AI Coding Tool Costs: Measure Cost per Merged PR

Count the work, not just the invoice

Include model charges where they apply, but don't stop there. Track time spent recovering from failed attempts, reviewing generated changes, and waiting when a person is actually blocked. If a request "only takes two minutes" but no one saves time because of cleanup and rework, "two minutes saved" isn't a real business outcome.

Be picky about wait time. A server that responds in 40 seconds doesn't automatically mean 40 seconds of labor is gone. Only treat it as labor-relevant time when someone can't move to another task - or agree on a different way to value that delay. Otherwise you end up paying for idle machine time and calling it engineering effort.

For self-hosted lanes, include operating costs: hosting, upgrades, monitoring, security work, and the time your team spends owning incidents. Allocate recurring costs across the work the lane supports. For paid seats, include seat or usage costs and any required administration. And use the same cost boundaries across options; comparing a fully loaded self-hosted lane to a vendor's usage fee alone is just not an apples-to-apples test.

Keep sunk costs out of the decision

Past setup time is a sunk cost. It might explain why you ended up with a system in the first place, but it shouldn't decide what's cheaper going forward. If setup work is ongoing - like rebuilding deployments per environment - count the expected future work. If it isn't, don't use old hours as a justification.

Developer satisfaction matters, but treat it as its own input unless you can measure it cleanly. One decent signal is whether people keep using the lane after the pilot excitement fades. Don't convert vibes into dollars and then pretend it's measured.

And one more thing: the scorecard isn't "objective truth." It's a set of shared assumptions. Its job is to make debate possible using the same numbers, not to make the spreadsheet feel magically authoritative.

Keep the data comparable

Use representative tasks from the same mix of work where possible. Don't compare a lane that only handled routine tests with another lane used mainly for migrations and unfamiliar code. If you expect task type or difficulty to change results, label it. Also, don't make logging so heavy that engineers start gaming around it. You're aiming for a decision-grade sample, not perfect observability.

A minimal aggregation can calculate variable cost per merged PR:

import collections
import json
LOADED_PER_MIN = 85 / 60  # Replace with your team's loaded hourly cost
lanes = collections.defaultdict(lambda: {
"merged": 0,
"model_cost": 0.0,
"labor_minutes": 0.0,
})
with open("ledger.jsonl") as ledger:
for line in ledger:
if not line.strip():
continue
row = json.loads(line)
lane = lanes[row["lane"]]
lane["merged"] += int(row["merged"])
lane["model_cost"] += row.get("model_cost_usd") or 0
minutes = (
(row.get("retry_min") or 0)
+ (row.get("review_min") or 0)
+ (row.get("blocked_wait_min") or 0)
)
lane["labor_minutes"] += minutes
for name, data in lanes.items():
if data["merged"] == 0:
continue
total = data["model_cost"] + data["labor_minutes"] * LOADED_PER_MIN
print(name, round(total / data["merged"], 2))

This is a starting point, not a full accounting system. It excludes fixed hosting, seat fees, and maintenance because those belong in the fixed-cost part of the break-even math below. It also assumes the time fields were measured consistently. If one lane includes all review time while another lane only counts AI-attributable review time, your result will be biased before the script even runs.

A repo ledger beats a dashboard owned by a single person (or vendor) because the raw evidence stays reviewable when pricing changes, a tool gets swapped out, or the original pilot owner moves on. Dashboards can be useful later, but they shouldn't be required to collect the data.

Worked example: make assumptions visible

Say the illustrative inputs are:

• Hosting or seat cost: $180 per month
• Initial setup: 30 hours, amortized over 12 months, or 2.5 hours per month
• Ongoing maintenance: 6 hours per month
• Loaded engineering rate: $85 per hour
• Current free lane: $4.10 per merged PR in variable cost
• Alternative hosted lane: $0.90 per merged PR in variable cost

The fixed-equivalent monthly cost is $180 + (2.5 + 6) × $85, or $902.50. The alternative saves $4.10 − $0.90 = $3.20 per PR in variable cost. Break-even is $902.50 ÷ $3.20, or about 282 merged PRs per month.

These numbers are just an example. The per-PR figures need to use the same accounting rules for both lanes. If the $4.10 includes review labor and the $0.90 is only a model charge, the comparison is broken.

Do a sensitivity analysis so you can see what moves the decision. For example:

The key point isn't the precision of any one row. It's that maintenance and the measured cost of the current lane can swing the decision more than the list price. Measure the sensitive inputs before negotiating around a number that doesn't match your workflow.

Treat free allowances as pilot runway

A free quota helps you collect evidence, but it's not a permanent budget line. Estimate runway from your usage:

Runway in months = allowance ÷ (median tokens per task × tasks per month)

Multiply the denominator by the number of people sharing the allowance. For example, with 9,000 tokens per task, 25 tasks per developer per week, and four developers, monthly usage is roughly 3.87 million tokens (using an average month of 4.3 weeks). A 10-million-token allowance would last about 2.6 months under those assumptions.

This calculation depends heavily on the quota and usage assumptions. Check the current terms directly before relying on them. Allowances change, screenshots go stale, and a "free server option" doesn't tell you who owns security, availability, backups, or incident response.

Use three gates

1. Gate 1: Instrument, days 0-3. Pick one person to own the pilot and ledger. Agree on lane definitions, labor assumptions, and what counts as blocked time. Collect at least 20 merged PRs per lane before you treat the comparison as meaningful. If the lanes cover very different task mixes, collect comparable examples or label the difference.
2. Gate 2: Compare, around day 14. Calculate variable cost per merged PR, fixed-equivalent monthly cost, and break-even volume. Compare it to your actual monthly volume. A practical rule: stick with the free lane when volume is below half the break-even point, re-quote or re-test the hosted option when volume is above twice the break-even point, and extend once when it's in the middle. Write down the reasoning before extending.
3. Gate 3: Verify and exit, by day 30. Re-check pricing, quotas, hosting terms, and data handling. Publish the ledger and the decision, including the assumptions that could flip it. End the pilot on its expiry date unless someone explicitly approves an extension. No silent renewal by inertia.

Choose for fit, not feature count

This table is about fit, not a universal ranking. Self-hosted gives you control over parts of the stack, but it also means accepting operational responsibility. Paid seats hand off some infrastructure work to a vendor, but you still need to assess data handling and service terms. Free lanes can be a good control arm, but "free" doesn't answer whether the lane is suitable for real production work.

This approach doesn't work well if your team can't log work for a couple weeks, the data path isn't verified for confidential code, or your monthly volume is so low that a few unusual tasks dominate the average. And it can't undo a decision already made for political or contractual reasons. In those cases, state the constraint directly rather than presenting a shaky cost estimate as evidence.

Disclosure: MonkeyCode is the open-source project referenced in the original example, and this article was prepared as part of its product outreach. Its free model access and server option can act as a zero-cost control arm, as long as you review the current terms and confirm the data path. Check the project's current documentation before relying on either option.

One more rule applies no matter which tools you test: before signing or switching, write down the single variable most likely to reverse your choice - review minutes, maintenance hours, monthly volume, or allowance size - and measure it first. A small, honest ledger beats a feature comparison that ignores the work your engineers actually do.