AI for Founders
Leverage generative AI as your primary leverage.
Lessons
Expand any topic for concept, action steps, and pro tips.
Concept
Prompt Engineering Masterclass: treat models as probabilistic teammates. Reliability comes from evals, constraints, retrieval, and human checkpoints — not vibes.
Why it matters
AI features that cannot be measured get worse in production. Founders who instrument quality ship durable leverage.
Action steps
- 1Specify the user job and success criteria before picking a model.
- 2Build a golden set of 20-50 eval examples for the critical path.
- 3Start with the simplest stack (prompt + tools) before multi-agent complexity.
- 4Log prompts, outputs, latency, and cost per successful task.
- 5Add guardrails for PII, jailbreaks, and hallucinated actions that spend money.
- 6Ship to a narrow cohort; compare against a non-AI baseline.
Done when
You have evals green on the golden set and a production path with cost caps.
Metrics
- · Task success rate
- · Cost per successful task
- · Latency p95
- · Human override rate
Anti-patterns
- · Agents without evals
- · Putting secrets in prompts
- · Ignoring cost until the bill arrives
If you cannot define correct, you cannot ship AI. Write the rubric first.
Stage quiz
AI for founders check
5 questions · pass at 70%
1.Before multi-agent systems, you should usually have:
2.RAG is mainly used to:
3.A production AI feature should track:
4.High-risk AI actions (spend money, send email, change data) should:
5.Best early AI product strategy:
Answer all questions to score.