ashlionTimeless/mike
A hands-on effort by ashlionTimeless to make Mike easy to run in a container and easy to watch while it works.
This is Mike with the plumbing turned up. Everything ashlionTimeless has shipped so far points in one direction: making the app straightforward to stand up and, once it's running, easy to see inside. The fork gains a defined build-and-run setup so the whole thing comes up as a package rather than a pile of manual steps, and it threads logging through the app so you're not guessing about what happened.
The centerpiece is an observability layer for agent runs. Each run gets captured in detail, and there's a separate reader app whose only job is to let you page back through those runs and read what the agent actually did, step by step. It's the kind of work you do when you plan to operate something seriously, not just demo it.
There's no rebrand here and no legal-domain specialization layered on yet - this is foundational, operator-facing work. If you run Mike yourself, or you want to understand its behavior rather than take it on faith, ashlionTimeless is building the fork you'd want. Click through to GitHub for the specifics.
What's in it
- Containerized deployment A defined build-and-run setup for both services, so the fork comes up as a reproducible package instead of a manual checklist.
- Pervasive logging Logging threaded through the application, so its behavior is traceable rather than opaque when you run it.
- Agent-run observability The fork's largest investment: each agent run is captured in detail, giving you a record of exactly what happened.
- Standalone log reader A separate reader app dedicated to browsing captured runs and walking through what the agent did, step by step.
Direction
infrastructureanalytics
Activity
Threads of work (detailed view)
ashlionTimeless gives the AI a flight recorder
A new logging layer records every step an agent takes during a run, then makes those traces readable.
ashlionTimeless is getting the fork ready to run in production
A maintainer checkpoint that's less about legal-AI features and more about turning the fork from a laptop experiment into something you can actually deploy and watch.
ashlionTimeless wires the fork to run clean, watch itself, and open a reader
A batch of operational work aimed at making the fork easy to stand up and observe, capped by a brand-new app - though none of it landed upstream.
Pull requests (detailed view)
✅ Merged (1)
ashlionTimeless · opened 18d ago · merged 18d ago by ashlionTimeless ⛔ Closed without merge (1)
ashlionTimeless · opened 18d ago · closed 18d ago