AI spend has no ceiling — and no link to outcomes.
The bill grows every month. Nobody can cap it without slowing the team down. And nobody can connect it to anything that shipped. Timo attacks the waste at its source and puts a real number — cost per shipped outcome — in front of it.
The bill is structural, not sloppy.
Coding agents don’t cost more because your team is careless. They cost more because of how they work — and because nobody is measuring what the tokens buy.
The tokens of single-shot use
That’s what coding agents consume compared to asking a model one question — with 30× variance on the same task. Two runs of the same job can differ in cost by an order of magnitude.
Of tokens go to the agent reviewing its own work
More than half the bill is the agent checking itself — re-reading, re-deriving, second-guessing. You pay for the doubt, not just the code.
Of enterprises exceeded AI budgets
In a year when token prices fell 67%. Cheaper tokens didn’t mean smaller bills — usage grew faster than prices dropped.
When AI coding costs pass a developer's salary
Gartner projects AI coding costs will surpass an average developer’s salary by 2028. Nearly a quarter of tech leaders already spend $200–500 per developer per month.
How long Uber’s entire 2026 AI budget lasted
Adoption jumped from 32% to 84% of ~5,000 engineers, at $500–$2,000 per engineer per month. Uber responded with a $1,500/tool/month cap. Its COO, asked about connecting the spend to shipped value: “That link is not there yet.”
“Claude burns through tokens with no regard.”
Your agent re-learns your codebase every session. You pay every time.
Most of the burn is the agent re-deriving your codebase from zero — reading files, tracing calls, rediscovering the same conventions and the same architecture it worked out yesterday. That’s not a model problem. It’s a missing-memory problem: nothing the agent learns survives the session, so you buy the same understanding again tomorrow.
What a session buys, with and without memory
Without memory, the bulk of the spend is rediscovery. With Timo Memory installed, the agent starts from written-down facts about your codebase — cited to file and line — and spends its tokens on the change itself.
Teams see 40–65% token reduction after memory install — not by throttling the agent, but by removing the work it never needed to repeat. How Timo Memory works →
Stop reporting spend. Start reporting what it bought.
A cap controls the bill and slows the team. Timo Scoreboard does something different: it connects every token to the work it produced, so you can cut waste instead of cutting output.
Token spend per task
Measured against a pre-memory baseline, so the reduction is a fact on a chart — not a feeling.
Cost per shipped feature
Not cost per seat, not cost per month. Cost per thing that actually reached your users.
Cost per accepted, production-safe outcome
The composite nobody else publishes: what it cost to get a change written, checked against what you asked for, and merged safely. It’s the link Uber’s COO said “is not there yet” — priced.
Share of tokens on the cheapest passing model
How much of your work runs on the cheapest model that still passes the gate — the routing lever most teams never pull because they can’t see it.
Every number ships with a baseline, a target, an owner, and a next action — so the board pack answers “what did the spend buy?” instead of restating the invoice. See Timo Scoreboard →
See the waste first. Then cap it at the source.
No budget meeting required. The first step is read-only and free.
Run the Agent-Readiness Scan
It shows what agents currently pay to rediscover your codebase — the missing memory, missing docs, and missing conventions that turn every session into a re-derivation. You get a Readiness Score per repo.
Install Timo Memory
Written-down, cited facts about your codebase that agents load instead of re-deriving. This caps the waste at the source — the agent stops buying the same understanding twice.
Put Timo Scoreboard in front of the spend
Token spend per task against its baseline, cost per shipped feature, cost per accepted outcome — with an owner and a next action on each. In the paid program, the pair reviews it with you every month.
Find out what your agents are paying to re-learn.
Five minutes to your first Readiness Score. Read-only — nothing written to your repo.