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For those of you for who it is working: show your code, please.
Where it consistently fails: anything involving the interaction between systems. If a bug spans a queue producer and its consumer, or the fix requires understanding how a frontend state change propagates through API calls to a cache invalidation - the model gives you a confident answer that addresses one layer and quietly ignores the rest. You end up debugging its fix instead of the original issue.
My stack: Claude Code (Opus) for investigation and bug triage in a ~60k LOC codebase, Cursor for greenfield work. Dropped autocomplete entirely after a month - it interrupted my thinking more than it helped.
Professionally I hardly use the tools for coding, since I’m in an architecture role and mostly write design docs and do reviews. And I write the occasional prototype.
I have started building tools to integrate copilot (Opus) better with $CORP. This way I can ask it questions across confluence and github.
Leveraging Claude for a project feels very addictive to me. I have to make a conscious effort to stop and I end up working on multiple projects at the same time.
my team is anti-AI. my code review requests are ignored, or are treated more strictly than others. it feels coordinated - i will have to push back the launch date of my project as a result. another teammate added a length check to an input field, and his request was merged near instantly, even though it had zero unit testing. this team is incredibly cooked in the long term, i just need to ensure that i survive the sh…
it sounds like you might have wasted your team's time previously and now they don't trust the code you put up with a PR. Maybe you can do something to improve your relationship with them? As a sidenote, I highly doubt they are cooked longterm. Using AI is not exactly skilled labor. If they want or need I'm sure they could learn patterns/workflows in like an afternoon. As things go on it will only get easier to use.
Like yeah sorry... not everyone has to be a risk-taker. Many people like to observe and await to see what new techniques emerge that can be exploited.
For those of you for who it is working: show your code, please.
Why is this the attitude when it comes to AI? Can you imagine someone saying “please provide your code” when they claim that Rust sped up their work repo or typescript reduced errors in production?
It works really well (using Claude Code and Opus 4.6 primarily). Incremental changes tend to be well done and mostly one-shotted provided I use plan mode first, and larger changes are achievable by careful planning with split phases.
We have skills that map to different team roles, and 5 different skills used for code review. This usually gets you 90% there before opening a PR.
Adopting the tool made me more ambitious, in the sense that it lets me try approaches I would normally discard because of gaps in my knowledge and expertise. This doesn't mean blindly offloading work, but rather isolating parts where I can confidently assess risk, and then proceed with radically different implementations guided by metrics. For example, we needed to have a way to extract redlines from PDF documents, and in a couple of days went from a prototype with embedded Python to an embedded Rust version with a robust test oracle against hundreds of document.
I don't have multiple agents running at the same time working on different worktrees, as I find that distracting. When the agent is implementing I usually still think about the problem at hand and consider other angles that end up in subsequent revisions.
Other things I've tried which work well: share an Obsidian note with the agent, and collaboratively iterate on it while working on a bug investigation.
I still write a percentage of code by hand when I need to clearly visualise the implementation in my head (e.g. if I'm working on some algo improvement), or if the agent loses its way halfway through because they're just spitballing ideas without much grounding (rare occurrence).
I find Elixir very well suited for AI-assisted development because it's a relatively small language with strong idioms.
For those of you for who it is working: show your code, please.
https://repo.autonoma.ca/treetrek
There's still some work to do on the rendering side of model objects. Developing the syntax highlighting rules for 40 languages and file formats in about 10 minutes was amazing to see.
https://repo.autonoma.ca/repo/treetrek/tree/HEAD/render/rule...
I work at a FAANG. Professionally, I have had almost no luck with it, outside of summarizing design docs or literally just finding something in the code that a simple search might not find: such is this team's code that does X? I am yet to successfully prompt it and get a working commit. Further, I will add that I also don't know any ICs personally who have successfully used it. Though, there's endless posts of peopl…
Experience depends on which FAANG it is. Amazon for example doesn't allow Claude Code or Codex so you are stuck with whatever internal tool they have Meta, despite competing with these, is open to let their devs use better off the shelf tools.