epic: deliver zero-to-first-memory desktop onboarding and isolated local channels

Goal

Deliver a zero-to-first-memory Answer Engine experience that a non-technical user can install from one copy-pasted prompt, launch from a desktop icon, connect to the AI agents they already use, import their history with informed consent, and prove memory recall in a fresh chat—while keeping a stable personal-memory instance completely isolated from local staging development.

Non-Technical Summary

A user should be able to paste a short prompt into Codex, ChatGPT Work/Desktop, Claude Code, or Claude Cowork and be guided through the complete setup. The installer welcomes them, asks which agents they use, checks their computer, installs the supported Answer Engine skills and MCP/CLI integrations, imports approved history, proposes an initial organization, and walks them through remembering and recalling one fact in a new chat.

A lightweight desktop application provides one-click access and health controls. The stable personal-memory channel keeps running in the background and cannot be affected by a staging channel used by local coding agents.

Supported Baseline

• macOS on Apple Silicon with at least 16 GB RAM.
• Windows 11 with WSL2 and a supported GPU with at least 8 GB VRAM.
• Capability detection recommends an appropriate local model/runtime and reports reduced-function or cloud-backed fallbacks honestly.
• Unsupported hardware or agent surfaces must fail clearly; the product must not claim local connectivity where the client cannot provide it.

Product Principles

• Local-first and private by default.
• No automatic home-directory scan.
• Every history or folder source requires explicit consent and a preview.
• Stable and staging data, credentials, ports, volumes, logs, and services are fail-closed and independently addressable.
• Skills teach workflows; MCP and CLI provide live tools and controlled actions.
• Distribution is pinned to a release/tag and verified by checksum rather than executing instructions from a floating branch.
• Installation, repair, upgrade, rollback, and uninstall are idempotent and observable.
• The Electron application is a control plane; a background service owns runtime availability.

Ordered Sub-Issues

• #41 - isolate stable and staging local Answer Engine channels
• #42 - add a cross-platform one-prompt installer and capability preflight
• #43 - install and verify Answer Engine skills, plugins, MCP, and CLI wiring
• #44 - guide and reconcile the first agent-history import
• #45 - add permissioned preview-first local folder ingestion
• #46 - propose and apply reversible AI-assisted memory organization
• #47 - prove first memory with a grounded cross-chat recall tutorial
• #48 - ship a lightweight desktop launcher and local release controls
• #68 - adopt legacy stable installs and open the real desktop web runtime
• #71 - ship immutable installer downloads and dependency-aware bootstrap
• #74 - keep local client credentials out of process arguments
• #76 - make OSS licensing and community policies unambiguous
• #77 - decide public Git history and contributor identity policy
• #78 - remove unsupported GHCR visibility mutation from release workflow
• #79 - harden GitHub settings for public contributions
• #86 - patch dependency advisories found by public-release audit
• #88 - avoid full-history archive churn on incremental transcript updates
• #89 - rebuild the public runtime from a patched base and dependency graph
• #93 - support OpenAI-compatible local model servers without LM Studio management APIs
• #80 - make the OSS repository and runtime image public
• #81 - publish and anonymously verify v1.1.2 installer assets
• #82 - validate v1.1.2 on clean Apple Silicon macOS
• #83 - validate v1.1.2 on clean Windows 11 with WSL2
• #49 - prove clean-machine onboarding and stable-staging isolation

End-to-End User Journey

1. Copy the canonical install prompt from GitHub or the website and paste it into a supported agent.
2. Answer a short welcome interview: operating system, hardware, stable/staging intent, and agents used.
3. Review preflight results and approve installation.
4. Launch Answer Engine from a desktop icon and confirm healthy local services.
5. Review discovered agent histories and explicitly approve the first import.
6. Optionally select folders, review a dry-run inventory, and approve local ingestion.
7. Review proposed libraries and tags before applying organization changes.
8. Install and verify supported skills/plugins plus MCP or CLI wiring for selected clients.
9. Tell one client a harmless fact to remember, open a fresh chat, and recall it through a real Answer Engine tool with source evidence.
10. Develop against staging without changing stable memory.

Acceptance Criteria

• A canonical, version-controlled prompt drives an agent-led install without requiring the user to understand Docker, MCP, or model configuration.
• Clean installation passes on the supported Apple Silicon and Windows baselines.
• Stable and staging channels cannot share data, credentials, ports, volumes, or sync jobs.
• A desktop icon opens a lightweight control surface and the stable runtime survives closing that surface.
• Selected supported clients receive the appropriate global or packaged skills plus verified MCP/CLI wiring.
• Client capability detection explains any ChatGPT web or Cowork localhost limitation and offers only supported alternatives.
• First history import is previewed, consented, resumable, and reconciled to a final inventory.
• Folder ingestion is opt-in, preview-first, source-backed, removable, and integrity-verifiable.
• Organization suggestions are previewed before mutation and can be audited and undone.
• A cross-chat remember/recall tutorial succeeds through real tools and grounded source inspection.
• Clean-machine acceptance, desktop/mobile visual checks, and pnpm verify pass.
• No enterprise-only roles, RBAC, teams, billing, or permission-management code enters OSS.
• No npm package is published as part of this epic.

Related Foundations

• #4 — installer-managed local UI access without a manually created API key.
• #6 — complete single-user OSS application.
• #12 — clean installer-managed product acceptance over real imported history.
• the-answerai/answer-engine-enterprise#964 — enterprise composition over the OSS core.

Sequencing

• Execute the ordered sub-issues serially because installer, runtime, client configuration, and desktop packaging surfaces overlap.
• Keep Graphify excluded.
• Only the first unblocked child should carry the ready label.
• Final acceptance must run from clean environments and explicitly prove stable/staging isolation.

Start with the remaining child issues, especially #49, #80, #81, #82, and #83, rather than treating this epic as a standalone change. Read the canonical install prompt and desktop runtime entry points, then run pnpm verify in a clean supported environment. Done means the end-to-end acceptance criteria pass, including stable/staging isolation and first-memory recall.