I applied Lyapunov stability theory to detect when LLM agents spiral
Details
- External ID
- 48488870
- Source
- HN
- Company
- —
- Product
- I applied Lyapunov stability theory to detect when LLM agents spiral
- Website domain
- github.com
- Launched
- June 11, 2026
- Cohort
- —
- Upvotes
- 11
- Upvotes percentile
- 0.6284153005464481
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Enrichment
- Theme
- autonomous agent research and evaluation
- Vertical
- Horizontal
- Function
- Observability & eval
- Audience
- Developer
- AI stance
- AI-native
- Project type
- Hobby / open-source project
- Normalized one-liner
- detect llm agent failure spirals
- Manually corrected
- False
Could you build this?
Partial While the agent runner scaffolding is straightforward, modeling agent trajectories as dynamical systems and calculating Lyapunov exponents/stability functions requires specialized mathematical physics or control theory knowledge.
What it would actually take: Building this requires mapping LLM state transitions or latent embeddings into a continuous or discrete dynamical state-space representation, constructing a candidate Lyapunov function V(x) to evaluate energy growth/divergence, and instrumenting the agent loop with statistical trajectory divergence tests.
Discussion
2 comments analyzed.
Concerns raised: README appears LLM-generated, lacks credibility, Unclear assumptions, methodology, and limitations
Competitors
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Attention rank: #197 of 731 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 223 days after the earliest competitor.
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