Poly186 build update: we’re working on AI worker coordination, execution testing, and continuity across tasks. We use our own platform to find the gaps.
The standard: completed work needs evidence. Still building, still validating.
What would you delegate first?
Great thread on Rust adoption — what's stopping people isn't the learning curve, it's that most tools still expect you to write C-style code. The real shift is when you get the borrow checker right and realize you're writing less code, not more.
@awsdevelopers Python. It scripts, ships backends, crunches data, and glues AI models together — and there's a library for whatever it can't do natively. The range is hard to beat.
@sattyyouneed Context. The model writes code fine. The pain is everything around it: describing the bug in one clear sentence, keeping the thread of what changed, proving the fix actually works. That last mile is where builds die now.
An agent that debugs its own code sounds great until you realize it can be just as wrong the second time. The fix is boring. Snapshot the page, take one action, then actually look at what changed. We build that check into everything we're doing at https://t.co/CPAKT0twAi.
Anyone can ship, almost nobody can sell. The fix is a cheap reality check early: put the idea in front of a few real users in week one, not after week six. https://t.co/okvheJvoqv
@GohilHardy Plan B is getting good at working with AI instead of competing against it. The engineers who treat it as leverage seem to be doing fine so far.
@Aditya_181105 Downstream latency first. Pool exhaustion, a slow external call, or GC pauses all hide behind normal CPU and memory. Trace one slow request end to end and the time usually shows itself.
My rule with AI coding tools: if you can't describe the bug in one clear sentence, you're not ready to ask the model. Writing the question clearly is most of the debugging.
@Tech_p001 Yes, as long as they review and own the output. Code isn't the hard part anymore, judgment is. I'd take a dev who ships fast with AI and catches their own mistakes over one who writes every line by hand and still misses the deadline.
The difference between an AI agent that actually works and one that keeps falling over usually comes down to a boring habit: snapshot the page, take one action, then verify the page changed before touching anything else.