Loading...
Loading...
Tools that make your AI agent improve itself. Every session gets smarter. Every failure becomes a lesson. This is the compound effect.
Ranked directory
Frameworks that let your agent observe its own performance and get better autonomously.
Hierarchical Agent Loop Optimization. Trace, analyze, fix, redeploy. Recursively self-improving.
Adaptive learning with trajectory tracking, verdict judgment, memory distillation.
Microsoft: turn one-shot agents into learning agents with RL and prompt optimization.
Train any agent simply by talking. Reinforcement learning from conversation.
Self-evolving skill engine. 46% fewer tokens via learned patterns.
The sensor that closes the feedback loop. Scans code quality, scores it, agent improves, rescans — recursive self-improvement. Quality goes from 6/10 to 9.5/10 automatically.
Can a stock AI agent bootstrap an autonomous bug bounty system from scratch? Hermes Alpha hands a Nous Research agent a single identity document (soul.md) and challenges it to build, deploy, and continuously improve a second AI agent.
Ranked directory
Persistent memory systems that make every session build on the last.
Procedural memory for AI agents. Three-layer cognitive architecture, confidence decay, anti-pattern learning.
Graph-first cognitive daemon v8.2. Persistent knowledge graph as source of truth.
Shared memory for teams. Every agent session compounds into a Karpathy-style wiki. 49% speedup.
Auto-captures everything Claude does, compresses with AI, injects relevant context back.
Karpathy-style persistent knowledge base. Self-healing, compounds over time.
How it works
Track what worked, what failed, what was slow.
Pull the pattern into knowledge-base.md.
Update the relevant SKILL.md or agent config.
Rate 1-10. Did quality improve?
This loop runs after every task in AI Brain Pro. Your AI gets smarter with every session.
AI Brain Pro includes the full compound loop, 1,700+ skills, and all memory systems pre-configured.