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94 lines
5.8 KiB
Markdown
94 lines
5.8 KiB
Markdown
# 09 — Product Roadmap (Phase 8)
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Everything from discovery, split into releases and **prioritised by user value vs
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engineering effort**. The guiding sequence: **ship the redesign + dramatically better
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(deterministic) search first**, then layer **optional local AI** in value order, each tier
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reusing infrastructure the previous one built.
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> **Update — multi-provider platform epic.** The
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> [multi-provider + admin/settings design](multi-provider/README.md) is a **v1.x platform
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> epic** (its own 6-phase plan) that the search/AI features build on. Sequencing note: the
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> **provider abstraction, unified email model, settings, and feature-flag engine land early
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> in v1.x** (they underpin multi-user + AI gating); the AI features from this roadmap then
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> plug into that flag system. Both plans share the same flag-gated, ship-dark discipline.
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## Prioritisation framework
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Score each item **Value (1–5) × (6 − Effort 1–5)**, then sequence so that (a) high-value/
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low-effort ships first, (b) risky/expensive AI comes only after its infrastructure exists,
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and (c) **nothing in an early release depends on AI being enabled.**
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```
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Value ▲ ★ MVP first ● do next ○ later
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5 │ ★ranking ★redesign ●NL search ○ask-inbox
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4 │ ★fuzzy ★chips ★summary ●semantic ●brief ○knowledge graph
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3 │ ★perf/indexes ●people ●extract ○collaboration
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2 │ ●categorise-tail ○plugins ○mobile
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1 │ ○multi-provider
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└───────────────────────────────────────────────────►
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low effort ──────────────────────────► high effort
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```
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---
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## MVP → **v1.0.0** — "The redesign + world-class deterministic search"
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Rationale: the single biggest perceived-quality jump, built mostly on **deterministic**
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tech (low risk). AI appears only as a few optional, reversible wins behind a toggle.
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- **UX v2 shell + design system + both themes** (dark-first, green ramp) — the "world-class" feel.
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- **Search core:** relevance ranking (RRF/`ts_rank`), multi-field weighted FTS, `pg_trgm`
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fuzzy, **filter chips**, saved/recent/suggested, **"why matched"** (lexical), keyset pagination.
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- **Perf/debt:** `pg_trgm` + FTS indexes, virtualised list, code-splitting, fix EF
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query-filter warning, language-aware FTS.
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- **AI foundation:** extended abstraction (`IAiProvider`+`IEmbeddingProvider`+facade+router),
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Null + Ollama wired, **VRAM guard**, prompt templates.
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- **First AI wins (optional):** thread summary · follow-up detection (heuristic + AI confirm)
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· reply suggestions.
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- **Why now:** delivers the flagship promise (fast, approachable, ranked, explainable search
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+ a premium UI) even with AI off.
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## v1.1 — "Assisted search & productivity"
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Rationale: build on MVP's embedding groundwork; assist without heavy compute.
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- **Natural-language search** parse (rules-first + optional LLM), shown as editable chips.
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- **People search** · **attachment (filename) search** · **search-driven bulk actions**.
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- **Inbox assistant / daily brief** · **task/calendar/reminder extraction**.
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- **Categorisation long-tail** (embedding zero-shot + confidence) · **priority prediction v1**.
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- **Why now:** the "assisted, not syntactic" search vision, plus the highest-value AI
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productivity features — all still light on VRAM.
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## v1.2 — "Semantic tier"
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Rationale: introduces `pgvector` + embedding backfill; unlocks meaning-based features.
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- **Semantic search** (pgvector HNSW, hybrid RRF) · **related / find-similar**.
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- **Near-duplicate detection** · **thread summaries surfaced in results** · **conversation insights**.
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- **Relationship mapping (basics)**.
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- **Why now:** semantic recall is a headline differentiator but needs the embedding
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infrastructure and backfill worker to be mature and VRAM-safe.
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## v2.0 — "Ambitious AI"
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Rationale: flagship, compute-heavy features that need a mature semantic + vision stack.
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- **Conversational "ask your inbox"** (RAG + **citations**).
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- **Entity search & facets** (amounts, orgs, dates) · **attachment OCR/content understanding** (vision, on-demand).
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- **Phishing reasoning** (LLM over flagged mail, async, explained) · **knowledge graph**.
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- **Why now:** highest wow-factor and the strongest "local private AI" story, but only
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worthwhile once retrieval, extraction, and vision infra are proven.
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## v3.0 — "Platform"
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Rationale: expand beyond the individual power-user once the core is best-in-class.
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- **Collaboration / shared inbox** (assign, comment) · **automation / rules engine**
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(a `docs/specs/feature-rules-engine.md` already exists — fold it in).
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- **Multi-account & additional providers** (IMAP/Outlook) · **plugin ecosystem** (analyzer
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API) · **mobile app** · **multi-window / desktop shell** (Tauri) · **multi-provider AI**.
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- **Why now:** platform bets that only pay off on top of a beloved core product.
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---
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## Sequencing principles (explained)
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1. **Deterministic value before AI.** MVP's biggest wins (ranking, chips, redesign) need no
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AI — they de-risk the release and prove the product before compute-heavy features.
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2. **Infrastructure amortised.** Embeddings introduced once (v1.1 foundations → v1.2 usage)
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power search, dedup, related, categorisation, and RAG — spread the cost.
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3. **Value-first within a release.** Inside each version, highest value/effort ships first so
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partial delivery is still shippable.
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4. **AI is always additive.** Every release is complete and excellent with AI disabled —
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protecting the "works without AI" mandate and the mainstream audience.
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5. **Platform last.** Collaboration/plugins/mobile are large and only worthwhile once the
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individual experience is genuinely best-in-class.
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