Lab 11 — Unit-Economics Cost Calculator

Runs fully offline (Python 3 only). Model the cost ladder and prove (or fix) your margin — the business-side skill every senior engineer/CTO needs. Concepts: Phase 15.05, cheatsheet 18.

Goal

Compute cost per request → task → resolved task → user → gross margin, and quantify the impact of routing + caching levers.

Files

lab-11-cost-calculator/
  README.md
  cost_calc.py     ← runnable: cost ladder + margin + routing/caching levers

Run

python3 cost_calc.py
# a chatty agent with retries on an expensive model
python3 cost_calc.py --in-tok 6000 --out-tok 1500 --in-price 3 --out-price 15 \
    --requests-per-task 4 --success-rate 0.6 --tasks-per-user 300 --price-per-user 99

Exercises

  1. Negative margin: find inputs (expensive model, low success rate, high usage) that produce a negative gross margin. Then fix it with the levers.
  2. Resolved-task cost: show how a low success rate inflates cost per resolved task vs cost per request.
  3. Levers: quantify the margin improvement from 80% routing to a 0.1× model + 50% cache hit.
  4. Break-even (stretch): add a self-host model (fixed GPU $/month + ~0 marginal) and find the monthly volume where it beats the API.
  5. Pricing: given a target 75% margin, solve for the minimum price per user.

Deliverables

  • A cost ladder for your product idea (real token counts + prices).
  • A before/after-levers margin comparison.
  • A pricing recommendation (to-margin) + a usage cap to prevent power-user blowout.

Why it matters (interview)

"Every request costs money — here's my cost per resolved task and how I engineer 75% margin with routing/caching" is exactly what platform/CTO interviews probe (interview-prep 09). Pairs with the cost-model template.