# 09 — Product Roadmap (Phase 8)

Everything from discovery, split into releases and **prioritised by user value vs
engineering effort**. The guiding sequence: **ship the redesign + dramatically better
(deterministic) search first**, then layer **optional local AI** in value order, each tier
reusing infrastructure the previous one built.

> **Update — multi-provider platform epic.** The
> [multi-provider + admin/settings design](multi-provider/README.md) is a **v1.x platform
> epic** (its own 6-phase plan) that the search/AI features build on. Sequencing note: the
> **provider abstraction, unified email model, settings, and feature-flag engine land early
> in v1.x** (they underpin multi-user + AI gating); the AI features from this roadmap then
> plug into that flag system. Both plans share the same flag-gated, ship-dark discipline.

## Prioritisation framework
Score each item **Value (1–5) × (6 − Effort 1–5)**, then sequence so that (a) high-value/
low-effort ships first, (b) risky/expensive AI comes only after its infrastructure exists,
and (c) **nothing in an early release depends on AI being enabled.**

```
 Value ▲   ★ MVP first        ● do next        ○ later
   5 │ ★ranking ★redesign     ●NL search       ○ask-inbox
   4 │ ★fuzzy ★chips ★summary ●semantic ●brief  ○knowledge graph
   3 │ ★perf/indexes          ●people ●extract  ○collaboration
   2 │                        ●categorise-tail  ○plugins ○mobile
   1 │                                          ○multi-provider
     └───────────────────────────────────────────────────►
        low effort ──────────────────────────► high effort
```

---

## MVP → **v1.0.0** — "The redesign + world-class deterministic search"
Rationale: the single biggest perceived-quality jump, built mostly on **deterministic**
tech (low risk). AI appears only as a few optional, reversible wins behind a toggle.
- **UX v2 shell + design system + both themes** (dark-first, green ramp) — the "world-class" feel.
- **Search core:** relevance ranking (RRF/`ts_rank`), multi-field weighted FTS, `pg_trgm`
  fuzzy, **filter chips**, saved/recent/suggested, **"why matched"** (lexical), keyset pagination.
- **Perf/debt:** `pg_trgm` + FTS indexes, virtualised list, code-splitting, fix EF
  query-filter warning, language-aware FTS.
- **AI foundation:** extended abstraction (`IAiProvider`+`IEmbeddingProvider`+facade+router),
  Null + Ollama wired, **VRAM guard**, prompt templates.
- **First AI wins (optional):** thread summary · follow-up detection (heuristic + AI confirm)
  · reply suggestions.
- **Why now:** delivers the flagship promise (fast, approachable, ranked, explainable search
  + a premium UI) even with AI off.

## v1.1 — "Assisted search & productivity"
Rationale: build on MVP's embedding groundwork; assist without heavy compute.
- **Natural-language search** parse (rules-first + optional LLM), shown as editable chips.
- **People search** · **attachment (filename) search** · **search-driven bulk actions**.
- **Inbox assistant / daily brief** · **task/calendar/reminder extraction**.
- **Categorisation long-tail** (embedding zero-shot + confidence) · **priority prediction v1**.
- **Why now:** the "assisted, not syntactic" search vision, plus the highest-value AI
  productivity features — all still light on VRAM.

## v1.2 — "Semantic tier"
Rationale: introduces `pgvector` + embedding backfill; unlocks meaning-based features.
- **Semantic search** (pgvector HNSW, hybrid RRF) · **related / find-similar**.
- **Near-duplicate detection** · **thread summaries surfaced in results** · **conversation insights**.
- **Relationship mapping (basics)**.
- **Why now:** semantic recall is a headline differentiator but needs the embedding
  infrastructure and backfill worker to be mature and VRAM-safe.

## v2.0 — "Ambitious AI"
Rationale: flagship, compute-heavy features that need a mature semantic + vision stack.
- **Conversational "ask your inbox"** (RAG + **citations**).
- **Entity search & facets** (amounts, orgs, dates) · **attachment OCR/content understanding** (vision, on-demand).
- **Phishing reasoning** (LLM over flagged mail, async, explained) · **knowledge graph**.
- **Why now:** highest wow-factor and the strongest "local private AI" story, but only
  worthwhile once retrieval, extraction, and vision infra are proven.

## v3.0 — "Platform"
Rationale: expand beyond the individual power-user once the core is best-in-class.
- **Collaboration / shared inbox** (assign, comment) · **automation / rules engine**
  (a `docs/specs/feature-rules-engine.md` already exists — fold it in).
- **Multi-account & additional providers** (IMAP/Outlook) · **plugin ecosystem** (analyzer
  API) · **mobile app** · **multi-window / desktop shell** (Tauri) · **multi-provider AI**.
- **Why now:** platform bets that only pay off on top of a beloved core product.

---

## Sequencing principles (explained)
1. **Deterministic value before AI.** MVP's biggest wins (ranking, chips, redesign) need no
   AI — they de-risk the release and prove the product before compute-heavy features.
2. **Infrastructure amortised.** Embeddings introduced once (v1.1 foundations → v1.2 usage)
   power search, dedup, related, categorisation, and RAG — spread the cost.
3. **Value-first within a release.** Inside each version, highest value/effort ships first so
   partial delivery is still shippable.
4. **AI is always additive.** Every release is complete and excellent with AI disabled —
   protecting the "works without AI" mandate and the mainstream audience.
5. **Platform last.** Collaboration/plugins/mobile are large and only worthwhile once the
   individual experience is genuinely best-in-class.