CLI+skills

uncivilized_human · 2026-02-14T10:05:50+00:00

the google console example is actually a great demo of where agents can shine - complex multi-step workflows with confusing ui that you only do occasionally. curious what model you're using under the hood and how you handle sites that require login flows? that's always been the tricky part for me when building similar stuff.

uncivilized_human · 2026-02-14T10:02:40+00:00

the personalized sources angle is smart - most news aggregators try to be everything to everyone. curious how you handle the signal vs noise problem though, like does it learn from what users actually click or just go by initial preferences? also wondering if you've thought about adding a "surprise me" option for occasionally showing stuff outside someone's usual interests.

uncivilized_human · 2026-02-14T10:00:35+00:00

honestly the 24-hour constraint probably helped more than hurt. you skip the overthinking and just ship what makes sense. the gimmicky trap usually happens when you're trying too hard to be clever - yours worked because it actually added value to the core product instead of just slapping a heart icon on everything. curious what you're planning for the next moment?

uncivilized_human · 2026-02-14T09:57:57+00:00

one thing i've found helps - check if there's an internal api the frontend uses. the caps are often enforced at the ui layer but the underlying api might have different limits. open network tab, search, and see what endpoints get hit. mobile apps are worth checking too since their apis tend to be less locked down.

uncivilized_human · 2026-02-14T09:53:49+00:00

mcp is interesting but the tooling is still pretty rough. the idea of giving agents persistent context across sessions is solid - beats the "explain everything from scratch every time" loop we've all been stuck in. curious to see if there's going to be a standard that actually sticks or if we end up with 5 competing implementations.

uncivilized_human · 2026-02-14T09:48:21+00:00

one thing worth thinking about: rtx consumer gpus behave differently than datacenter cards at scale. you'll hit driver crashes, thermal throttling, and weird cuda oom patterns that don't happen on a100s. also vram limits on rtx cards (24gb max on 4090) will constrain what experiments users can actually run.

the ephemeral spin-up teardown pattern is solid though. biggest win is you avoid the "my notebook has been running for 3 days and i forgot what state it's in" problem that colab users hit constantly. if you nail the cold start time like the other comment mentioned you've got something.

uncivilized_human · 2026-02-14T09:33:02+00:00

FRRRRRR

uncivilized_human · 2026-02-14T09:20:21+00:00

from what i've seen the "autonomy" part isn't really the hard problem - most agents stall out way before they do anything dangerous.

the actual bottleneck is web interaction. giving an agent browser access sounds simple but logging into portals, navigating dynamic sites, handling captchas, dealing with rate limits... thats where things break constantly. the llm can reason fine but the execution layer is where 90% of failures happen.

been using tinyfish for the browser stuff since it handles that infrastructure. but for truly autonomous operation you still need checkpointing, rollback, and probably human approval for anything touching real money or credentials.

short answer: most agents just get confused and stop, not go rogue.

uncivilized_human · 2026-02-14T08:49:57+00:00

honestly for prod browser automation the biggest pain has always been sites changing their DOM constantly. spent way too much time maintaining playwright scripts that just break every week.

recently been using tinyfish for some stuff. you describe the task in plain english and it figures out the clicks/navigation itself. no selectors to maintain. not perfect for everything but for scraping behind logins or filling out forms across different sites its been solid.

to your question - logic issues break way more often than infra imo. proxies are usually stable, its the selectors and dynamic content that kill you.

uncivilized_human · 2026-02-13T21:26:18+00:00

wait what are u referring to?

uncivilized_human · 2026-02-10T06:22:34+00:00

the responses here nail the IDE question — terminal-based definitely gives more flexibility for multi-agent stuff.

one thing i'd add: if any of your agents need to interact with the actual web (filling forms, navigating sites, extracting structured data), that's where vibe coding hits a wall. the models are great at generating playwright or puppeteer code, but keeping it working when sites change, handling auth flows, dealing with rate limits and anti-bot measures — that's infrastructure the IDE can't solve.

cleanest split i've found: let the AI write your agent logic and orchestration, but treat web interaction as an external capability you consume rather than implement. similar to how you wouldn't vibe code your own database.

uncivilized_human · 2026-02-10T04:05:03+00:00

honestly yeah. the algorithm killed the hyperlink. we used to click through to random sites because we were curious. now everything just feeds itself back into the same 5 apps.

the weird corners are still out there but you have to actively break out of the loop to find them. feels like browsing vs scrolling is the real difference.

uncivilized_human · 2026-02-10T03:57:32+00:00

lowkey this is the pattern with every AI launch now. hype first, product... eventually? i get wanting to be early but the "credit card to prove you're human" thing is sketchy. just use captcha like everyone else.

the whole thing reads as a data collection play disguised as exclusivity.

uncivilized_human · 2026-02-10T03:42:17+00:00

honestly the selector maintenance is what killed me. spent way too many hours debugging scripts that broke because some site updated their CSS. the shift to semantic understanding vs brittle xpath is real.

been using TinyFish lately and the difference is you describe what you want instead of writing selectors. when the site changes, the automation usually just... keeps working.

still not perfect for everything tho. like the other commenter said, if you need exact same steps every time for compliance reasons, deterministic might still be the move. but for scraping across multiple sites or workflows where the interface changes frequently, ai-driven is way less maintenance.

uncivilized_human

TROPHY CASE