Decision Log

And the patterns that stand alongside it, or against it —

• alternative-toBlack-Box Opaqueness✕— Anti-pattern: ship an agent without traces, decision logs, or provenance, then debug from user reports.
• complementsAttention-Manipulation Explainability·— Surface which input tokens caused a given output by perturbing attention across all transformer layers and measuring the resulting change in output probability, producing a per-token relevance map alongside the model's response.
• complementsSelf-Archaeology·— Synthesize the agent's past thought history into time-layered trajectory notes so it can articulate how its understanding evolved without recomputing the narrative each time.
• complementsMemo-As-Source Confusion★— Anti-pattern: the agent cites its own past memos as ground truth instead of re-verifying them against the artifacts they describe, accumulating false confidence in stale summaries.
• complementsInterrupt-Resumable Thought·— Preserve multi-step reasoning across interrupts by supporting paused-and-resumed thought frames so a new message handles cleanly without clobbering in-flight work.
• complementsIntra-Agent Memo Scheduling★— Let an agent drop a note for its own future self at a specified time so present decisions can hand off context to a later run without external infrastructure.
• complementsEcho Recognition·— Recognize human message repetition as emphasis or a re-ask rather than as an independent input, so the agent does not produce a near-duplicate reply when the human repeats themselves.
• alternative-toErrors Swept Under the Rug✕— Anti-pattern: scrub failed actions, stack traces, and error observations from the agent's own context so the trace looks clean, leaving the model with no evidence of what did not work.
• complementsTyped Refusal Codes★— Define a single source of truth for machine-readable refusal codes across all guard surfaces, so refusals can be triaged mechanically rather than by string-grepping ad-hoc human-readable messages.
• complementsCommitment Tracking·— Extract stated intents from each agent turn into a structured ledger with open / followed-through / expired status, making the gap between promise and follow-through visible and auditable.
• alternative-toAgentic Skill Atrophy✕— Anti-pattern: let agents take over routine architectural and debugging decisions in code until developers no longer form the implicit knowledge that lets them review the agent's output or recover when it fails.
• alternative-toAgentic Debt✕— Anti-pattern: deploy agents on top of an unconsolidated data foundation, weak governance, or missing MLOps infrastructure, so every subsequent capability — observability, retraining, compliance retrofit — pays compounding interest on the skipped foundational work.
• complementsRigor Relocation★— Relocate verification rigor from the model loop to surrounding scaffolding (evals, judges, decision logs, policy gates) so failures are caught by the wrapper rather than the agent.
• complementsSynchronous Execution-Plan Confirmation★— Agent synchronously emits its full execution plan for user confirmation before any side-effect step, and provides asynchronous operation recordings for post-hoc review.
• complementsPolicy-Gated Agent Action (KRITIS)★— Each agent action passes through a policy gate (NIS2, EU the agent Act, BSI rules) and is tagged with Run ID + Model Digest + Policy Hash for WORM-audit reconstruction.
• complementsDecision Context Maps★— Before any consequential decision, require the agent to gather a declared set of contextual inputs (resource availability, schedules, downstream dependencies) into a 'context map' the decision must cite.
• complementsAgent Middleware Chain★— Wrap every model call, tool call, and memory access in a composable pre/execute/post interceptor pipeline so cross-cutting concerns attach without touching agent or orchestrator code.
• complementsMulti-Principal Welfare Aggregation·— When an agent serves multiple humans with conflicting preferences, declare the aggregation rule explicitly rather than letting it be implicit in the prompt or fine-tune.