docs(01-foundation): create phase plan

.planning/ROADMAP.md

@@ -29,7 +29,7 @@ Decimal phases appear between their surrounding integers in numeric order.
   4. The LLM backend pool routes requests through LiteLLM to both Ollama (local) and Anthropic/OpenAI, with automatic fallback when a provider is unavailable
   5. A new AI employee can be configured with a custom name, role, and persona — and that persona is reflected in responses
   6. An operator can create tenants and design agents (name, role, persona, system prompt, tools, escalation rules) via the admin portal
-**Plans**: TBD
+**Plans**: 4 plans
 
 Plans:
 - [ ] 01-01: Monorepo scaffolding, Docker Compose dev environment, shared Pydantic models, DB schema with RLS
@@ -47,7 +47,7 @@ Plans:
   3. The agent can invoke a registered tool (e.g., knowledge base search) and incorporate the result into its response
   4. When a configured escalation rule triggers (e.g., failed resolution attempts), the conversation and full context are handed off to a human with no information lost
   5. Every LLM call, tool invocation, and handoff event is recorded in an immutable audit trail queryable by tenant
-**Plans**: TBD
+**Plans**: 4 plans
 
 Plans:
 - [ ] 02-01: Conversational memory layer (Redis sliding window + pgvector long-term storage with HNSW index)
@@ -64,7 +64,7 @@ Plans:
   3. A new tenant completes the full onboarding sequence (connect channel → configure agent → send test message) in under 15 minutes
   4. An operator can subscribe, upgrade, and cancel their plan through Stripe — and feature limits are enforced automatically based on subscription state
   5. The portal displays per-tenant agent cost and token usage, giving operators visibility into spending without requiring access to backend logs
-**Plans**: TBD
+**Plans**: 4 plans
 
 Plans:
 - [ ] 03-01: Channel connection wizard (Slack + WhatsApp), onboarding flow, portal polish