The AI Consultant Handbook
A working reference for the job of turning AI from a demo into something a client pays for: the technology, the delivery, and the business around it.
PDF · v1.0.0
Forty-six chapters across ten parts, taking you from what a model actually is to what to charge for one. It covers the fundamentals (machine learning, tokens, open weights against proprietary, neural networks), the build (Next.js, Vercel, Supabase, working with open-source repositories), chatbots end to end (system prompts, memory, RAG, tools, guardrails, monitoring and their unit economics), agents and automation (webhooks, APIs, MCP, cron, endpoints), and the business (the first consultation, proposals that get a yes, productising into recurring revenue, and running a one-person automation agency). Every worked example carries real arithmetic in CAD rather than a round number, and the appendices add a glossary, a prompt library and six operational checklists.
What you get
- 46 chapters across 10 parts, roughly 380 pages
- Worked economics: token cost, retainers, margin, MRR
- A glossary, a prompt library and six checklists
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The first 11 pages, free: the cover, the opening part and the whole of chapter one. Enough to judge the typography and the tone before you pay for the rest.
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