Product readiness

Current status: core design consulting product is locally release-ready; website improvement control tower, Website Console handoff evidence tracking and CLI/bundle evidence export with verified bundle evidence metadata, target-repo execution checklist metadata, generated bundle contract verification with per-file diagnostics and repair preview/apply, and packed-tarball evidence preservation smoke, public registry Website Console smoke coverage, Website Console MCP readiness probes, MCP probe count telemetry with package/shared smoke self-test coverage for Website Console MCP probe counts, local learning preferences, focused agent backlog reports, preview-only skill proposal reports with Markdown review artifacts, read-only review-check gates, and read-only accepted proposal apply plans, public registry workspace restore-backups readiness smoke, learning restore rollback backup pruning, workspace learning restore-backups readiness, learning restore rollback backup inventory, learning restore rollback backups, learning profile restore, learning profile diff, workspace curation report next actions, workspace learning curation next actions, learning curation Markdown reports, usage-aware learning curation review, workspace learning usage readiness, workspace learning eval freshness checks, sibling workspace learning eval checkpoint auto-detection, shell-safe workspace learning eval commands, workspace learning eval-template hints, learning eval checkpoint templates, learning eval checkpoints, usage sidecar recording/reporting, archive-first learning curation, starter learning bootstrap, explicit check feedback capture, and internal dogfood readiness snapshots are shipped; model training is not part of the shipped product.

This document separates shipped product scope from future product ideas so the roadmap does not imply that every possible AI feature is already complete.

TL;DR

Area	Status	Evidence	Remaining work
Design consulting skills	Complete for v4.55	20 skills across design systems, website improvement, UX audit, critique, handoff, motion, illustration, print, video, game UI, conversational UI, and spatial design	Keep knowledge fresh through normal stability review
Design agent workflows	Complete for v4.55	17 commands, 4 review agents, route/prompt/pack/check/search/show/examples CLI workflows	Real-CI verification before external launch
Website improvement control tower	Complete for v4.55	Zero-dependency static Web App under docs/website-console/, static Workflow Graph rendering with graph JSON copy/export, browser-local handoff evidence tracking for executed work / verification results / remaining risks / next actions, CLI/bundle evidence export through design-ai site --json, --tasks, --report, and --bundle, verified bundle evidence metadata, MCP probe evidence, bundle-check JSON/human and bundle-handoff JSON/prompt boundary metadata for deterministic-local, no-external-call, and no-target-repo-mutation handoff validation, MCP probe count telemetry and package/shared smoke self-test coverage for Website Console MCP probe counts through --next-actions, --bundle-check, --bundle-compare, and --bundle-handoff JSON, bundled Website Console mcp-probes.json saved probe evidence payload instead of the full site --mcp-check --probes --json response, generated bundle contract verification with per-file diagnostics through bundle-check/compare/handoff metadata, repair guidance through bundle-check and bundle-handoff metadata, repair preview/apply through --bundle-repair with repair report --out file output-file persistence, packed-tarball evidence preservation smoke for non-empty implementationEvidence, generated contract counts, generated drift diagnostics, repair guidance, and repair preview/apply through verified bundle paths, website-improvement route/skill/command, design-ai site sample workspace generation, prompt template listing, MCP readiness check through --mcp-check, read-only MCP readiness probes through --mcp-check --probes, Markdown MCP action plan export through --mcp-plan and --mcp-plan --probes, prioritized local operator checklists with read-only probe readiness and probe counts through --next-actions, portable workflow graph export through --graph --json, complete handoff bundle export with mcp-probes.json and downstream MCP probe count JSON through --bundle --out, handoff bundle fingerprint verification through --bundle-check --strict --json, handoff bundle comparison through --bundle-compare --strict --json, target-repo handoff prompt generation through --bundle-handoff --strict --json, local handoff bundle repair through --bundle-repair --yes --json, refactor task generation, single prompt template export with task selection, plus JSON validation/report/prompt generation, Site Profile, audit checklist, MCP readiness matrix, refactor plan generator, prompt generator, and handoff report export	Future phases can add real MCP connection probes, Playwright/Lighthouse/axe automation, and VS Code Webview reuse
Local release confidence	Complete for v4.55	npm run release:check now passes after the Website Console bundle mcp-probes.json saved-payload guard phases, after the Product Readiness and release-facing policy docs bundle boundary metadata guards for bundle-check JSON/human and bundle-handoff JSON/prompt boundary metadata plus full release:self-test evidence recording, after the release-facing policy docs guard for Website Console bundle boundary metadata full release:check evidence, and after the release-facing policy docs Product Readiness release policy full gate evidence guard, covering unit tests, strict audits, whitespace checks, package contents, release metadata, release self-tests, the full npm run release:self-test chain across shared smoke assertions, package smoke, registry smoke, release metadata, local CI, and token extractor self-tests, and packed-tarball smoke including workspace strict failure/success readiness checks plus workspace --learning-usage sidecar summaries and workspace --learning-eval checkpoint summaries and design-ai workspace workspace learning restore-backups readiness with restore rollback backup inventory, Website Console export validation through design-ai site --stdin --json, Website Console sample workspace generation through design-ai site --sample, Website Console from-intake workspace JSON stdout, JSON --out, and handoff bundle coverage through design-ai site --from-intake, Website Console project init workspace coverage through design-ai site --init in installed-bin and one-shot paths, Website Console init handoff bundle coverage through design-ai site --init --bundle --out <dir>, Website Console prompt template listing through design-ai site --prompt-list --json, Website Console MCP readiness check through design-ai site --stdin --mcp-check --json, Website Console MCP readiness probe check through design-ai site --stdin --mcp-check --probes --json, Website Console MCP action plan export through design-ai site --stdin --mcp-plan, Website Console workflow graph export through design-ai site --stdin --graph --json, Website Console handoff bundle export through design-ai site --stdin --bundle --out <dir>, Website Console non-empty evidence preservation through design-ai site --stdin --report, --tasks, and --bundle --out <dir>, Website Console handoff bundle check through design-ai site <bundle-dir> --bundle-check --strict --json with SHA-256 checksum verification, bundle digest/fingerprint verification, and generated bundle contract verification plus repair guidance, Website Console handoff bundle compare through design-ai site <bundle-dir> --bundle-compare <other-bundle-dir> --strict --json with bundle digest comparison plus warning-state strict smoke coverage that keeps identical warning bundles at sameBundle: true while exiting non-zero under --strict, Website Console target-repo handoff prompt through design-ai site <bundle-dir> --bundle-handoff --strict --json from a verified bundle digest, Website Console bundle repair preview/apply through design-ai site <bundle-dir> --bundle-repair --yes --json with repair report --out file output-file persistence, Website Console refactor task generation through design-ai site --stdin --tasks, Website Console task-selected single prompt generation through design-ai site --stdin --prompt codex-implementation --task task-homepage-cta, check learning capture, learning feedback, learn feedback --out output-file persistence, backup, redaction, learn JSON --out file writes, learn verify --out output-file persistence, learn diff JSON output, learn restore JSON output plus learn restore --out file-write confirmation, restore rollback backup inventory coverage, restore rollback backup prune preview/apply coverage through design-ai learn --restore-backups --prune --keep N, learn import --out output-file persistence, learn stats --out output-file persistence, human / JSON design-ai learn --usage usage sidecar report plus learn usage --out file-write confirmation, human / JSON design-ai learn --eval-template checkpoint generation plus generated checkpoint strict validation, human / JSON design-ai learn --eval checkpoint report plus learn eval --out file-write confirmation plus learn eval --strict failure gate, learn audit --out output-file persistence, learn --curate archive-first curation preview/apply plus --report --out Markdown report artifacts and usage-aware curation JSON review, verify, diff, restore, import, query-filtered learn list explanation/export, brief-relevant prompt/pack learning selection, prompt/pack learning usage sidecar recording, and audit cleanup guidance	Public registry smoke after publish now also verifies public registry design-ai site Website Console export validation, sample workspace coverage, prompt template listing, MCP readiness, MCP action plan, handoff bundle, bundle-check/compare/handoff/repair, refactor task generation, task-selected prompt generation, workspace --learning-usage sidecar summaries, workspace --learning-eval checkpoint summaries, public registry design-ai workspace workspace restore-backups readiness with restore rollback backup inventory, public registry design-ai learn --eval-template checkpoint generation plus public registry generated checkpoint strict validation, public registry JSON design-ai learn --restore preview/apply output plus public registry learn restore --out file-write confirmation, public registry learn restore rollback backup verification, public registry learn restore --backup-file path coverage, public registry design-ai learn --restore-backups restore rollback backup inventory coverage, and public registry design-ai learn --restore-backups --prune restore rollback backup pruning coverage
Internal dogfood readiness	Complete for v4.55	design-ai workspace reports read-only git cleanliness/sync, separates active status from ignored untracked local portfolio/evidence artifacts in JSON, canonical repository remote/metadata alignment, local learning profile audit state, usage sidecar event counts and stale selected-id readiness, optional or auto-detected sibling learning usage sidecar status, optional or auto-detected sibling learning eval checkpoint status, freshness warnings for checkpoint metadata that predates or mismatches the active learning profile, release-script availability, shell-safe learning profile/usage/checkpoint/report path commands in workspace next actions, usage-aware curation next actions plus companion learn --curate --report --out learning-curation-report.md report artifact commands for learning profile audit warnings and usage sidecar drift, and eval-template bootstrap next-action hints when a clean learning profile has entries but no checkpoint, sibling restore rollback backup inventory readiness, latest backup metadata, and prune next-action hints when older rollback backups exceed the default keep count; --strict exits non-zero on readiness warnings/failures; package smoke verifies strict JSON failure and clean-success behavior plus learning-usage, learning-eval, and workspace restore-backups summaries in installed-bin and one-shot paths, and registry smoke verifies the same learning-eval and workspace restore-backups contracts plus public registry Website Console coverage and public registry eval-template checkpoint generation after publish	Use findings to decide whether the next surface should be CLI, web UI, VS Code, Figma, or SDK
AI chat / conversational design consulting	Complete for v4.55	conversational-ui-designer, /conversational, and conversational knowledge cover voice, chatbot, and AI chat UX	Keep Korean platform conventions current
Local AI learning preferences	Complete for v4.55	design-ai learn, preview-first learn --init starter profile bootstrap, explicit learn --feedback keep/improve/avoid guidance with JSON --out artifact persistence, explicit check --learn --yes capture for local QA warning/failure results, full learn --backup --json export, redacted learn --redact --json sharing export from local profile / --from-file / --stdin, safe --out file output with --force overwrite control for JSON artifacts and export Markdown, non-mutating learn --verify, read-only learn --diff profile comparison against portable JSON, preview-first learn --restore full-profile replacement from portable backups with automatic rollback backup and optional --backup-file path, read-only learn --restore-backups sibling rollback backup inventory, preview-first learn --restore-backups --prune --keep N cleanup that deletes only older rollback backup files after --yes, confirmed learn --import, query-filtered learn --list --explain / learn --export without recency fallback, brief-relevant filtered prompt --with-learning / pack --with-learning with selection scoring metadata, local learning.usage.json sidecar events that store selected ids and short brief hashes, read-only learn --usage reports for sidecar activity, read-only learn --signals --report --out learning-signals.md Markdown signal handoff artifacts, focused read-only learn --agent-backlog --report --out agent-backlog.md agent backlog artifacts, preview-only learn --propose-skills reports for repeated check-capture skill deltas with --report --out skill-proposals.md Markdown review artifacts, read-only --review-file decision joins, read-only --apply-plan accepted proposal manual apply plans, --review-template --out skill-proposals.review.json JSON decision scaffolds, and --patch --out skill-proposals.patch unified diff handoffs, learn --eval-template runnable checkpoint generation from the active profile, read-only learn --eval checkpoint reports for deterministic learning selection QA with --strict failure gating, confirmed learn --forget/--clear, non-mutating learn --audit cleanup suggestions / learn --stats, safe learn --audit --fix --dry-run previews plus confirmed --fix --yes cleanup, archive-first learn --curate preview/apply with sibling *.archive.json preservation, learn --curate --report --out Markdown review artifacts, workspace report next actions for saving those artifacts before cleanup, and usage-aware profile-mismatch/stale/unused review hints, and learned-context audit summaries provide explicit local preference memory	Keep privacy boundaries clear as learning scope expands
AI model training	Not shipped scope	README states fine-tuning is outside shipped scope	Define a separate product phase if embeddings or fine-tuning becomes a goal
External launch	Not complete	Launch kit exists, but roadmap still marks external launch as held	Push, observe Real-CI, then publish/announce

What is complete

The shipped product is a model-agnostic design intelligence layer for AI coding agents. It is complete when an agent can:

• Route a design request to the right workflow.
• Load the relevant design knowledge and examples.
• Produce design-system, component, UX, motion, illustration, print, video, game UI, conversational, spatial, document, and slide-deck artifacts.
• Prepare website improvement work through a local Site Profile, audit checklist, MCP readiness matrix, refactor plan, prompt generator, browser-local handoff evidence tracker, CLI/bundle evidence export, verified bundle evidence metadata, handoff readiness guidance in bundle README and summary.json.handoff, MCP probe count telemetry, generated bundle contract verification with per-file diagnostics and repair preview/apply, and handoff report without mutating the target website repo from design-ai.
• Check those artifacts for grounding, accessibility, responsive coverage, route-specific quality, and unresolved markers, with optional check --learn preview/application for non-pass QA feedback.
• Inspect the current local dogfood workspace with a read-only design-ai workspace snapshot, optionally include --learning-usage path and --learning-eval path, rely on automatic sibling learning.usage.json sidecar and learning-eval.json checkpoint detection when available, treat stale or source-mismatched usage sidecars and checkpoint freshness as a readiness warning, follow usage-aware learn --curate --usage-file next actions when profile audit or usage drift needs review, save companion learn --curate --report --out learning-curation-report.md curation report artifacts before applying archive cleanup, use the eval-template bootstrap next action when profile entries exist without a checkpoint, rely on shell-safe path quoting in learning usage/eval/report next-action commands, or use design-ai workspace --strict when warnings should block handoff, before deciding whether to continue development, run verification, capture learning feedback, commit, or push.
• Store, initialize starter dogfood preferences through preview-first learn --init, record explicit keep/improve/avoid feedback, capture local check warning/failure feedback after --yes, query-filter with optional list explanations, audit with cleanup suggestions, preview/apply safe audit cleanup, archive duplicate/sensitive entries through learn --curate --yes without losing audit history, save learn --curate --report --out Markdown curation reports, review usage sidecar profile mismatch, stale selected ids, and unused active entries through advisory usage-aware curation, summarize profile and usage activity, generate runnable eval checkpoint templates, evaluate deterministic learning-selection checkpoints, export, write JSON/export artifacts through safe --out file output, create redacted shareable backups from local profiles or portable JSON sources, verify/diff/restore with rollback backup, list restore rollback backups, preview/apply older rollback backup pruning without mutating the active profile, and import portable profiles, forget, and clear explicit local learning preferences, and inject brief-relevant scoped category/limit subsets into prompts/packs only when requested with selection scoring, audit-summary metadata, and privacy-preserving usage sidecar events attached.
• Install, update, status-check, and uninstall through the packaged CLI.
• Pass the release gate without relying on manual inspection.

As of v4.55, these are covered by the manifest, commands, skills, agents, examples, and release smoke suite, including packed-tarball checks for workspace strict failure/success readiness behavior plus workspace learning-usage summaries and learning-eval summaries, Website Console export validation through design-ai site --stdin --json, Website Console sample workspace generation through design-ai site --sample, Website Console project init workspace coverage through design-ai site --init in installed-bin and one-shot paths, Website Console init handoff bundle coverage through design-ai site --init --bundle --out <dir>, Website Console prompt template listing through design-ai site --prompt-list --json, Website Console MCP readiness check through design-ai site --stdin --mcp-check --json, Website Console MCP readiness probe check through design-ai site --stdin --mcp-check --probes --json, Website Console MCP action plan export through design-ai site --stdin --mcp-plan, Website Console workflow graph export through design-ai site --stdin --graph --json, Website Console handoff bundle export through design-ai site --stdin --bundle --out <dir>, Website Console handoff bundle check through design-ai site <bundle-dir> --bundle-check --strict --json with SHA-256 checksum verification, bundle digest/fingerprint verification, and generated bundle contract verification plus repair guidance, Website Console handoff bundle compare through design-ai site <bundle-dir> --bundle-compare <other-bundle-dir> --strict --json with bundle digest comparison plus warning-state strict smoke coverage that keeps identical warning bundles at sameBundle: true while exiting non-zero under --strict, Website Console target-repo handoff prompt through design-ai site <bundle-dir> --bundle-handoff --strict --json from a verified bundle digest, Website Console bundle repair preview/apply through design-ai site <bundle-dir> --bundle-repair --yes --json with repair report --out file output-file persistence, Website Console refactor task generation through design-ai site --stdin --tasks, Website Console task-selected single prompt generation through design-ai site --stdin --prompt codex-implementation --task task-homepage-cta, public registry checks for the same workspace strict contract plus workspace learning-usage sidecar summaries, learning-eval checkpoint summaries, workspace restore-backups readiness, public registry design-ai site Website Console export validation, sample workspace coverage, prompt template listing, MCP readiness, MCP action plan, handoff bundle, bundle-check/compare/handoff/repair including warning-state bundle-compare strict smoke coverage, refactor task generation, and task-selected prompt generation after publish, check learning capture, learning feedback, learn feedback --out output-file persistence, backup, redaction, learn JSON --out file-write confirmation and forced overwrite coverage, portable learning verify --out output-file persistence, portable learning diff JSON output, portable learning restore JSON output plus restore --out file-write confirmation plus restore rollback backup verification, restore --backup-file path coverage, design-ai learn --restore-backups restore rollback backup inventory coverage, and design-ai learn --restore-backups --prune restore rollback backup pruning coverage, portable learning import --out output-file persistence, learning stats --out output-file persistence, human / JSON design-ai learn --usage usage sidecar report plus learn usage --out file-write confirmation, human / JSON design-ai learn --eval-template checkpoint generation plus generated checkpoint strict validation, human / JSON design-ai learn --eval checkpoint report plus learn eval --out file-write confirmation plus learn eval --strict failure gate, learning audit --out output-file persistence, archive-first learn --curate preview/apply coverage with curation Markdown report output, workspace curation report next actions, and usage-aware curation JSON review, verify, diff, restore, import, query-filtered learn list explanation/export, brief-relevant prompt/pack learning selection, prompt/pack learning usage sidecar recording, and learning audit cleanup suggestions. Public registry smoke also verifies public registry design-ai workspace workspace restore-backups readiness with restore rollback backup inventory, public registry design-ai learn --eval-template checkpoint generation plus public registry generated checkpoint strict validation, public registry JSON design-ai learn --restore preview/apply output plus public registry learn restore --out file-write confirmation, public registry learn restore rollback backup verification, public registry learn restore --backup-file path coverage, public registry design-ai learn --restore-backups restore rollback backup inventory coverage, public registry design-ai learn --restore-backups --prune restore rollback backup pruning coverage, learning feedback/init bootstrap, public registry learning feedback --out output-file persistence, portable learning verify --out output-file persistence, portable learning backup --out output-file persistence, public registry learning import --out output-file persistence, learning stats --out output-file persistence, public registry learning audit --out output-file persistence, portable learning import/redact behavior, query-filtered learn list/export behavior, brief-relevant prompt/pack learning selection, and learning audit cleanup suggestions plus safe cleanup dry-run/apply behavior after publish.

Local learning preferences are documented in AI-LEARNING.md.

What is not complete

The product now includes local learning preferences, but it should not be described as having completed AI model learning unless that scope is explicitly added later.

Not shipped:

• Fine-tuning a model.
• Training a private model on user artifacts.
• Embedding index generation for semantic retrieval.
• Background feedback loops that learn from accepted/rejected design recommendations without an explicit CLI command.

These are valid future product ideas, but they are different from the current architecture. The current architecture is deterministic corpus routing, prompt packing, quality checking, scoped local preference injection, and release-smoked CLI distribution.

Current release blockers

Only launch-readiness items remain in the active roadmap:

• Real-CI verification: complete — main-branch pushes run green on GitHub Actions (audit + docs deploy), and npm publish run 28569283984 succeeded with provenance (verified 2026-07-03).
• External launch: publishing is complete (npm @design-ai/cli@4.56.0, GitHub Release v4.56.0, Homebrew tap, VS Code Marketplace sungjin.design-ai-vscode v0.4.1, GitHub Pages docs); the public announcement itself remains a maintainer decision.
• Reference-link policy: decided — refs/ source links moved behind generated reference pages. tools/extractors/reference_pages.py emits docs/reference/{ant-design,mui,shadcn-ui,awesome-design-md}.md, and corpus pages (knowledge/components/INDEX.md, knowledge/patterns/brand-references.md, examples/*.md) link to those pages instead of the gitignored refs/ mirror. Plain-text refs/ provenance mentions (frontmatter source:/sources:, link text) stay as-is, and the MkDocs refs-only warning baseline in tools/audit/local-ci.py is now 0.

Recommended next decision

The next product decision is scope, not another hardening pass:

1. If the goal is to ship the current design consulting tool, run the push/Real-CI/public launch path.
2. If the goal is a deeper AI learning product, open a new phase for retrieval memory, embeddings, or fine-tuning, with explicit data boundaries and privacy constraints.
3. If the goal is “best design tool” as a broader product, define whether the next surface is CLI, VS Code, web UI, Figma plugin, or agent SDK.