# Design Decisions

This file records architectural choices and the alternatives considered.
New entries are added when a design decision is resolved (not when options
are brainstormed). Unresolved questions live in DESIGN.md §10.

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## Why Mattermost Plugin vs Bot Account

**Context:** AI assistants in Mattermost can be implemented as plugins
(running inside the Mattermost server process) or as bot accounts
(independent services using the REST API and WebSocket).

**Alternatives considered:**
1. **Plugin** — hooks into slash commands, message hooks, KV store, System
   Console config UI, and the plugin lifecycle. No separate process to
   manage. Deployment is a single `.tar.gz` upload.
2. **Bot account** — separate service, more language freedom, but requires
   managing OAuth tokens, WebSocket reconnection, a separate process with
   its own lifecycle, and the bot account itself in Mattermost.

**Outcome:** Plugin chosen for v0.1.0 because:
- Single deployment artifact
- Built-in config UI via System Console
- No bot account to create and maintain
- KV store for persistence without a database
- Simpler for the target audience (self-hosted teams)

**Trade-off:** Plugin runs inside the Mattermost process — bugs can affect
server stability. Mitigated by standard isolation practices (panic recovery,
goroutine lifecycle management).

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## Why Ollama

**Context:** Backend LLM provider for the plugin.

**Alternatives considered:**
1. **Ollama** — Single binary, simple REST API, streaming, model management,
   self-hosted (data never leaves the infrastructure). Community Edition
   friendly.
2. **OpenAI / Anthropic API** — SaaS, API key required, data leaves the
   network, ongoing API costs. Not aligned with self-hosted Mattermost
   ethos.
3. **Local inference (llama.cpp, etc.)** — More complex to set up and
   manage. Ollama wraps this with a clean API.

**Outcome:** Ollama. It matches the self-hosted, no-data-leaves paradigm of
Mattermost Community Edition and provides the simplest API surface for a
plugin to consume.

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## Why Per-Channel Per-User Context (Proposed)

**Context:** When a user sends `/ai <prompt>`, should the plugin remember
previous exchanges?

**Alternatives considered:**
1. **Per-user global** — Context follows the user across channels. Simple
   but confusing: context from a #general question leaks into #dev.
2. **Per-channel per-user** — Each user gets separate context in each
   channel. Natural mapping: different channels are different topics.
3. **No context** — Stateless. Simplest but every prompt is isolated;
   users can't have a conversation.

**Outcome (proposed):** Per-channel per-user. Marked as D2 in DESIGN.md —
not final until v0.1.0 implementation.

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## Why @-mention + Engagement Lifecycle over Slash-Command-Only

**Context:** How does the user interact with the AI agent? Slash commands
(`/ai`) are explicit but unnatural — users must learn a command syntax.
Bot @-mentions match how users already talk to each other in Mattermost.

**Alternatives considered:**
1. **Slash command only** (`/ai <prompt>`) — Explicit, discoverable via
   `/ai help`. But every interaction requires the prefix, and thread
   continuation is ambiguous.
2. **@-mention only** (`@mattermore <prompt>`) — Natural, familiar UX.
   Users already @-mention teammates. Thread replies continue the
   conversation without re-mentioning. Risk of accidental triggers.
3. **Channel whisper (reply to everything)** — Simplest for the user but
   noisy and invasive. The user explicitly rejected this.
4. **Hybrid: @-mention primary + /ai fallback** — Both work identically.

**Outcome:** Hybrid (#4) chosen because:
- @-mention is the primary, most natural interface
- `/ai` is available for users who prefer it or when @-mention is
  inconvenient (e.g. automated scripts, mobile)
- Both paths go through the same `EngagementEngine` — identical behaviour
- Thread replies auto-continue without re-mentioning (D6 resolved — core
  feature, not deferred)

**Trade-off:** @-mention requires a bot account (`API.CreateBot()`). This
adds a one-time setup step and a DB row, but the plugin handles creation
and deactivation automatically. The bot account is not a separate service —
it's an identity within the plugin process, so there's no extra deployment
artifact or OAuth management.

## Why Thread Posts Instead of Ephemeral Messages

**Context:** Where does the bot's response appear?

**Alternatives considered:**
1. **Ephemeral post** — Only the requesting user sees it. Clean but
   invisible to the rest of the channel/reviewers.
2. **Channel-wide post** — Visible to everyone. Can be noisy if the bot
   posts long responses.
3. **Thread post** — Visible to everyone but collapsed into a thread.
   Channel stays clean, conversation history is easy to follow. Thread
   replies naturally continue the conversation.

**Outcome:** Thread post (#3) chosen because:
- Threads keep the channel tidy
- Community can see and follow AI interactions
- Thread replies map 1:1 to conversation continuation
- Users can collapse/hide threads they don't care about

**Trade-off:** Threads require the user to click into them to see the full
response on some clients. Mitigated by showing a preview snippet in the
channel.

## Why No Webapp UI

**Context:** Should the plugin ship a webapp component (channel header
button, right-hand side panel, custom settings page)?

**Alternatives considered:**
1. **No webapp** — Pure server-side plugin. @-mention + `/ai` + thread
   replies covers everything. Simplest to build and maintain.
2. **Channel header button** — Button to open an AI chat panel. Adds
   discoverability but duplicates what @-mention already does.
3. **Custom settings page** — Duplicates System Console settings in the
   main UI. Adds complexity for marginal benefit.

**Outcome:** No webapp (#1) chosen because:
- @-mention is already discoverable (Mattermost autocompletes)
- Thread replies provide a natural conversation UI
- No frontend to build, bundle, or version
- All configuration stays in System Console where admins expect it

**Trade-off:** Users must know the bot exists to @-mention it. Mitigated by
mentioning it in channel header, onboarding posts, or `/ai help`.

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*This file follows the template from the `project-docs` skill.*