[criley2]

Imo current models can already break things up into bite sized pieces. The limiter I've seen is twofold

1) Maintaining context of the overall project and goals while working in the weeds on a subtask of a task on an epic (so to speak) both in terms of what has been accomplished already and what still needs to be accomplished

and 2) Getting an agentic coding tool which can actually handle the scale of doing 50 small projects back to back. With these agentic tools I find they start projects off really strong but by task #5 they're just making a mess with every change.

I've played with keeping basically a dev-progress.md file and implementation-plan.md file that I keep in context for every request and end each task by updating files. But me manually keeping all this context isn't solving all my problems.

And all the while, tools like Cline are gobbling up 2M tokens to make small changes.

[jhrmnn]

> Maintaining context of the overall project and goals while working in the weeds on a subtask of a task on an epic (so to speak) both in terms of what has been accomplished already and what still needs to be accomplished

This is a struggle for every human I’ve ever worked with

[mmis1000]

This is probably the biggest difference between people who wrote code and people that should never write code. Some people just can't write several connected progtam file without logical conflict. It's almost like their brain context is only capable for hold one file.

[drob518]

True, but if AI only gets as useful as an average developer, it isn’t that useful.

[pertymcpert]

Yes. I wonder if the path forward will be to create systems of agents that work as a team, with an "architect" or "technical lead" AI directing the work of more specialized execution AIs. This could alleviate the issue of context pollution as the technical lead doesn't have to hold all of the context when working on a small problem, and vice versa.

Shit. Do we need agile AI now?

[Rudybega]

This is kind of what the modes in roo code do now. I'm having great success with them and having them as a default just rolled out a couple days ago.

There are a default set of modes (orchestrator, code, architect, debug, and ask) and you can create your own custom ones (or have roo do it for you, which is kind of a fun meta play).

Orchestrator basically consults the others and uses them when appropriate, feeding in a sensible amount of task definition and context into the sub task. You can use different LLMs for different modes as well (I like Gemini 2.5 Pro for most of the thinking style ones and gpt o4-mini for the coding).

I've done some reasonably complicated things and haven't really had an orchestrator task creep past ~400k tokens before I was finished and able to start a new task.

There are some people out there who do really cool stuff with memory banks (basically logging and progress tracking), but I haven't played a ton with that yet.

Basic overview: https://docs.roocode.com/features/boomerang-tasks

Custom Modes: https://docs.roocode.com/features/custom-modes