Try this: Keep your CLAUDE.md as simple as possible, disable skills, and request Opus to start a subagent for each of the files and process at most 10 at a time (so you don't get rate limited) and give it the instructions in the skill for whatever processing you're doing to the markdowns as a prompt, see if that helps.

yes we had to tune the claude.md and the skill trigger quite a bit, to get it much better. But to be honest also 4.6 did improve it quite a bit. Did you run into your issues under 4.5 or 4.6?

you can host the whole thing locally :)

To clarify, our data set consists solely of Claude Code sessions, specifically those with a human behind them. Rudel AI, in its current form, focuses on "How teams code with AI". We have plans to expland to a larger range of agentic observability use cases.

What tools do you use to run your analysis?

Can you expand on the USDC friction piece?

1. can only partly be answered, because we can only capture the "edits" that are prompted, vs manual ones. 2. for us actually all of them, since we do everything with ai, and invest heavily and continously, to just reduce the amount of iterations we need on it 3. thats a good one, we dont have anything specific for debugging yet, but it might be an interesting class for a type of session.

this jumped out at me too. What counts as "abandoned"? How do you know the goal was not simply met?

I have longer threads that I don't want to pollute with side quests. I will pull up multiple other chats and ask one or two questions about completely tangential or unrelated things.

I agree. In my experience: "single-purpose sessions for small tasks" is the key

This is a great idea, documented and added to our roadmap.

insights is straight ego fluffing - it just tells you how brilliant you are and the only actionable insights are the ones hardcoded into the skill that appear for everyone. things like be very specific with the success criteria ahead of time (more than any human could ever possibly be), tell the llm exactly what steps to follow to the letter (instead of doing those steps yourself), use more skills (here's an example you can copy paste that has 2 lines and just tells it to be careful), and a couple of actually neat ideas (like having it use playwright to test changes visually after a UI change)

Ohh this is exciting, I kinda overlooked it. I assume there are still a lot of differences, especially for accross teams. But I immediately ran it, when I saw your comment. Actually still running.

true, the best comes out of it when one uses claude code and codex as a tag team

Hey, here is Rafa, another Rudel AI developer. The ultimate goal is to make developers more productive. Suddenly, we had everyone having dozens of sessions per day, producing 10X more code, we were having 10X more activity but not necessarily 10X productivity.

With this data, you can measure if you are spending too many tokens on sessions, how successful sessions are, and what makes them successful. Developers can also share individual sessions where they struggle with their peers and share learnings and avoid errors that others have had.

It will be only enabled for the repo where you called the `enable` command. Or use the cli `upload` command for specific sessions.

Or you can run your own instance, but we will need to add docs, on how to control the endpoint properly in the CLI.

it's reasonable to note that w/o sharing the data these findings can't be audited or built upon

but i think the prior on 'this team fabricated these findings' is v low

Its our own sessions, from our team, over the last 3 months. We used them to develop the product and learn about our usage. You are right, they will remain closed. But I am happy to share aggregated information, if you have specific questions about the dataset.

> A local-first desktop and web app for browsing, searching, and analyzing your past AI coding sessions. See what your agents actually did across every project.

Thx for the link - sounds great !

Our focus is a little bit more cross team, and in our internal version, we have also some continuous improvement monitoring, which we will probably release as well.

Cool, whats the link? We have some learnings, especially in the "Skill guiding" part of our example.

Ah sorry, the readme is more about how to run the repo. The "product" information is rather on the website: https://rudel.ai

We used it across the team, and when you want to bring metrics together across multiple people, its easier on a server, than local.

the skill usage was one of these "I am wondering about...." things, and we just prompted it into the dashboard to undertand it. We have some of these "hunches" where its easier to analyze having sessions from everyone together to understand similarities as well as differences. And we answered a few of those kinda one off questions this way. Ongoing, we are also using a lot our "learning" tracking, which is not really usable right now, because it integrates with a few of our other things, but we are planning to release it also soon. Also the single session view sometimes helps to debug a sessions, and then better guide a "learning". So its a mix of different things, since we have multiple projects, we can even derive how much we are working on each project, and it kinda maps better than our Linear points :)

Team of 4 engineers, 1 data & business person, 1 design engineer.

I would say roughly equal amount of sessions between them (very roughly)

Also maybe 40% of coding sessions in large brownfield project. 50% greenfield, and remaining 10% non coding tasks.

I was about to say they have a self-hosting guide, but I see they use third party services that seem absolutely pointless for such a tiny dataset. For comparison, I have a project that happily analyzes 150 million tokens worth of Claude session data w/some basic caching in plain text files on a $300 mini pc in seconds... If/when I reach billions, I might throw Sqlite into the stack. Maybe once I reach tens of billions, something bigger will be worthwhile.

The docker-compose contain everything you should need: https://github.com/obsessiondb/rudel/blob/main/docker-compos...

Yes we added codex support, but its not yet extensively tested. Session upload works, but we kinda have to still QA all the analytics extraction.

The tool does have a quite detailed view for individual sessions. Which allows you to understand input and output much better, but obviously its still mysterious how the output is generated from that input.