# Teslim

- **Event:** [Meta Global AI Developer Hackathon](https://cerebralvalley.ai/e/meta-ai-developer-hackathon)
- **When:** Oct 26, 12:00 PM – Nov 4, 9:00 PM (EST)
- **Where:** Online
- **Team:** [Teslim Yusuf](https://cerebralvalley.ai/u/tessy_dev)
- **GitHub:** https://github.com/tessyjonburica/boardbreaker
- **Demo video:** https://youtu.be/AKCdQaeUJUw
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3413

A dead circuit board usually means tracing the power tree by hand: input, protection, regulator, rails, loads. It is repetitive, it takes experience, and the first measurements are the same on every board.

BoardBreaker does the tracing. Take a photo of a PCB: SAM 3.1 segments the components and the silkscreen becomes a component map. Give it a symptom and it plans the next measurement, states what it expects to rule out, and updates on the reading - under a hard six-probe budget. It returns ranked suspects with evidence for each.

A DC solver then re-simulates every known fault mode at the exact nodes the agent probed and checks which hypothesis actually fits. The model decides where to look; the physics decides what fits.

On an 18-fault benchmark at a six-probe budget: the agent alone reaches 16/18 top-1 and 17/18 top-3; the same probes re-checked by the DC solver reach 18/18. A deterministic full 15-probe sweep gets 17/18. So the agent reaches a better answer with less than half the measurements.

The BB-100 is a synthetic sensor node with a nodal-analysis solver behind it, so every reading is generated from a board with a planted fault and the ground truth is exact. The product loop is identical with real probes - the bench boundary is two functions.

## More from Meta Global AI Developer Hackathon

- [Evidient](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3410)
- [Mindstrip](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3411)
- [BatchSort](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3412)
- [Building Twin Lab](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3414)
- [ReGenLab](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3415)
- [relib](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3416)

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