AI ORG CHART STARTER KIT (90-DAY LEADERSHIP FRAMEWORK)

Purpose: Help a founder/CTO/VP Eng roll out AI-assisted and agentic workflows with measurable productivity gains while maintaining security, quality, and clear accountability.

A) WEEK 1–2: DEFINE SCOPE + BASELINES
1) Pick two “high-volume, low-ambiguity” workflows to start:
   - Example A: PR drafting + PR review summaries
   - Example B: Incident communications + postmortem first draft
2) Capture baselines (last 30 days):
   - Median PR cycle time (open → merge)
   - Review latency (open → first review)
   - Change failure rate (% deploys causing incident/rollback)
   - MTTR (mean time to recovery)
3) Write one success statement with guardrails:
   - “Reduce median PR cycle time by 20% in 90 days while keeping change failure rate within ±1%.”

B) WEEK 3–4: STANDARDIZE THE AI STACK
4) Choose defaults (company-wide) for:
   - Chat assistant (enterprise plan preferred)
   - Coding assistant (IDE + repo integration)
   - Agent framework (if building agents) + logging destination
5) Identity and access:
   - SSO required; no personal accounts for work data
   - Define access tiers: Public, Internal, Confidential, Regulated
6) Data rules (one page):
   - What can be pasted into AI tools
   - Redaction guidance (tokens, keys, customer PII)

C) WEEK 5–8: BUILD REUSABLE PROMPTS + EVALUATIONS
7) Create “golden prompts” for the two pilot workflows:
   - PR description template with checklists
   - Test plan template
   - Incident update template (status, scope, ETA, mitigations)
8) Establish an evaluation set (“golden set”):
   - 25–100 real examples (sanitized) representing your common cases
   - Include edge cases and known failure modes
9) Define pass/fail metrics:
   - Accuracy (human-rated), citation coverage (links to sources), policy compliance
10) Set a regression process:
   - Any model/tool change runs evals before rollout

D) WEEK 9–12: DEPLOY GUARDED AGENTS + SCALE
11) Add 1–2 limited-scope agents (optional):
   - Docs updater that opens PRs only
   - Dependency upgrade bot that proposes changes + runs tests
12) Guardrails (mandatory):
   - Human approval for production changes
   - Tool allowlist/denylist (e.g., deny key rotation, apply-terraform)
   - Rate limits + blast-radius constraints
13) Logging and audit:
   - Store prompts, context references, and tool calls for approved agents
   - Set retention (30–180 days) aligned with legal/security

E) ORG DESIGN: ROLES + ACCOUNTABILITY
14) Assign owners:
   - AI Platform Owner (stack, cost controls, access)
   - Eval Lead (quality metrics, regression gates)
   - Security/Legal partner (data and vendor controls)
15) Update RACI for AI-involved workflows:
   - Human accountable for outcome
   - AI role explicitly labeled: Drafter / Checker / Executor

F) OPERATING CADENCE
16) Replace status meetings with:
   - Weekly AI impact report (metrics + examples)
   - Monthly governance review (incidents, exceptions, model changes)
17) Track these metrics:
   - Cycle time, review latency, escaped defects
   - Automation ratio (% tasks AI-assisted)
   - Error amplification incidents (count + severity)

G) LAUNCH CHECKLIST (READY TO SCALE)
18) You are ready to expand when:
   - Pilot metrics improved for 4 consecutive weeks
   - No material increase in change failure rate or security exceptions
   - Evals run automatically before tool/model updates

If you do only one thing: make AI usage measurable and auditable. Speed without accountability turns into risk.