AcontextSkill memory layer for agents: auto-captures learnings from runs into plain Markdown skill files you can read, edit, git and share across frameworks — memory without an opaque store.
Why switchSame loop — learn from runs, distill into reusable instruction text, inject next time. ACE keeps a Skillbook inside its own LiteLLM-based engine with benchmark receipts; Acontext externalizes everything as standard skill files any framework can mount.
Full comparison → hindsightAgent memory that learns, not just recalls: retain/recall/reflect API over Postgres, SOTA on LongMemEval. Self-host via Docker with UI; Python/TS clients, any LLM provider.
Why switchBoth sell 'agents that learn, not just remember' — opposite deployments: Hindsight is a self-hosted memory service (Docker + Postgres, retain/recall/reflect over HTTP); ACE is an embedded Python loop distilling strategies in-process. Service vs library.
Full comparison → claude-reflectClaude Code plugin that learns from your corrections — hooks capture them in-session, /reflect syncs approved learnings to CLAUDE.md/AGENTS.md, /reflect-skills mines history into reusable commands.
Why switchSame learn-from-corrections loop at different scopes: claude-reflect is a Claude Code plugin syncing learnings into CLAUDE.md; ACE is a framework-level engine for any agent you build, with strategies as first-class objects.
Full comparison → hivemindActiveloop's shared brain for agent TEAMS: traces from Claude Code, Codex, Cursor & co become reusable skills every teammate's agent can execute — cloud-backed, 25% cheaper on LoCoMo.
Why switchSame learn-from-experience loop, different scope: ACE is an embedded Python engine distilling strategies for the agent you're building; Hivemind is a service layer distilling skills across every off-the-shelf agent your team runs.
Full comparison → JITJIT-Agent: a meta-agent that writes a task-specific harness on the fly — memory, planning, action and capability modules emitted as code — and revises it from traces at test time.
Why switchBoth learn from failures between runs. ACE distils strategies into a Skillbook injected into the next prompt; JIT-Agent rewrites the scaffold itself — memory, planning, action modules — from the traces.
Full comparison →