launchsolo.ai
Roles / AI Cost & Spend Engineer
AI Cost & Spend Engineer

Every run draws power. Now it draws a budget too.

Agent and inference spend is the line item nobody can predict and everybody fears. I make it a number you set in advance - estimated before a run executes, hard-stopped at a cap, so a runaway loop can never drain the account.

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pre-run estimatehard cap, not a warningper-task / per-model spendcost-aware routing
The benefit, before anything else

You approve the spend. You don't discover it.

A typical run is estimated up front and sized against the cap you set. If a loop tries to overshoot, it halts at the limit - it does not send a warning email after the money is gone. The bill stops being a surprise and starts being a setting.

live run, against your cap
normal taskest. $0.41
approved before it ran - well under cap
runaway loophalted at cap
hard-stopped at the limit - no surprise invoice
What this work actually is

Turning a scary variable bill into a fixed, governed line.

Cost engineering for AI is knowing what a run will cost before you run it, and making sure it can never cost more than you allowed. It is instrumentation, estimation, and hard limits - the parts that put a ceiling over the one number finance cannot currently forecast.

Where this gets deployed in the real world

The same control, across very different rooms.

Any organization running models at volume hits the same wall: spend that scales faster than anyone forecast. Cost governance is how they keep using AI without the invoice setting the agenda.

Scale-ups & SaaS

The feature that ate its own margin

A product ships an AI feature, usage climbs, and the inference bill quietly outruns the revenue it earns. Per-user cost caps and routing put the unit economics back in the black.

Enterprise & finance

The budget line nobody could sign off

Finance will not approve a spend it cannot bound. A pre-run estimate plus a hard cap turns "unknown agent cost" into a fixed monthly ceiling a CFO can actually authorize.

Public sector & nonprofits

The grant that can't be overspent

An agency or foundation runs AI against a fixed-grant or fixed-fund envelope. Hard caps guarantee the program never spends a dollar past what was allocated for it.

The frontier most cost tools still miss

The bill is set before the run starts - so the control belongs there too.

Almost every AI cost tool records spend after it happens. That is an autopsy. The expensive truth is that an agent task is not one call - it is a loop that re-pays for its own growing context every step, and a runaway is already over budget by the time a dashboard shows it. The leverage is a ceiling set before execution, which almost nobody sells.

Estimate first

Price the run before it runs

The most useful number is the one you get before the money is spent. Knowing a run's likely cost lets you refuse the expensive ones up front instead of finding them on the invoice.

Cap the loop

A hard ceiling, not a chart

Decide the maximum a task may spend or how many steps it may take, and stop it there. An agent stuck at step N is not finishing at N+1 - the cap turns a runaway into a known, bounded cost.

Trim the context

Stop re-paying for the same tokens

Large tool outputs do not need to ride along for the whole task. Summarize or drop them once used, so step twelve is not still paying for the blob step three read.

Why this is early

I build the pre-run estimate and the hard cap into the agent itself - spend control that acts before the money is gone, where observability tools only watch. Related: your AI bill is the retry loop →

How it works

Fixed scope. Async. One payment after the audit.

  1. Scope and audit. You send your current AI spend shape and where it scares you. I return a fixed price and a plan within 24 hours, or a straight no.
  2. Instrument the spend. Wire in measurement so every run's cost is visible and attributable.
  3. Add estimation and caps. Pre-run estimates plus hard stops, so spend is approved and bounded.
  4. Hand off the controls. A dashboard and runbook so your team governs cost without me in the loop.
Real work, not a skills list
Proof

I built Runcap, an open-source tool that estimates a run's cost up front and hard-stops it at a cap, with delta-encoding that cut a real call from 1,186 to 737 tokens losslessly. See Runcap →

The arithmetic, your numbers

If cost-aware routing trims even 25% off a $4,000/month AI bill, that is $12,000 a year back - and a single prevented runaway run can pay for the whole engagement on its own.

Tell me where the bill scares you

Send me your current AI spend shape and the run you are most afraid will spike. Within 24 hours you get a free written teardown of it - what I would build, what it would take, and a fixed price - or a straight no.

Get my free teardown →
Cost-control builds typically $1,500 - 5,000 CAD ยท single payment after the audit document is delivered