Launching today
AI Economics Field Guides
Practical worksheets for AI costs, limits, and pricing
1 follower
Practical worksheets for AI costs, limits, and pricing
1 follower
Two free workbooks for teams building with AI. Survive the Launch helps founders model cost per useful task, launch spikes, free-tier exposure, heavy users, and agent budgets. Add AI. Keep Your Margins. helps established teams protect plan margins, design included usage, choose a value unit, and set pricing triggers. Each guide has 10 five-minute exercises and a readiness card. No signup. No catch. Just practical lessons learned the hard way.
Hi Product Hunt 👋
I made these field guides after seeing the same gap come up around AI products: teams can see a provider bill, but they often cannot say what one useful customer task costs, what a launch spike would expose, or when an “AI included” plan stops making economic sense.
I wanted something more useful than another pricing essay, so each guide is built around ten short decisions and a five-minute worksheet for each one.
There are two starting points:
🚀 Field Guide 01: Survive the launch is for founders and builders preparing a new AI product, free trial, cohort, or launch. It covers cost per useful task, success scenarios, free-tier budgets, heavy users, guardrails, context, model choice, agent budgets, and pricing triggers.
📈 Field Guide 02: Add AI. Keep your margins. is for established software teams adding AI to existing customers and plans. It covers feature P&L, plan margin, account attribution, hidden cross-subsidy, value units, included usage, guardrails, and packaging review triggers.
Both PDFs are free, vendor-neutral, and available without a signup. You can complete them with provider dashboards, logs, and a spreadsheet.
I’m still learning too. I’m offering a free 30-minute 1:1 to hear how teams are approaching AI pricing and to work through your answers together. There is no pitch. You can schedule it from the landing page if that would be useful.
I would especially value feedback on one question: Which AI economics decision is hardest for your team to make with confidence today?