I’ve finally written a deep-dive into the 250-hour build process behind syntaqlite.

While AI agents were the only reason I finally overcame the 8-year inertia to start this project, using them taught me a lot about the psychological toll of AI-assisted engineering and the trap of "vibe-coding."

The full post-mortem with journal logs and commit history:
https://lalitm.com/post/building-syntaqlite-ai/

(Thread on the key takeaways follows)

Eight years of wanting, three months of building with AI

For eight years, I’ve wanted a high-quality set of devtools for working with SQLite. Given how important SQLite is to the industry1, I’ve long been puzzled that no one has invested in building a really good developer experience for it2. A couple of weeks ago, after ~250 hours of effort over three months3 on evenings, weekends, and vacation days, I finally released syntaqlite (GitHub), fulfilling this long-held wish. And I believe the main reason this happened was because of AI coding agents4. Of course, there’s no shortage of posts claiming that AI one-shot their project or pushing back and declaring that AI is all slop. I’m going to take a very different approach and, instead, systematically break down my experience building syntaqlite with AI, both where it helped and where it was detrimental. I’ll do this while contextualizing the project and my background so you can independently assess how generalizable this experience was. And whenever I make a claim, I’ll try to back it up with evidence from my project journal, coding transcripts, or commit history5.

Lalit Maganti
Working with coding agents feels like a slot machine. You send a prompt, wait 30 seconds, and get something great or something useless. I found myself at 1am thinking "one more prompt" even when I knew it wouldn't work. When I was tired, my prompts got vague, the output got worse, and I'd try again anyway. It is a dopamine trap that prioritizes shipping over thinking.
At several points, I lost the mental model of the codebase. Instead of "change FooClass," I was saying "change the thing that does Bar." I had become the engineering manager who doesn't actually understand the code—the exact person I used to complain about. AI makes it dangerous to stop owning the "why" behind your implementation.
AI has no sense of time. It sees a codebase as a snapshot but doesn't feel why decisions were made, reversed, or avoided. Losing a senior engineer hurts a team for similar reasons; AI never had that institutional memory to begin with.