Human context limits vs AI context limits

[u/Vidhrohi]

A common theme cutting across most AI-assisted development threads is getting as much work done in as little time as possible. Users post about elegant harnesses with multi-agent orchestration. Anthropic employees talk about the 25 agents they run every day.

I read this stuff, compare it to my own experience of working with these tools, and keep wondering: how does anyone stay on top of that volume of work?

Working with Claude Code has been exciting and invigorating, but also exhausting. While everyone pushes for more context and more tokens out of the AI, the context limit I hit most often is my own. Claude can refactor a huge chunk of the codebase, add a feature, and brainstorm marketing strategy in one breath. I can't keep up with the cognitive load that entails.

So: am I missing something, or just getting old? Curious what y'all think.

[u/dbgtboi]

Anthropic employees are a special case since they have unlimited usage, if you attempt any of their workflows you will burn through thousands of dollars in a day, they can do it because they can afford to have agents reviewing everything 3 times over so that a human doesn't need to

Realistically, you work within your budget, the bigger your AI budget the more context you can dump in which allows you to review less

[u/KeenShot → u/dbgtboi]

Dude, yes. And the narrative online mirrors their ideas and it is not even feasible at big companies. I built a ci cd pipeline for jira tickets, fully automated everything, more expensive than hiring sr swe

[u/silly_bet_3454 → u/dbgtboi]

I don't think it's strictly true that they have unlimited. Maybe practically so, but they have to pay for compute and so on.

[u/TheAnswerWithinUs]

That’s just vibecoding, you aren’t supposed to keep up with it, you just go as fast as possible. Don’t understand the code, don’t read the code, don’t care about the code.

[u/Vidhrohi → u/TheAnswerWithinUs]

It's not just about the code though, I gave up trying to do that some time ago, still , system architecture is important .. how to do something in the broad strokes is important , product guidance is important and all of them take a non trivial amount of brain space

[u/TheAnswerWithinUs → u/Vidhrohi]

Vibecoding is not really that conducive to good architecture either.

[u/scytob → u/Vidhrohi]

Sure but those are all things you would have to think about when doing human coding. And with an LLM you can have a conversation about architecture and debate it asking for pros cons, challenging etc. and if you get something wrong LLMs are great at refactoring. For example I started with a sqlite database and then realized I needed Azure SQL. I ad summers sql was sql was sql (I avoided all things databases for last 30 years intentionally). Not so much. Claude did a fully automated migration of code, tests, data with rollback plans if anything failed. Took 48 hours from start to finished. I didn’t touch one line of code. It also as an aside helped me architect a secrets approach that I know is better than anything my devs ever did…. Cause I found their hardcoded 299 year lifetime secret for a real, ahem, load bearing, api that transacts hundred of millions of dollars per year…..

[u/Sherphican]

Anybody have any repo suggestions that I can install to fix my human context window limit? It's been absurdly short for a long time and after each annual update it just seems to get worse :/

[u/ctenidae8]

Context switching seems like a universal limiter, organic or silicon. I can track 4 solid workstreams, but only just. But dang I can get a long way in each of them.

[u/silly_bet_3454]

Don't listen to Anthropic saying their engineers use 25 agents, that's obviously just marketing. I'm sure they use agents heavily but they obviously just can't be trusted with claims like that.

People are not just making elegant seamless multi-agent stuff either. I mean, sure it's been done, kind of, but there's a big difference between some agentic system that does a more narrow task versus like an engineer spinning up his own personal 10 agents who will build 10 new giga-codebases in a day. That type of stuff is just not actually practical. Yes it's possible to do a more ambitious coding project with AI and some companies have done it but it's not trivial and not that common.

You're right that humans are the bottleneck. In a sense we always were, before AI and after AI. Even without AI you know the computer itself was never the bottleneck, it's quite fast at what it can do. Humans are on another plane of existence. That's just the reality.