X @@akshay_pachaar · May 17, 2026
Full analysis by SuperBM
Akshay 🚀: self-evolving skills in Hermes agent.
6/10 Solid
Describes Hermes agent's self-evolving skills that remember and reuse problem-solving procedures.
Key Insights
- Distinguishing memory (facts) from skills (procedures) is a valuable architectural insight.
- The self-improvement loop described is a plausible but unverified approach to agent learning.
- Skill bloat and curation are recognized challenges in persistent agent systems.
Caveats & Flags
- No verifiable source or link to Hermes agent codebase or benchmarks.
- Claim of 'never auto-deleting anything' is unverifiable and technically dubious.
- Author presents speculative system description as factual without evidence.
- caveats
Valid Points
- Separation of factual memory from procedural skills is a known and useful design pattern.
- Automatic skill creation after problem-solving can improve efficiency over time.
- A background curator merging overlapping skills addresses skill bloat plausibly.
Counterpoints
- No evidence that this specific agent actually implements the claimed loop without error.
- Automated skill creation may persist bad or non-generalizable solutions without human review.
- The curator's claimed capability to merge overlapping skills is non-trivial and unproven.