100%. It's the accountability that I find most compelling.
My AI assisted software has far FEWER bugs than when I hand-coded everything.
Why? I use it to improve and augment my judgement, rather than replace it. Critical analysis, rapid PoC spikes, more tests, more documentation. Half the tests may be superfluous, and the documentation might be overly verbose...but there are more good tests, and the documentation is at least PRESENT and consistent.
LLM's are information processors. Linters on steroids.
Don't talk to them? Maybe that's the issue..treating them like people instead of the text processors that they are.
I use LLM's consistently every day and haven't had a "chat" with one in many months. Issue commands and request documents. The whole "thinking machine" role-play makes the tool dumber, not smarter, and corrupts your own patterns of thinking into ones that are dependent rather than imperative.
Conversation is literally the least interesting and most error prone use case that LLM's can provide.
This is all down to these AI companies anyways. The simple fact that every single thing that comes out of these AI tools is processed and mangled to imitate human-like speech tells you everything you need to know about how deceitful these things are designed to be.
I want Claude to stop referring to itself as “I”. I want it to reply with imperative sentences, free of personal pronouns. Give me what I ask for; do not pretend to be a human while doing it. But alas, no matter how many times I ask it to stop, it just won’t.
I have been shipping software for twenty years, most of it Rails, and what I own has always run wider than the code I write. The work starts in a room where most of the people are not engineers and the problem has not been named yet, and it carries through the data model, the API contract, the authorization boundary, the background queues, the deploy, and whoever holds the pager afterward. Being accountable across that whole span is a broader claim than full stack, and a harder one to fake.
The depth sits in Rails and Postgres, where I have built async pipelines that had to survive real traffic, payments and third-party integrations that could not quietly drop money, and authorization models that grew more intricate every quarter as the business kept inventing new kinds of users. I reach for Hotwire when the product needs a face, run Docker daily, and treat application security as ordinary hygiene rather than a phase, which means reading the CVEs that touch my stack, running Brakeman and bundler-audit, and reviewing changes against OWASP before they land.
I work with agents every day and skeptically, on the same practice I was using before the tooling existed: discovery before implementation, verification before reference, scope control before anything ships.
Two of the more interesting systems I built are ones I argued to shut down, once the numbers showed they cost more than they were worth, and I wrote up the reasoning both times so the decision outlived the project. That judgment matters more to me than shipping volume, because I would rather be right in month three than committed in month nine.
I am looking for senior IC, staff, or principal work on a team with clear direction and problems worth the depth, whether that runs toward Rails and backend architecture, greenfield systems design, or LLM work that has to earn its place in the product. Available now.
My AI assisted software has far FEWER bugs than when I hand-coded everything.
Why? I use it to improve and augment my judgement, rather than replace it. Critical analysis, rapid PoC spikes, more tests, more documentation. Half the tests may be superfluous, and the documentation might be overly verbose...but there are more good tests, and the documentation is at least PRESENT and consistent.