Intelligence & learning

Status: complete (published 2026-08-19). Scope finalized at Batch C kickoff with maintainer POV; see findings.md and sources.md.

Scope inventory (v0)

• Estate: BI and dashboards, notebooks and data science platforms, feature stores, model registries, MLOps
• Agent-era: conversational analytics over metrics layers, LLMOps/AgentOps, eval infrastructure (golden datasets, LLM-as-judge, human review queues, regression gates), trace-to-dataset curation
• Improvement machinery: fine-tuning and distillation pipelines, A/B and canary rollout for agent changes, experiment tracking, classical ML (classifiers, topic models, forecasting) as the deterministic muscle next to LLMs
• Risk: model risk management alignment for regulated environments

Challenged-default candidates

LLM-first analytics vs metrics-layer grounding; buying eval platforms vs building on open tooling. Each track proposes its final list at kickoff.

Files

findings.md and sources.md carry this track's research. The scoping brief and the vendor map were archived on 2026-08-23 (see archive/, decision D038).