The problem is the remaining 30% - the next 10-20% starts to require things like multi-agent judge setups, external memory, context management, and that gets you to something that’s probably working but you sure shouldn’t ship to production. As to the last 10% - I’ve seen agentic workflows with hundreds of different agents, multiple models, and fantastically complex evaluation frameworks to try to reduce the error rates past the ~10% mark. By a certain point, the amount of infrastructure and LLM calls are running into several hundred dollars per run, and you’re still not getting guaranteed reliable output.

If you know what you’re doing and you know where to fit the LLMs (they’re genuinely the best system we’ve ever devised for interpreting and categorizing unstructured human input), they can be immensely useful, but they sing a siren song of simplicity that will lure you to your doom if you believe it.

It feels like they’re a few versions behind what I’m doing, which is… odd.

Self-hosting a plane.io instance. Added a plane MCP tool to my codex. Added workflow instructions into Agents.md which cover standards, documentation, related work, labels, branch names, adding of comments before plan, after plan, at varying steps of implementation, summary before moving ticket to done. Creating new tickers and being able to relate to current or others, etc…

It ain’t that hard. Just do inception (high to mid level details) create epics and tasks. Add personas, details, notes, acceptance criteria and more. Can add comments yourself to update. Whatever.

Slice tickets thin and then go wild. Add tickets as your working though things. Make modifications.

Why so difficult?

So adding a QA agent, while it sounds logical, just ends up being even more of this. Rather than converging on a solution, they just get all out of whack. Until that is solved, far better just to have your dev agent be smart about doing its own QA.

The only way I could see the QA agent idea working now is if it had the power to roll back the entire change, reset the dev agent, update the task with some hints of things not to overlook, and trigger the dev process from scratch. But that seems pretty inefficient, and IDK if it would work any better.

If you're using the agent to produce any kind of code that has access to manipulate the filesystem, may as well have it understand its own abilities as having the entirety of CRUD, not just updates. I could easily see the agent talking itself into working around "only be able to edit" with its other knowledge that it can just write a script to do whatever it wants. This also reinforces to devs that they basically shouldn't trust the agent when it comes to the filesystem.

As for pwd for existing projects, I start each session running tree local to the part of the project filesystem I want to have worked on.

I'm very interested in what this will look like for outputs from other job functions. And if we'll end up with a similar framework that makes non-deterministic, often-wrong LLMs easier to work with.

Very interesting.