npub1lw…gy86j on Nostr: Here are the 10 steps: 1 → LLMs create. Agents act. Jev decides the next move. 2 ...
Here are the 10 steps:
1 → LLMs create. Agents act. Jev decides the next move.
2 → Turn agent forks into three primitives: Choice, Score and probability.
3 → Build with OpenAI, Anthropic or xAI first, then swap Jev in without rebuilding the graph.
4 → Start with shared state, parallel decisions, risk thresholds and an execution queue.
5 → Batch decisions instead of making them sequentially. In one test, 13 questions were 10x faster and 12.2x cheaper.
6 → Put Jev at bounded forks: agent, model, tool, browser action or human escalation.
7 → Benchmark the whole loop, not just individual model calls.
8 → Rank wide, read narrow: shortlist first, then spend compute on what matters.
9 → Reuse the same system: State → Questions → Action → Verify.
10 → Keep Jev out of math, writing and irreversible execution. Code computes, LLMs create, Jev decides.
Published at
2026-09-20 23:37:57 UTCEvent JSON
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"content": "https://blossom.primal.net/67bbb710d05a23626e8fba6932a9c3a12735fb8339058a42506128e26648851c.png\n\nHere are the 10 steps:\n\n1 → LLMs create. Agents act. Jev decides the next move.\n\n2 → Turn agent forks into three primitives: Choice, Score and probability.\n\n3 → Build with OpenAI, Anthropic or xAI first, then swap Jev in without rebuilding the graph.\n\n4 → Start with shared state, parallel decisions, risk thresholds and an execution queue.\n\n5 → Batch decisions instead of making them sequentially. In one test, 13 questions were 10x faster and 12.2x cheaper.\n\n6 → Put Jev at bounded forks: agent, model, tool, browser action or human escalation.\n\n7 → Benchmark the whole loop, not just individual model calls.\n\n8 → Rank wide, read narrow: shortlist first, then spend compute on what matters.\n\n9 → Reuse the same system: State → Questions → Action → Verify.\n\n10 → Keep Jev out of math, writing and irreversible execution. Code computes, LLMs create, Jev decides.",
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