when moving fast. Things like “you changed this call signature but didn’t update one caller” or "this default value subtly changed behavior or implied contract”.

What surprised me is how much faster cross-stack work gets. Stuff that used to stall because it crossed boundaries (Swift → Obj-C → JS, or backend → frontend) becomes straightforward because the AI can reason across all of it at once.

I’m intentionally strict about “surgical edits”. I don’t let the AI rewrite files unless that’s explicitly the task. I ask for exact lines to add or change. That keeps diffs small and reviewable.

This is very different from autocomplete-style tools. Those are great for local edits, but they still keep you as the integrator across files. This approach flips that: you stay the architect and reviewer, the AI does the integration work, and a second AI sanity-checks it.

Costs me about $40/month total. The real cost is discipline: always providing context, always reviewing diffs, and never pasting code you don’t understand.

I’m sharing this because it’s been a genuine step-change for me, not a gimmick. Happy to answer questions about limits, failure modes, or where this breaks down.

Developing an AI Data Center

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