Build Your First Software Factory Execution Harness

Oct 1, Reserve a seat
Free to read

Prompt Engineering Crash Course

Zero-shot won't cut it. Learn the advanced techniques that actually ship: few-shot extraction, chain-of-thought reasoning, ReAct agents, and prompt evaluation arrays, all with real Python code.

Start readingPreview curriculum

Still deciding? Ask first.

Message a mentor about fit, prerequisites, or where to start. Replies come on WhatsApp, usually within a day.

  • Curriculum fit, prerequisites, or where to start
  • Honest answer, no pressure to enroll

Taught by an engineer who has shipped this

  • ISO 27001

    Led the engineering work behind the certification of a regulated EU platform.

  • Series A platform

    Architected the case-management product that became the business a €11.6M round was raised on.

  • 3x faster deploys

    Cut time-to-deploy by migrating to Kubernetes on GCP with deploy-on-merge.

Zero-shot won't cut it in production. Learn the techniques that actually ship: few-shot examples, chain-of-thought reasoning, ReAct agents, and prompt optimization, all with real Python code, not toy demos.

The prompting techniques senior AI engineers use daily, and most tutorials skip.

What you'll ship

Real projects, not toy demos.

  • Write prompts that return reliable, structured outputs, not random noise
  • Apply the techniques senior AI engineers actually use in production
  • Build chain-of-thought pipelines for multi-step problem solving
  • Design reusable prompt templates you can drop into any project
  • Create a ReAct agent that reasons through problems and takes action

What you'll learn

You finish able to:

  • Write prompts that return structured, reliable outputs every time
  • Apply few-shot, chain-of-thought, and self-consistency techniques
  • Build reusable prompt templates for any LLM provider
  • Design a ReAct agent that reasons and takes action autonomously
  • Optimize prompts systematically instead of guessing

Curriculum

From Zero-shot to Production Prompts.

  1. 01

    Prompt foundations

    Learn the core building blocks of effective prompts: structure, clarity, roles, and data separation.

  2. 02

    Core techniques

    Master few-shot prompting, chain-of-thought reasoning, self-consistency, and prompt chaining.

  3. 03

    Advanced patterns

    Tackle iterative refinement, guardrails, and meta-prompting for production-grade prompt systems.

  4. 04

    Agentic prompting

    Build agent-like systems with ReAct prompting, multi-turn conversations, and evaluation pipelines.

Who it's for

Is this for you?

Software engineers

who want to move beyond basic ChatGPT usage and build reliable AI features

Backend developers

integrating LLMs into production systems and tired of unpredictable outputs

AI-curious engineers

who learn best by writing code, not just watching theory lectures

FAQ

Common questions.

  • Do I need to know Python?

    Yes, basic Python knowledge is required. If you are new to Python, take the Python for GenAI Beginners course first.

  • Which LLM provider do I need?

    We use LiteLLM so you can use any provider: OpenAI, Anthropic, Google AI Studio, or others. A free Google AI Studio key works fine.

  • Is this just prompt tips I can find on Twitter?

    No. This course covers production patterns like structured outputs, chain-of-thought pipelines, and ReAct agents, with working Python code, not one-liners.

  • How long does it take to complete?

    About 6 hours if you work through the exercises. You can go at your own pace.