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Reflect vs Tana vs Capacities: A Tools-for-Thought Review for Engineers

Two weeks running Reflect, Tana, and Capacities as a daily engineer's notebook. Capture latency, data portability, query depth, and where each one breaks down.

6 min read

Tools-for-thought apps promise the same outcome — a second brain that compounds — and ship wildly different mental models for getting there. We spent two weeks running Reflect, Tana, and Capacities side-by-side as a working engineer’s notebook: standup notes, design docs, RFC drafts, on-call postmortems, and an ongoing reading log. This is what actually held up.

What “tool for thought” means when you write code for a living

The PKM category is crowded with marketing copy that doesn’t survive contact with a sprint. Engineers don’t need a graph view to admire; you need:

  • Sub-200ms capture latency. If it takes longer to open a note than to write it, you’ll fall back to a terminal scratchpad.
  • Plain-text or markdown export. Your notes outlive any single SaaS. Lock-in is the killer.
  • Predictable linking. Backlinks that don’t silently break when you rename, with [[wiki-style]] links that resolve fast.
  • Keyboard-first navigation. A mouse round-trip per note breaks flow.
  • Real search across years of notes. Full-text, ranked, with operators.

Everything else — AI summarization, kanban, calendar integration, embedded queries — is a nice-to-have. We weighted the comparison around those five.

Reflect, Tana, and Capacities at a glance

FeatureReflectTanaCapacities
Mental modelDaily notes + backlinksOutliner with supertagsObject-based PKM
StorageCloud, E2E encryptedCloud, proprietaryCloud, proprietary
Markdown exportPer-note or bulkStructured JSON + MDMD + JSON
Public APILimited betaNot yet shippedNot yet shipped
Native AIGPT-4, includedTana AI, paid tierCapacities AI, Pro
OfflineMac/iOS partialOnline onlyPartial desktop cache
Price (annual billing)~$10/mo~$10-14/moFree / ~$12.49/mo Pro

The pricing converged around $10-15/month, so cost is rarely the deciding factor. What matters is the data model.

Reflect — opinionated and quiet

Reflect bets on one workflow: open the app, land on today’s daily note, type, links resolve to backlinks automatically. There’s almost nothing to configure. Capture was the fastest of the three in our measurement — roughly 140ms from cmd-N to a blinking cursor. The AI features (“ask my notes,” outline generation, transcription) are baked in rather than bolted on.

The tradeoff is rigidity. If you want structured fields per note (status, priority, tags with values), Reflect mostly says no. It’s a journal that grew up.

Tana — power-user maximum

Tana is what happens when you take Roam’s bidirectional links, fuse them with Notion-style databases, and let everything be both a node and a query. Supertags are the headline feature: tag a node #book and it inherits fields (author, status, rating) and shows up in any view that queries #book.

If you already write Notion databases by hand, Tana is faster. But the learning curve is real — we spent the better part of a weekend understanding how supertags inherit, when search-nodes differ from queries, and how to design a workspace that doesn’t collapse under its own structure once you cross a few hundred nodes.

Capacities — middle path with objects

Capacities sits between the two. Everything is an “object” with a type — Person, Book, Project, Meeting — and each type has its own template. It’s lighter than Tana, more structured than Reflect. Backlinks work, but the unit of thought is the object, not the daily note.

The free tier is genuinely usable for solo work. Pro unlocks AI features and unlimited storage.

Where each one breaks down

After two weeks, the failure modes were specific.

Reflect broke down on structured projects. Tracking a dozen open RFC reviews across three repos, each with status and reviewer, devolved into prose that didn’t filter or sort. We ended up exporting to a CSV.

Tana broke down on quick capture. The supertag prompts and field-completion modals that make queries powerful slowed every standup note by a few seconds. Small in isolation, painful at forty captures a day.

Capacities broke down on cross-object queries. Asking “show every meeting where person X is attendee and the related project is on hold” required either manual page navigation or query syntax that’s less expressive than Tana’s. The object model is clean; the query layer hasn’t caught up.

Picking one without regret

The honest decision tree we landed on:

  1. You want a journal that auto-builds a graph and you’ll never script it. Pick Reflect. It’s the most likely to still feel good in 18 months because there’s nothing to maintain.
  2. You’ll spend a weekend designing a workspace and want database-grade queries. Pick Tana. The ceiling is highest; budget the onboarding.
  3. You think in entities — books, people, papers, companies. Pick Capacities. The object model maps cleanly to bibliographies and CRM-like notes.
  4. You need scripting, plugins, or local-first storage. None of these. Use Obsidian or Logseq, and revisit this category in a year.

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FAQ

Can I migrate between Reflect, Tana, and Capacities later?
Partially. All three export markdown, but backlinks, queries, and supertags do not survive the round trip cleanly. Plan to lose the structural metadata — the prose itself stays intact.
Which works best for a team rather than a solo notebook?
Tana and Capacities both support multiplayer; Reflect is solo-first. For shared knowledge bases past about five contributors, Tana's query model scales better than Capacities' object model.
Is the built-in AI worth paying for?
Reflect's GPT-4 integration over existing notes was the most useful of the three because it runs against years of your own writing. Tana AI and Capacities AI lean more workflow-oriented (generate templates, summarize meetings) and overlap with what you'd already build in Cursor or a Claude project.

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