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docs(ai-sessions): document AI design sessions in context files and README - #27

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Sep 15, 2026
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Stacked on #26 (#21 → #22 → #23 → #25 → #26 → this). The base is feat/ai-generation-quality, so this diff shows step 6 only. After the PR below it merges, change this PR's base to main.

Why

Steps 1–5 replaced the one-shot "diagram from prompt" feature with saved, multi-turn AI design sessions, but the context files and README still described the old flow. This is step 6 of the AI sessions plan. It changes docs only; no code.

What

  • context/architecture-context.md:
    • a new AI Design Agent section:
      • one turn is one Trigger.dev run
      • the steps of a turn: canvas summary, analyze, plan, generate, validate and repair
      • rules enforced in code
      • replies saved when the session is read
      • timeouts, a single task attempt and the schema retry
      • model and thinking settings
    • invariants 5–9:
      • generated content reaches clients only through Liveblocks
      • the task never writes to the database or blob storage
      • a project's id is its room id
      • tokens are minted in one place after a TaskRun check
      • model output is validated
  • context/project-overview.md:
    • canvas snapshots are in Vercel Blob (the file still said "filesystem")
    • the AI section adds the question, plan and result cards, and canvas-aware generation that adds, but doesn't edit, components
  • context/ui-context.md: the AI sidebar session bar, saved-chat list and chat cards follow the paper conventions.
  • context/progress-tracker.md: the step 6 entry and the current goal (the Specs tab is next).
  • README.md: local AI setup covering the API key and model, the migrations, running and restarting the worker, and CRON_SECRET in production.

docs.md stays local

docs.md is listed in .gitignore and has never been committed, so it is not in this PR. The matching refresh was made in the local working copy:

  • the AI category rewritten (AI design sessions, How generation works, Sessions & storage)
  • updated reference tables, spec index S1–S6, architecture, roadmap and decisions
  • a fixed in-doc link

Keeping it local was a deliberate choice.

Verification

  • Stale-reference grep across README.md, the context files and the local docs.md (/api/ai/design outside the token route, useDesignAgent, generateObject, "Diagram from prompt", "lost on reload", "filesystem"): no stale matches remain.
  • Link check: every in-doc anchor link in the local docs.md resolves.
  • Not re-run: lint, typecheck and build, since no code changed.

🤖 Generated with Claude Code

…EADME

Brings the tracked docs in line with AI sessions steps 1-5. Docs only.
docs.md is gitignored, so its matching refresh stays local.

- context/architecture-context.md: AI Design Agent section (turn = run,
  turn steps, code-enforced rules, settle on read, reliability, model
  config) and invariants 5-9
- context/project-overview.md: canvas snapshots in Vercel Blob (was
  "filesystem"); chat cards and canvas-aware generation
- context/ui-context.md: AI sidebar session bar, saved chats and cards
  follow the paper conventions
- context/progress-tracker.md: step 6 entry and current goal
- README.md: local AI design agent setup

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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@Suharshit
Suharshit merged commit 7f0f249 into feat/ai-generation-quality Sep 15, 2026
5 checks passed
Suharshit added a commit that referenced this pull request Sep 15, 2026
GitHub main has steps 1-3 only; steps 4-6 were merged into stacked base branches. Content matches local exactly; a stacked merge into main conflicts in 11 files, so main needs a sync commit whose tree is the stack head.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Suharshit added a commit that referenced this pull request Sep 15, 2026
* feat(ai-sessions): add persistent storage for AI design sessions

The AI sidebar kept its chat in React state only, so a reload lost the
transcript and any in-flight run. This adds the storage layer the
multi-turn design agent will build on (not wired to the UI yet).

- AiSession / AiMessage Prisma models + additive migration; sessions
  cascade with their project, messages cascade with their session
- lib/ai/session-store.ts: 7-day sliding expiry, 10 sessions per user
  per project, 60 messages per session; reads ignore expired rows
- GET/POST /api/projects/[projectId]/ai-sessions and
  GET/DELETE /api/projects/[projectId]/ai-sessions/[sessionId],
  private to the session's creator
- Daily Vercel Cron cleanup at /api/cron/ai-sessions/cleanup,
  gated by CRON_SECRET (public in proxy.ts)

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* feat(ai-sessions): run the AI Architect chat on stored sessions

A reload no longer loses the chat or an in-flight run. Generation is
still one-shot; this changes persistence and resume only.

- POST /api/projects/[projectId]/ai-sessions/[sessionId]/turns stores
  the prompt and a PENDING reply carrying the run id (replaces
  POST /api/ai/design, which is removed)
- Replies are settled from runs.retrieve whenever a session is read, so
  a turn is saved even if the tab closed mid-run; concurrent reads
  settle once
- useAiSession replaces useDesignAgent: reopens the last chat, resumes
  pending runs via Realtime with a 4s polling fallback, stores new chats
  lazily on the first message
- Sidebar session bar with saved-chat history (delete, expiry) and
  New chat
- Limits moved to lib/ai/session-limits.ts for client use;
  formatRelativeTime extracted to lib/relative-time.ts

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* feat(ai-agent): multi-turn design agent - clarify, plan, then generate

Each turn is still one design-agent run, but the agent now keeps a
requirements brief, asks up to 3 rounds of clarifying questions when
an unknown would change the architecture, proposes a plan (components,
flows, decisions with rationale and alternatives, assumptions), and
only draws the diagram once the plan is approved.

- lib/ai/agent-schema.ts: brief, question, plan, turn-analysis and
  run-result schemas; list limits trimmed in code rather than enforced
  as maxItems, which models don't reliably honour
- lib/ai/prompts.ts, lib/ai/design-agent-engine.ts: analyze/plan/
  generate on generateText + Output.object; code-enforced decision
  rules; per-step thinking level (Gemini 3) or budget (Gemini 2.x);
  one retry on schema mismatch; per-call timeouts
- design-agent task: single attempt, maxDuration 300s
- Turns route accepts message, answers, generate and skip; stored
  replies are validated run output (QUESTIONS / PLAN / RESULT) and run
  failures are shown as friendly messages

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* feat(ai-agent): question, plan and result cards in the AI sidebar

The AI Architect chat now renders the design agent's turns as cards
instead of plain text, so users answer, skip and approve with buttons.

- QuestionsCard: option chips and a free-text answer per question,
  Send answers and Skip; read-only with the chosen answers once sent
- PlanCard: summary, highlighted key decisions with rationale and
  alternatives, components (folded after 6), flows, assumptions, and
  Draw this plan
- ResultCard: canvas summary with collapsible decisions
- Only the newest non-failed reply is interactive, and only while no
  turn is pending, mirroring the server's rules
- useAiSession.sendTurn sends message, answers, generate and skip,
  with optimistic user text matching what the server stores
- TurnInput, the generate/skip texts and payload readers now live in
  the client-safe agent-schema and are shared with the server; question
  and plan payloads also store the agent's reply

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* feat(ai-agent): canvas-aware generation with roles, async edges and repair

The design agent now sees what is already on the canvas, so follow-up
requests extend the existing design instead of redrawing it, and
generated diagrams match the starter templates' visual conventions.

- lib/ai/canvas-summary.ts: compact canvas listing with refs (ex-N),
  kinds, used connection points, connections and notes, passed to the
  analyze, plan and generate steps
- Generation schema: role + kicker instead of legacy dark colorId,
  sync/async delivery (async edges dashed); edges may reference
  existing components by ref
- buildCanvasGraph: resolves refs, folds redrawn or repeated components
  into the existing/first node, drops unknown and duplicate links, and
  assigns connection points counting existing edges
- lib/ai/graph-validation.ts + one repair call: duplicate/redrawn
  components, unknown refs, self loops, repeated links, >4 connections,
  unconnected components, missing plan components
- Shared NODE_ROLES / getRoleFill and SHAPE_KICKERS in types/canvas.ts
  (starter templates use them)
- Plan text no longer shows internal canvas refs

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* docs(ai-sessions): document AI design sessions in context files and README

Brings the tracked docs in line with AI sessions steps 1-5. Docs only.
docs.md is gitignored, so its matching refresh stays local.

- context/architecture-context.md: AI Design Agent section (turn = run,
  turn steps, code-enforced rules, settle on read, reliability, model
  config) and invariants 5-9
- context/project-overview.md: canvas snapshots in Vercel Blob (was
  "filesystem"); chat cards and canvas-aware generation
- context/ui-context.md: AI sidebar session bar, saved chats and cards
  follow the paper conventions
- context/progress-tracker.md: step 6 entry and current goal
- README.md: local AI design agent setup

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* feat(spec): generate a Markdown technical spec from the canvas

The Specs tab now turns the current canvas into a Markdown technical
spec that downloads automatically: an overview, key decisions
highlighted as callouts, one Mermaid diagram section per group of
connected components, a component reference, connections, and risks.

- spec-agent Trigger task: reads the room, builds the spec graph in
  code, makes one structured model call for the prose (sanitised
  against the graph, internal refs stripped), renders the Markdown in
  code; aborts on an empty or oversized canvas
- Stored on read like AI turns: GET /api/projects/[id]/spec uploads a
  finished run to private Vercel Blob and records it on Project
  (guarded on the run id); POST starts a run (409 while one is
  pending); GET .../spec/markdown downloads the file
- Decisions recorded in the user's AI design sessions are included and
  tagged as recorded
- Migration: TaskRun.kind (DESIGN or SPEC) and Project spec fields
- useSpecGenerator and SpecPanel replace the placeholder Specs tab
- Shared lib/ai/model.ts, lib/ai/run-failure.ts and lib/canvas-room.ts
  used by both agents

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* docs(tracker): record stacked merges of #25-#27 and the main sync need

GitHub main has steps 1-3 only; steps 4-6 were merged into stacked base branches. Content matches local exactly; a stacked merge into main conflicts in 11 files, so main needs a sync commit whose tree is the stack head.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* docs(tracker): record merging the AI stack into main

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 5 <noreply@anthropic.com>

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