AMOTION
Timo Memory · Timo Docs

Agents that stop re-deriving your codebase every session.

Timo writes verified memory for your agents and living documentation for your people — committed to your repos, in your git. Every claim cites the exact file:line that proves it, or is flagged as a gap. No unmarked guesses.

The waste, measured

Without memory, every session starts from zero.

The agent re-reads your code, re-derives the rules, re-discovers the gotchas — and forgets all of it when the session ends. You pay for the same understanding again and again.

~1000×

the tokens of single-shot use

That’s what agent-driven coding consumes — with 30× variance on the same task. Most of it is the agent working out things somebody on your team already knows.

arXiv:2604.22750
59.4%

of tokens go to the agent reviewing itself

More than half the bill is the agent checking its own work — without your team’s record of what correct looks like.

arXiv:2601.14470
73%

of enterprises exceeded their AI budgets

In a year when token prices fell 67%. Cheaper tokens didn’t make it cheaper — the re-deriving grew faster than the prices dropped.

EMA 2026 · industry survey
All you wind up doing is consuming all of your available context, with irrelevancies, and your agent gets dumber and costs more.
Hacker News, on legacy codebases
How it works

Every claim proves itself — or says it can’t.

Memory is only worth loading if your agents can trust it. Three rules make it trustworthy.

cite or flag

Every statement is backed or marked

Each line of memory either cites the file and line that proves it, or is flagged as a gap. There is no third state — no plausible-sounding filler for an agent to build on.

human check

A person verifies before it lands

Generated notes arrive unverified. Someone on your team promotes them before agents rely on them. Memory is approved by your engineers, not scraped and assumed.

stays true

It updates when code merges

Memory is checked and refreshed as part of the merge, so it moves with the code. A living record, not a wiki that rots — the citation either still holds, or the note gets fixed or flagged.

ai_memory/payments-service.mdProduct illustration — example note
RULE Payment retries must carry the idempotency key — a retry once re-posted a charge instead of replaying it.
→ src/payments/retry.ts:41 · verified
GOTCHA Webhook events arrive out of order under load. Consumers sort by event timestamp, never by arrival.
→ src/payments/webhooks.ts:112 · verified
GAP Partial-refund flow — not recorded yet. Waiting on a module owner to verify.
no citation — flagged as a gap
Cited, verified, or flagged — nothing else gets in
Two layers, one truth

Same facts. Two readers.

Agents and humans need the same knowledge in different shapes. Timo keeps both, from one set of verified facts — so they can’t drift apart.

Timo Memory — what agents load

The compact layer for the machine. Small enough to load at the start of every session. Dense enough that the agent starts already knowing the things that aren’t in the code:

  • What broke before, and why
  • The rules that apply to this module
  • The gotchas no file explains

Timo Docs — what humans read

The full docs for your people. Technical and functional documentation written from the same verified facts — what a new engineer reads in week one, what on-call opens at 2am:

  • Architecture and how the pieces connect
  • Screens, flows, and data — what the system does
  • Every claim cited or flagged, same as memory

Both live in your git. Both update when code merges. If you stop working with us, all of it stays yours.

What changes

After the install.

Memory doesn’t make agents smarter. It stops them spending your money re-learning what your team already paid to learn.

40–65%

token reduction

What teams see after memory install. The agent loads verified memory instead of re-reading the codebase to rediscover it.

Old bugs stop repeating

Memory of past incidents loads before the change is planned — the trap the agent would have walked into is already on the record.

Review gets cheaper

The gate checks each change against memory: has this broken before, which rules apply. Reviewers start from the record, not from a cold diff.

Every decision writes back

Each human gate decision — accept, reject, override — becomes memory. The next change starts knowing what the last reviewer decided.

The bar we hold ourselves to

What working memory has to prove.

This is the design target we test on your codebase at install — a goal we measure against, not a benchmark result we’re claiming.

Design target — tested at install, not a benchmark result

Same spec, same memory, nearly the same implementation — run after run, at a fraction of the tokens.

If memory doesn’t make agent output more repeatable on your codebase, it isn’t working — and the scoreboard will say so.

See the scoreboard →
Get started

Find out what your agents can’t see.

The Agent-Readiness Scan is free and read-only. Five minutes to your Readiness Score — including how ready your docs and memory are.