Four Medusa agents share one repo, discarding writes below a 0.82 score
A demo of four agents collaborating in one shared repo, where every write passes a CRC check and a score gate that discards anything below 0.82, writing 404.1K lines with 214/214 evals passing in a 22-second render.
404.1K LINES WRITTEN. 214/214 EVALS PASSED. CANARY AT 100%. And only 3 of 8 guards are lit. Four Medusa agents write into one shared repo, but every change has to pass a score before it reaches the board. "if score < 0.82: board.discard (block)" Here's how the system works: → 4 agents seek, grab, and carry code across one shared poard → 20 chips placed by the end → Every chip read gets a CRC check; corrupted reads are rejected → Writes travel over a 64-bit bus → Every code block gets scored; anything below 0.82 is discarded The board needs a human at just three critical moments: → Before a chip lands: Did the CRC match, or is an agent working from corrupted data? → When a block scores below 0.82: Is it useless noise or the one fix that mattered? → Before production: The deploy bar says 100%, but five guards are still dark. Who approved it? That's the part that matters. Four agents can share one board. That doesn't mean their output is safe to ship. In this 22-second render: → Lines written climb from 182.2K to 404.1K → Shipped count rises from 911 to 959 → The deploy log cycles through trace, A2A handshake, eval, canary, and guard The CRC check and 0.82 score sit on every write. Deployment is the final gate. The Jev engineering pattern, one layer deeper: 1. Medusa 01-04: Each agent runs its own seek, grab, and carry loop. 2. "read_chip()": Reads over a 64-bit bus and raises an "IOError" on CRC mismatch. 3. "weave()": Scores each streamed block, then injects or discards it. 4. Production gate: Tracks evals, guards, deployment percentage, cost, p95 latency, and error rate.
This post quotes another post: “CrawlHive uses Jev to filter signals and shipped 9 features in 3 days”