# Requirements Charter — AI-First Design Plan --- ## Core Principle > **AI drives the process. Humans only veto, choose, or initiate.** --- ## Human Role (Redefined) | Action | When | Cost | |---|---|---| | **Veto** | AI judgment is wrong | < 10s | | **Choose** | AI cannot auto-converge | Pick from AI options, < 30s | | **Initiate** | New direction or project | One trigger, AI takes over | Everything else — writing, aligning, versioning, risk detection, scheduling, notifying — is fully owned by AI. --- ## 5 Hard Rules (AI-Enforced) - [ ] **Upstream binding** — Charter is auto-generated from signal source; blank creation is blocked by AI - [ ] **Alignment gate** — Downstream unlocks automatically after AI confirms alignment; no manual gate-keeping - [ ] **Non-deletable structure** — 6 core modules enforced by AI at the logic layer, not just UI - [ ] **Version lock** — AI auto-classifies minor fix vs. major version change; humans never manage versions manually - [ ] **Full traceability** — All content, alignment records, versions, and tasks are bidirectionally linked and maintained by AI --- ## Page Layout ### Left Panel (280px, fixed) - [ ] **SSTC Chain Status Card (120px)** — 6-node chain; AI highlights current node and auto-locks downstream until aligned; clicking a locked node shows AI-generated reason - [ ] **Version List** — AI-managed; users see only the `Active` version by default; history visible on demand; AI auto-archives stale versions - [ ] **Create Charter Button** — "From Signal Source" (primary); AI intercepts and blocks if no signal source exists; offers to auto-generate one from pasted content (chat logs, emails, meeting notes) ### Right Panel (75%) #### Top Bar (100px, fixed) - [ ] Charter name, version tag, status badge, bound project, last modified, owner — all AI-maintained - [ ] Context actions by status: | Status | Available Actions | |---|---| | Draft | `Save Draft` / `Initiate Alignment` | | Aligning | `Veto Alignment` / `View AI Progress` | | Aligned | `New Version` / `Export` / `View History` | | Archived | `View History` / `Copy as New` | --- ## 6 Core Modules (Non-Deletable, AI-Driven) Every module follows the same contract: - [ ] Required metadata: `status`, `confidence_score`, `last_validated_at`, `evidence_refs[]`, `escalation_reason` - [ ] AI must maintain traceability from each generated field back to signal source evidence - [ ] If `confidence_score < 0.75` or source evidence conflicts, AI escalates for one human veto/accept decision ### Module 1 — Trigger & Goal *Auto-generated from signal source. Human is veto-only.* - [ ] **Inputs (required):** bound signal source IDs, target user segment, business context - [ ] **Outputs (required):** - One-sentence problem statement (max 120 chars, no vague terms) - One-sentence goal with baseline, target, and due date - 3–5 measurable KPIs (business + AI quality), each with `formula`, `baseline`, `target`, `owner`, `data_source`, `measurement_cadence` - [ ] **AI validations:** - KPI-to-source evidence mapping is complete - KPI definitions are testable (no unverifiable wording) - Goal and KPI are semantically consistent - [ ] **Escalation trigger:** inconsistent evidence, non-testable KPI, or unresolved goal ambiguity ### Module 2 — Scope & Alignment Checklist *AI auto-fills; humans review only low-confidence exceptions.* - [ ] **Outputs (required):** - In-scope: 3–7 features, each with acceptance condition - Out-of-scope: 3–7 explicit exclusions, each with boundary example - Fixed alignment Q&A (5 questions), each with answer + confidence + evidence ref: - Who is the core user and what pain is prioritized? - What is the launch date and immovable constraint? - What is explicitly out of scope? - What tech/model/third-party dependencies are required? - What are top risks and mitigations? - [ ] **AI validations:** - Detect overlap/conflict between in-scope and out-of-scope - Detect missing constraints (security, compliance, data/privacy, performance) - Block alignment if unanswered critical checklist items exist - [ ] **Escalation trigger:** any critical question with low confidence or conflicting source evidence ### Module 3 — AI Model & Tech Dependencies *AI generates one canonical dependency model and serves role-specific views from it.* - [ ] **Outputs (required):** - Primary model + fallback model with selection rationale - Capability table: context window, rate limits, latency range, token cost, known boundaries - Dependency map: frameworks, external APIs, data stores, observability requirements - Two synchronized views from one source of truth: - Business view (non-technical language) - Engineering view (technical specs and limits) - [ ] **AI validations:** - Budget simulation for P50/P90 workload - Boundary stress check against expected input size and concurrency - Semantic consistency check between business and engineering views - [ ] **Escalation trigger:** no feasible model stack under budget/SLA constraints ### Module 4 — Timeline & Resource Planning *AI schedules and allocates automatically; humans only veto exceptions.* - [ ] **Outputs (required):** - Milestone plan with `start`, `end`, `dependency`, `critical_path` - Role-level effort estimates with confidence intervals - Owner assignment from capability graph (not manual guessing) - Buffer policy for delivery risk and handoff delays - [ ] **AI validations:** - Capacity check: default cap at 85% utilization per member - Calendar check: timezone, holiday, leave windows - Deadline risk simulation and recommended reallocation when risk exceeds threshold - [ ] **Escalation trigger:** unresolved overload, missing capability match, or launch risk above allowed threshold ### Module 5 — Risks & Mitigations *AI owns risk detection, monitoring, and first-response execution.* - [ ] **Outputs (required):** - Risk register with `category`, `probability`, `impact`, `trigger_signal`, `owner`, `mitigation`, `fallback_plan` - Minimum coverage categories: tech, model, schedule, market, compliance/security - Runtime trigger rules bound to alert center - [ ] **AI validations:** - High-risk items must include executable fallback steps and ETA - Trigger signals must map to observable metrics/events - Risk owner must exist in org graph and match capability domain - [ ] **Execution rule:** when trigger fires, AI executes fallback, records action trail, and notifies affected owners - [ ] **Escalation trigger:** fallback unavailable, owner missing, or mitigation fails repeatedly ### Module 6 — Attachments & Notes *Optional in UI, mandatory in indexing and governance.* - [ ] **Outputs (required):** - Structured attachment metadata: `type`, `source`, `version`, `owner`, `confidentiality_level`, `linked_module` - AI-generated summary and decision extraction for each attachment - Search index + semantic tags for cross-project retrieval - [ ] **AI validations:** - Duplicate/conflict detection across attachment versions - Broken link and inaccessible file detection - Sensitive content scan with masking/redaction suggestion - [ ] **Governance rule:** attachments are references only; source-of-truth fields must live in Modules 1–5 ### Module Definition of Done (DoD) - [ ] 100% required fields completed with evidence refs - [ ] All module validations pass with no critical blockers - [ ] Any escalated items resolved by single human veto/accept - [ ] Module state is auditable and traceable in version history --- ## AI Alignment Engine (Replaces Manual Alignment Flow) ### New Alignment Logic: No Opposition = Aligned - [ ] Charter locked and distributed to all members on alignment initiation - [ ] Members have **24 hours** to raise objections; silence = consent - [ ] AI monitors behavior signals (opened charter, acted on related tasks, no objection raised) to infer stance - [ ] AI auto-records: `Active Confirmed` / `Implicit Consent` / `Objected` — all auditable - [ ] If objection raised: AI analyzes disagreement, generates resolution proposal, pushes to relevant parties for a single accept/veto - [ ] 100% resolved (by active confirmation or implicit consent) → AI auto-marks as `Aligned`, unlocks downstream ### Alignment Status Views **Aligning** - [ ] AI progress card: `X/N resolved` — breakdown of active confirms, implicit consents, pending objections - [ ] Unresolved objections show AI-generated resolution proposals inline - [ ] No manual "remind" buttons — AI handles follow-up autonomously **Aligned** - [ ] Green banner: "Charter aligned by AI. Downstream task breakdown unlocked." - [ ] Permanent alignment record: timestamps, consent type, immutable - [ ] `New Version` + `AI Breakdown Tasks` buttons --- ## AI Version Management - [ ] AI classifies every change: **minor fix** (auto-merged, no new version) vs. **major change** (new version + re-alignment) - [ ] Classification based on semantic diff + learned team behavior patterns - [ ] If two parallel versions exceed 80% similarity, AI proposes merge - [ ] Version tree auto-maintained by AI; stale branches auto-archived - [ ] Humans always see only the current active version; history on demand --- ## AI Signal Source Engine (Cold Start Solution) - [ ] AI connects to Feishu, email, meeting notes — continuously monitors for requirement signals in the background - [ ] When a signal is detected, AI auto-generates a structured signal source draft and notifies PM: "Potential requirement detected. Create charter?" - [ ] PM one-tap confirms → signal source + charter draft generated simultaneously - [ ] If no integrations available: paste any raw content (chat screenshot, email, voice transcript) → AI structures it into a signal source + charter draft - [ ] Cold-start rule: signal source binding is a **warning**, not a hard block, during first 30 days; AI tracks and prompts completion --- ## AI Capability Graph (Cold Start Solution) - [ ] On first use: member confirms role + seniority (10 seconds) - [ ] AI uses industry benchmark data as baseline - [ ] After each task: AI auto-captures actual vs. estimated hours, updates capability model silently - [ ] No manual input ever required again; model improves with every project --- ## AI Toolbar (Fixed, Below Modules) | Button | Trigger | AI Action | |---|---|---| | Re-validate Charter | Before alignment | Full charter scan: vague expressions, missing fields, logical inconsistencies — auto-fixed where possible | | Compare Versions | Has history | AI-generated semantic diff with change summary | | Export Charter | Any status | PDF / Markdown with full alignment record | --- ## SSTC Chain Integration - [ ] **Upstream**: signal source changes auto-trigger charter refresh; AI notifies owner of delta - [ ] **Downstream lock**: task breakdown stays locked until AI confirms `Aligned` status - [ ] **Task generation**: on alignment, AI auto-generates full task tree from charter — assigns owners, estimates hours, zero manual input - [ ] **Execution sync**: major task delays auto-trigger charter change assessment by AI; escalates to human only if major revision needed - [ ] **Retrospective**: AI auto-compares charter goals vs. actuals → generates retrospective report → feeds into team knowledge graph --- ## Mobile - [ ] View-only (no editing on mobile) - [ ] Collapsed module list, tap to expand - [ ] One-tap veto or confirm - [ ] Voice input for objections (AI transcribes + structures) - [ ] Swipe left = version history, swipe right = alignment record - [ ] Push notifications for alignment requests and AI-escalated decisions --- ## Dev Rollout — 3 Phases ### Phase 1 — Core Loop (Week 1) - [ ] Left panel: AI-managed version list + chain status card - [ ] 6 structured module editors with AI auto-fill - [ ] AI alignment engine: 24h implicit consent, objection handling - [ ] Downstream auto-unlock on alignment - [ ] AI version classification (minor fix vs. major change) ### Phase 2 — AI-Native (Week 2) - [ ] Real-time vague expression detection + auto-fix - [ ] AI self-validation (cross-check generated content) - [ ] Role-aware dual-language view for Module 3 - [ ] Model binding + match evaluation + capability boundary validation - [ ] Signal source auto-detection (Feishu / email integration) - [ ] Task auto-generation from charter on alignment ### Phase 3 — Polish & Advanced (Week 3+) - [ ] Capability graph auto-learning from task execution - [ ] Version merge suggestions + version tree visualization - [ ] Mobile adaptation - [ ] Feishu card actions (veto / confirm directly in Feishu) - [ ] Retrospective auto-report generation - [ ] Charter template library --- ## Summary: What Changed vs. Original Plan | Original | AI-First | |---|---| | 100% manual confirmation to unlock downstream | 24h no-objection = aligned, AI records | | AI assists human writing | AI writes + self-validates; human vetoes | | Human creates signal sources | AI detects signals proactively; human one-tap confirms | | Human manages versions | AI fully manages; human sees active version only | | All members see one charter | AI serves role-appropriate language view per member | | Human fills capability graph | AI learns from task execution automatically | | AI is a feature | AI is the process engine; humans are veto holders |