AI 扩展计划 / Playbooks
AML Capstone 入口
1. Read AML_ABPA_10_DAY_STARTER.md from top to bottom.
56 行abpa/capstone-aml/README.md
AML Copilot ABPA Capstone
This folder is the first filled ABPA case package. It uses existing AML Copilot work as evidence and does not replace or delete any earlier learning material.
Current Artifact
| Artifact | Path | Status |
|---|---|---|
| 10-day starter pack | AML_ABPA_10_DAY_STARTER.md | v0.1 complete |
| 30-day deepening plan | AML_30_DAY_DEEPENING_PLAN.md | v0.1 complete |
Evidence Reused
| Evidence | Why it matters |
|---|---|
docs/AML_COPILOT_PRD.md | product intent, target workflow, user value |
src/aml/types.ts | domain objects and case structure |
src/aml/evalBaseline.ts | baseline scoring and evaluation assumptions |
src/aml/failureTaxonomy.ts | failure modes and quality risks |
src/aml/groundTruthEval.ts | ground-truth evaluation direction |
src/aml/__tests__/aml.test.ts | regression behavior |
src/aml/__tests__/p1evals.test.ts | P1 evaluation coverage |
How To Use This Capstone
- Read
AML_ABPA_10_DAY_STARTER.mdfrom top to bottom. - Pick one unfinished section and turn it into a standalone portfolio artifact.
- Use the templates in
../templates/when a section needs more depth. - Keep evidence links close to each claim.
- Add new versions beside old ones when learning evolves.
For a structured next step, use AML_30_DAY_DEEPENING_PLAN.md to deepen the starter into data readiness, workflow, eval, architecture, operating model, adoption, business case, and interview rehearsal assets.
Recommended Next 30 Days
| Week | Focus | Output |
|---|---|---|
| W1 | Data readiness | AML Data Readiness Pack v0.1 |
| W2 | Architecture choices | AML Architecture ADR Set v0.1 |
| W3 | Operating model | AML Operating Model + RACI v0.1 |
| W4 | Adoption and value | AML Adoption Dashboard + Business Case v0.1 |
Portfolio Storyline
| Interview angle | Story to tell | Evidence to show |
|---|---|---|
| AI BA | translated ambiguous AML pain into eval-ready requirements | opportunity canvas, stakeholder map, requirements-to-eval |
| AI PM | balanced adoption, quality, risk, and unit economics | adoption dashboard, business case |
| AI Solutions Architect | selected bounded architecture with controls and observability | ADR set, control pack |
| Financial domain expert | understood AML workflow, case review, audit, and risk controls | PRD, failure taxonomy, eval tests |
Preservation Rule
Do not delete older AML, Web3, architecture, LLM, DSDB, AIPA, or daily-note assets when improving this capstone. Add indexes, cross-links, versions, and review notes instead.