Your Agent's Memory Is a Playbook From the Last War
Trajectory retrieval over successful past runs is not a neutral accelerator; it is an overfitting mechanism that fails hardest exactly when the environment shifts, so memory pipelines need a staleness/shift detector and a re-derivation step before any prior plan is treated as executable.
AngleAttack the default top-k successful-trajectory design in agent memory, using the 'do not fight the last war' failure mode as the framing and proposing stored successes be demoted from plans to hypotheses with explicit validity conditions.
Source video ↗Tactical Hell Is an Architecture Bug, Not a Reasoning Bug
Agents that thrash on local signals do not need smarter per-step reasoning, they need a separate abstraction tier that consumes a compressed world state and rewrites goals; the design problem therefore moves to the tier boundary — what crosses upward and how often objectives are rewritten.
AngleReframe the reactive-vs-deliberative debate as an interface specification problem, and connect the Athena/Ares coexistence to an explicit arbitration router with a stated criterion for when deliberation is worth its latency.
Source video ↗Stop Scoring Your Agent on Tactical Metrics
Because a tactical defeat can be a strategic victory, self-improvement loops driven only by local success signals can invert true performance; evaluation must be a hierarchy with an independently measured governing objective, which means agents cannot be safely self-improved using their own local success signal.
AngleUse the Tet Offensive level-shift to argue that eval harnesses need explicit metric-to-objective mapping, and derive concrete consequences for routing, critique and self-critique loops.
Source video ↗The Sycophancy Bug Is an Objective-Corruption Bug
Optimization toward what the principal wants to hear and the strategist's emotion-driven modeling of a desired reality are the same mechanical failure: neither is a motivational defect, both substitute a preferred model for the actual one, and both require a feedback channel deliberately decoupled from the principal's desires.
AngleUnify sycophancy literature with the strategy framing of wishful thinking, and propose an architectural check that the world model is not the desired-world model.
Source video ↗Last-War Bench
newAgents that inject retrieved successful trajectories under a distribution shift will score lower than agents that re-derive per-episode, and adding an online shift detector before memory injection will recover most of the gap.
Proof of conceptBuild paired environments where episode statistics shift at a known point; run three policies with the same base model — top-k trajectory retrieval, rule extraction, and per-episode re-derivation — with and without a shift-gated injection step. Log every injected exemplar and whether it was subsequently contradicted.
MeasurementTask success rate before vs. after the shift point, regret relative to an oracle re-derivation policy, rate of confidently applied stale playbooks, and change in success when the shift gate is enabled.
Source video ↗Tier-Boundary Router
movement-labA two-tier agent with an explicit fast reactive controller plus a slow elevation layer that rewrites objectives will outperform a single-loop agent of equal per-step reasoning budget on long-horizon tasks, and deliberation spend will pay off only above a measurable stakes/latency threshold.
Proof of conceptImplement both agents on an identical task suite. Instrument the router and sweep the switching criterion across task stakes and time budgets, counting the number of objective rewrites and the total cost paid at the tier boundary.
MeasurementLong-horizon task success, variance of action distribution (thrash proxy), number of goal rewrites per episode, and net payoff of deliberation as a function of stakes and time budget.
Source video ↗Inverting-Metric Harness
beyond-evalsOptimizing a well-chosen operative metric alone will invert outcomes relative to an independently scored governing objective on tasks engineered to contain a Tet-Offensive-style level shift, and this inversion will be detectable only by the higher-level scorer.
Proof of conceptDefine per-task metric hierarchies with a separately measured governing objective; train or route one arm on the operative metric and one on the hierarchical objective; check whether the operative-metric arm improves locally while regressing on the governing objective.
MeasurementOperative metric vs. governing objective correlation across iterations, fraction of iterations where the two move in opposite directions, and detection latency of the inversion by each scorer.
Source video ↗Counterparty Model Injection
gatehouseAgents maintaining a persistent, refreshed counterparty/context model (norms, incentives, social environment) will outperform agents treating the environment as a generic interface in multi-agent scenarios, and stale counterparty models will degrade performance in the same way stale playbooks do.
Proof of conceptPrototype a persistent context artifact that conditions plan selection in agent-vs-agent scenarios; run an ablation with the artifact frozen at t0 versus continuously refreshed, against a no-model baseline.
MeasurementNegotiation/coordination outcome quality, number of plan revisions attributable to counterparty evidence, and performance decay of the frozen model as opponent behavior drifts.
Source video ↗