5 articles
ACE and IBM's ALTK-Evolve both turn agent trajectories into reusable lessons. The difference is delivery: one injects the whole playbook every step, the other calibrates. On AppWorld, calibration wins with the same accuracy at a fraction of the tokens.
A new 600-session benchmark shows coding assistants that read a user's resolved session history resolve ambiguous requests with far fewer clarifying questions - Claude Opus 4.8's first-turn success jumps from 24.3% to 60.3% when history is available.
AREX and the July deep-search papers point to the next useful research-agent primitive: a ledger of claims, constraints, failed paths, and unresolved questions that survives beyond the chat transcript.
SearchOS turns web research from a growing chat transcript into shared state: frontier tasks, evidence graphs, coverage maps, and failure memory. That is the pattern serious deep-research agents need.
AgentMemory gives Claude Code, Codex, Cursor, and other agents persistent local memory. The real adoption question is not recall accuracy. It is whether your team can inspect, prune, and govern what gets remembered.
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