Master AI Prompt Engineering
Structured Claude, ChatGPT, and Gemini prompt engineering training for AI-assisted software development — production-grade prompts for coding, testing, automation, and enterprise architecture.
AI Prompt Engineering Training Programs
Four structured programs covering the full spectrum of AI-assisted software development — from your first Claude prompt to production microservice modernization.
AI Prompt Engineering Learning Roadmap
A four-stage path from your first Claude prompt to shipping AI-assisted code with the same rigor as any production change — including DDD, CQRS, and STRIDE threat modeling.
Foundations
LLMs, Claude, prompt fundamentals, effective prompt design.
Software Development
APIs, schemas, UI, debugging, refactoring — at intermediate and advanced depth.
Existing Code
Codebase analysis, scientific debugging, incident management, safe modification.
Production-Ready
STRIDE threat models, 7 quality gates, prompt libraries, team-scale governance.
Why this matters — six lenses
Why Prompt Engineering Matters
LLMs generate plausible continuations — not facts. The quality of the output is bounded by the precision of the prompt. Engineering prompts is the highest-leverage skill in AI-assisted work.
AI in Software Development
Used well, Claude shortens the time between intent and a first working draft. Used badly, it ships invented APIs and anemic models. The difference is prompt discipline.
AI Productivity
Reusable prompt libraries, structured templates, and self-critique loops turn one engineer into a force-multiplier across reviews, docs, and routine work.
AI for Testing
Property tests, mutation testing, contract testing, and load scenarios become accessible — generated, reviewed, and committed alongside the code they verify.
AI for Automation
Multi-step prompt chains automate triage, enrichment, routing, and reporting workflows that previously required custom scripts.
AI for Business
From ADR drafts to SEV1 post-mortems, AI accelerates the structured writing every engineering organisation depends on.
AI Tools Covered: Claude, ChatGPT, Gemini & More
The AI coding and productivity platforms covered in this curriculum — prompt engineering techniques transfer across all of them.
Frequently asked
Is this platform tied to a single AI vendor?
The curriculum was authored against Claude and uses it as the primary teaching surface, but the prompt techniques transfer cleanly to ChatGPT and Gemini. Each program is model-agnostic at the technique level.
Do I need to know .NET / C# to follow along?
Foundations (Program 1) is language-agnostic. The Advanced programs and the 10-Day Intensive use a .NET 8 reference stack (DDD, CQRS+MediatR, EF Core, Dapper, Stryker.NET, FsCheck, YARP) — the prompt patterns transfer to other stacks but the named prompts are calibrated to .NET.
How is progress tracked?
Per-lesson progress is stored against your account. The dashboard shows continue-learning, completion percentages, prompt library bookmarks, quiz scores, and certificates.
Can my team self-host this?
Yes. Next.js + PostgreSQL deploys cleanly to Vercel, AWS, Azure, or any Node-capable runtime. The schema and seed are reproducible from source.
Where does the content come from?
The curriculum is derived from the Anthropic Claude Prompt Engineering training corpus (Primary Doc, Doc 1 New-Project Advanced, Doc 2 Existing-Project Advanced, plus the 10-Day Plan and role guides). The Prompt Library preserves the doc/section reference for every named prompt.