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  _zoltan_
  "In this post, I’ll cover a third, not-so-obvious approach: building ways for the agent to validate more of its own work before a human has to step in. "this has been an obvious thing to do since at least January (since Geoffrey Huntley published "everything is a ralph loop"), and this is how I've been working: build enough orchestration tooling to be able to automate everything: development container bringup, building it, running the unit tests, doing integration testing, and using the software as eventually an end user. then to iterate set performance goals on an already solid basis so the automated agent ("gym") can go and iterate autonomously, and let you know when it's "done".I understand this probably does not work if you're on some subscription and not using the API (tokens burn fast), but this has been extremely productive for me.
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  xg15
  Isn't this a bit of an incorrect usage of the term "backpressure"?OP quoted the correct definition right at the start:> In systems engineering, backpressure is the mechanism by which a downstream component signals upstream that it can't accept more work(the "downstream component" being the human reviewer in this case)But the measures they propose don't actually do that. They are more like fixed throttle elements which would slow down the rate of submissions of an agent and weed out some low-quality submissions before hitting "downstream".I'm missing the connection to the actual capacity (or will) that the human developers have to review the submissions.
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  pshirshov
  A very long post about a simple and very obvious idea with many different implementations.The three main problems are 1) API usage is deadly expensive 2) Claude is about to make all automation very expensive 3) all the flows where a model has the initiative are strictly biased towards unwarranted stops (checkpointing).Also, I won't call that "backpressure", there is no producer-consumer disbalance or something similar. From what I can see, the author just proposes a structured feedback loop. That's a discussion about organizational principles for system which consist of multiple unreliable but very complex components and this "backpressure" is just one of the aspects. Personally I find the viable system model framework productive as both a mental model and literal implementation guideline.Lesser problem is that agent SDKs are bad and building a custom harness is hard.
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  vermilingua
  > It should also reduce the number of low-quality PRs your teammates have to review for details the agent should have caught itself.Oh boy.
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  denysvitali
  This seems to be the coding agents 101: build a strong feedback loop. Am I missing something?
• SkiFreeWin3
  Looks like plenty of recent prior art on this:https://pura.xyzhttps://github.com/puraxyz/puraxyz/blob/main/docs/paper/main...
• EMM_386
  I always use a standard workflow and it has never been a problem.- Define the task and the goal, write a short spec document (markdown is fine)- Point the agent at it in plan mode and have it write the plan to disk with phases. Iterate on its plan if necessary here and now.- Have each agent tackle a phase and have it update it as a living document (switch models if some phases are more difficult than others)- Clear and repeat until doneI've never had to overcomplicate this and it's worked both on enterprise-scale projects and personal projects. I am not sure what I'm missing - if anything.
• jon-wood
  This what hooks[1] are for, except hooks allow specifying criteria in certain conditions (like the agent believing it’s done and ready to hand back to the user) in a manner that the agent won’t just forget about once it’s a few turns deep, and doesn’t require triggering a whole other LLM instance to read some plain text instructions while you hope it interprets them correctly.It absolutely makes sense to have a system in place that allows the code generated by an LLM to be automatically validated but there’s no need to resort to a non-deterministic system for these sort of deterministic pass/fail conditions.[1] https://code.claude.com/docs/en/hooks
• mark_l_watson
  Interesting ideas for generalizing goals to reduce human labor in human <—> agent interactions. That said, maybe it is better to set up customized skills and infrastructure for large projects? At our early stage of trying to capture value of agentic systems, the good ideas in this article might be premature optimization.
• yearesadpeople
  If the systems invariants are well defined, and a suite of conformance + requirements tests (ensuring invariance is respected) are defined, wouldn't this be a broad - _'base case'_ - approach in general?
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  cadamsdotcom
  Everyone looking into this and other verification should be moving away from long prompts and complex skills, and looking into hooks.If you put all these checks in your stop hook and your git commit hook, your repo docs can tell your agent that checks will run automatically when it stops work, and it should fix any problems found.It’s wonderful to reintroduce determinism at the QA end of your process. I find it very calming to know the agent can’t skip or forget to check its work because with hooks the checks are run by the harness.
• xlii
  If that's third then I have fourth. Self plug obviously, but figured that I'd like something between smart autocomplete and an agent - an autocomplete that has wider context.Called it rik, and it's on GitHub if anyone's interested checking it.https://github.com/exlee/rik
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  dnnddidiej
  Oh this is 101. Anyone not doing this? If not do it now!
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  wellpast
  I’m willing to be wrong but this industry-wide emphasis on AI creative/coding workflows seems way over-engineered.Ime successful creative execution looks like micro-iterations where each output informs the next creative move.I can build something incredibly fast from essentially caveman grunt instructions through an LLM harness, iterating as I go.Optimizing for feeding a huge plan to an agent sounds to me like a net waste of time. And looking over the shoulder of industry peers trying to do this, I don’t see their outputs or throughput some remarkable improvement over what I can produce with minimal fanfare usage.
• cyanydeez
  interesting idea, unfortunately programming the structure is equivalent (P=NP) to just programming itself. same as TDD.as usual, the tool isnt really doing whats listed on its label.however, people are different so this might improve someones capability to deploy LLMs. might even provide better evidence where actual brain power is needed.
• haeseong
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• jongguk
  [dead]
• indianrestrooms
  [dead]