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Show HN: LoopGain – Stop agent loops with control theory, not max_iterations

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Re: Show HN: LoopGain – Stop agent loops with control theory, not max_iterations

#11

Post by N_Lens »

stephantul wrote: post #9
fitz2882 wrote: post #5

Earlier quoted context omitted.

Hey, thanks for your comment. This is an idea that I thought up, researched, developed, and in the end built a useful, working, open source tool. Yes I used AI to assist me in the process, it's a complicated subject. But I take your point that it would be better to write in my own words. You're right, lesson learned. Anyhow, whether I used a tool like AI to assist me or not, I am here to share something I built that…

I don’t think this is the right take-away though. Your fully generated project description makes people lose faith in the actual project. If you went through the trouble of writing the whole code yourself, why generate the comment presenting it to the public wholesale.

He’s passionate about using AI!

Re: Show HN: LoopGain – Stop agent loops with control theory, not max_iterations

#12

Post by gavmor »

fitz2882 wrote: post #2

Hey HN — Dave here. While building a multi-agent system a couple of years ago, I kept noticing that the diagrams of agents passing feedback to each other looked just like the electrical circuit diagrams from control theory. I got curious whether the established math transferred, and to my surprise it did. LoopGain is the first product of that research: an open-source library that replaces the max_iterations=N cap on…

I've got an application for this. Will try and get some benchmarks in the next few weeks. We're definitely attempting to converge on a quality inference without wasting tokens/time.

For now, we're passing the first pass to the humans, and that's roughly 80 for 20, but to get the last 20 without blowing up our token spend? This might be the approach.

Thanks for the write up comment, btw.

Re: Show HN: LoopGain – Stop agent loops with control theory, not max_iterations

#13

Post by fitz2882 »

gavmor wrote: post #12
fitz2882 wrote: post #2

Hey HN — Dave here. While building a multi-agent system a couple of years ago, I kept noticing that the diagrams of agents passing feedback to each other looked just like the electrical circuit diagrams from control theory. I got curious whether the established math transferred, and to my surprise it did. LoopGain is the first product of that research: an open-source library that replaces the max_iterations=N cap on…

I've got an application for this. Will try and get some benchmarks in the next few weeks. We're definitely attempting to converge on a quality inference without wasting tokens/time. For now, we're passing the first pass to the humans, and that's roughly 80 for 20, but to get the last 20 without blowing up our token spend? This might be the approach. Thanks for the write up comment, btw.

Hey gavmor, thanks for your comment! Let me know if you need any assistance, I would be happy to help or get any feedback at dave@loopgain.ai

Re: Show HN: LoopGain – Stop agent loops with control theory, not max_iterations

#14

Post by fitz2882 »

Hey everyone, I just want to clear some things up here based on the comments:

I (Dave) am a real person, and yes I used AI to help me with every part of this project, including my initial comment introducing it here. That was a mistake, I should have just written it myself. I am a self-taught developer who is passionate about AI development and curious about seeing what I can do with it. I come up with my ideas and test them with the help of AI. Then I have AI help me understand it. This all started because I was building multi-agent systems, just experimenting, and I noticed that they looked to me like electrical circuit diagrams. So it made me curious if there was any cross over between the laws of electrical engineering and how it might apply to agentic systems. With AI today you can pursue any idea you have, so I have fun by seeing what happens when you take concepts from one established field and apply them to something else. I had AI do deep research on electrical engineering concepts, and asked it to research how those might be applied to agentic systems. It came up with interesting ideas, so I had it plan scientific experiments on ones that looked promising, and the one that looked like the most obvious application is what turned into LoopGain. With the help of AI I developed it into a working system, created a website and company around it, made the project open source, wrote blog articles about the experiments, then asked AI how to best share it with the world. I love developing useful tools and researching the edge of AI capabilities, so that is what I am doing here. Thanks for reading.

Re: Show HN: LoopGain – Stop agent loops with control theory, not max_iterations

#15

Post by killix »

fitz2882 wrote: post #2

Hey HN — Dave here. While building a multi-agent system a couple of years ago, I kept noticing that the diagrams of agents passing feedback to each other looked just like the electrical circuit diagrams from control theory. I got curious whether the established math transferred, and to my surprise it did. LoopGain is the first product of that research: an open-source library that replaces the max_iterations=N cap on…

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Re: Show HN: LoopGain – Stop agent loops with control theory, not max_iterations

#17

Post by fitz2882 »

prabhanjana_c wrote: post #16

Curious to understand , if this can be added as a skill to claude code cli /goal along with. I see it supports claude code agent sdk.

Hey, sorry I didn't see your comment until now. Yes I just added a Claude Code plugin that allows LoopGain to work with /goal.

/goal's checker knows when it's done but not when it has stopped improving. The plugin sets a Stop hook that, after each turn, runs your own verifier (such as failing-test count) and stops the loop when LoopGain sees it's converged or stalled instead of a guessed cap.

- two install commands:

   - /plugin marketplace add loopgain-ai/loopgain-plugin

   - /plugin install loopgain
Any skill that iterates can just call the LoopGain library from a small script to decide when to stop instead of a hardcoded cap. I do this in my own skills. It recurses until the number of unresolved pieces stops dropping, no fixed depth limit.

You can also point any AI agent to the repo so it learns how LoopGain works and it will be able to help you set it up how you like. It's open-source.

Re: Show HN: LoopGain – Stop agent loops with control theory, not max_iterations

#18

Post by killix »

fitz2882 wrote: post #17
prabhanjana_c wrote: post #16

Curious to understand , if this can be added as a skill to claude code cli /goal along with. I see it supports claude code agent sdk.

Hey, sorry I didn't see your comment until now. Yes I just added a Claude Code plugin that allows LoopGain to work with /goal. /goal's checker knows when it's done but not when it has stopped improving. The plugin sets a Stop hook that, after each turn, runs your own verifier (such as failing-test count) and stops the loop when LoopGain sees it's converged or stalled instead of a guessed cap. - two install commands:…

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