Added output Selected
Same team. More output.
Estimate the engineering capacity an AI rollout creates, what AI tools and annual training cost to run, how long a cohort rollout takes, and when it pays back. Use it to set a target, test a business case, or check a training proposal.
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One flat budget for all upfront program, setup, rollout, and employee time costs. $500,000 is an editable planning assumption.
Cumulative trained engineers. The whole team is trained from Month 3. Each trained engineer contributes the selected gain; untrained engineers contribute no added benefit.
6 months with no modeled productivity benefits. Everyone reaches the selected productivity gain in month 7. This period is an editable planning assumption.
Total team included in the model.
Blended salary, benefits, taxes, and overhead. The $200,000 baseline is a planning assumption. [12]
The target gain once trained. With three-wave training, this applies only to trained engineers in each month. The 30% baseline is a planning assumption. [1]
All subscriptions and additional billed usage; count each charge once. The $350 baseline is a planning assumption. [9] [10]
Recurring training budget, spread evenly across months.
Payroll freed after costs
The same productivity gain can create more output or reduce the payroll needed for today’s output.
Same team. More output.
Same output. Less payroll.
Both figures are before AI and training costs. The team needed for the same output is rounded up to whole engineers. Added output is capacity value. Payroll freed becomes cash savings when staffing or planned hiring decreases. Recurring costs remain budgeted for the full original team.
Benefits follow the selected rollout timing. Payback is the first month cumulative value covers all costs incurred so far.
Annual net run-rate excludes the one-time investment. The cumulative chart and tables include it. Ongoing costs stay flat; productivity follows the selected benefit timing and stays at the target gain after rollout. No discount rate or hiring changes are modeled.
Hover or focus a numbered source for a preview. Select it to jump to and highlight its reference below. The source links open the original publications.
| Published figure | Context | Source |
|---|---|---|
| +10–15% | Typical gain from AI coding tool rollouts. 25–30% where teams redesign the end-to-end process around the tools. | [1] Bain Technology ReportSep 2025 |
| $150–250/mo | Average Claude Code cost per developer across enterprise deployments, about $13 per active day. 90% of users stay under $30 per active day. | [9] Claude Code docs2026 |
| $500–2,000/mo | Uber's reported spend per engineer after Claude Code adoption rose from 32% to 84%. It used its 2026 AI budget by April. | [10] CFO Dive2026 |
| $136K → ~$195K | Median US software developer wage, and loaded cost before overhead given benefits at 30% of compensation. | [12] BLS wages · BLS benefits2025–2026 |
The $200,000 loaded cost, 30% productivity gain, and $350 monthly AI cost are editable planning assumptions informed by this evidence. The investment, rollout timing, and annual training budget are planning inputs.