v0.11.0

0.11.0 - 2026-10-31

Delivers roadmap milestone v0.9 (Optimization Intelligence).

Added — optimization recommendations (agenticlens.optimization)

• Trace-level rules over many runs, each citing run and span evidence and the
  thresholds used: prompt caching (repeated prompt.prefix_sha256 prefixes
  without a provider cache hit) and compression (input-heavy model calls),
  retrieval top-k pruning (never below the deepest used chunk) and reranking
  (perfect-reranker upper bound), memory summarization and retention windows,
  tool-result caching (side-effecting and non-idempotent tools are skipped),
  non-retryable error types (no observed retry recovered), redundant steps
  (same input and output), and handoffs whose receiver did no work.
• Quality-cost trade-offs: analyze_tradeoffs reports per-variant success with
  Wilson intervals, cost per success, Pareto status, and deltas and p-values
  against a baseline; QualityCostTradeoffRule proposes cheaper variants within
  an allowed success drop and reports any drop as a separate risk.
• Every Opportunity keeps a ProjectedBenefit (tokens, cost, latency per
  run and per month, with its basis; cost unavailable when any span lacks it),
  graded confidence with reasons (capped for assumed reductions and small
  samples), and separate QualityRisks. Stable IDs hash the kind and subject.
• RecommendationLedger: append-only JSONL decisions bound to the report's
  SHA-256 with enforced accepted/rejected/adopted/reverted transitions.
• evaluate_outcome: projected and observed per-run tokens, cost, latency, and
  success rate side by side after adoption, a re-check of the originating
  rule, a realized ratio, and realized, partially_realized,
  not_realized, quality_regressed, or insufficient_evidence.
• Reproducible OptimizationReport (no wall-clock values), YAML/JSON configs
  that reject unknown keys, Markdown renderers, and schemas in
  schemas/optimization/.

Added — CLI

• agenticlens optimize analyze TRACES... [--config] [--baseline-variant] [--ledger] [--save] [--markdown]
• agenticlens optimize decide REPORT ID --status --by --ledger [--reason] [--change] and agenticlens optimize status REPORT --ledger
• agenticlens optimize outcome REPORT ID --before --after [--ledger] [--min-runs] [--save] [--markdown] [--fail-on-regression] (exit 9)

Added — examples, CI, docs

• examples/optimization_demo.py with recorded before/after support-agent
  traces and committed artifacts; CI's optimization job records an adoption
  and gates on post-adoption regression.
• Optimization guide, CLI/API reference, roadmap acceptance, and audit
  evidence.

Compatibility

• Additive. Existing workflow recommenders, routing, and ModelFit are
  unchanged. Evals, Chaos, Sidecar (<1), and Tower (<1) dependency ranges
  remain sufficient. MCP 0.4.3 pins Lens 0.11.0 and exposes read-only
  lens.optimization_analyze.
• Optimization artifacts are Lens-local, not part of the normative AIOS
  contract. Recommendations are advisory and never change prompts, models,
  tools, or routes.