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Interactive technical fluency training for non-engineers. 43 lessons, 11 modules, single HTML file. How software, data, and AI agents actually work.

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Technical Fluency for Non-Engineers

An interactive training app for non-engineers who need to work effectively with software teams. Built to teach the mental models behind modern software, AI products, and technical collaboration — without requiring anyone to learn to code.

Why I Built This

Most nontechnical professionals are told to “learn to code” when what they actually need is technical fluency: the ability to understand how software works, ask better questions, and contribute more effectively in product, strategy, and operational conversations. I built this app to make that fluency accessible in a compact, usable format.

Who This Is For

  • Product managers, designers, and business leaders who collaborate with engineers
  • Founders and operators building or directing technical products
  • Anyone who wants to understand how software gets built without learning to code

What You'll Learn

The training covers 43 lessons across 11 modules:

  1. What Software Actually Is — State, logic, and interface. Frontend vs backend. How web apps work. HTML, CSS, and JavaScript in plain English.
  2. How Software Gets Built — Git and GitHub. Dev, staging, and production environments. CI/CD and deployment. Unit, integration, and end-to-end testing.
  3. The Stuff That Makes It Hard — APIs. Databases and persistence. Permissions and edge cases. Technical debt.
  4. Data — The Real Foundation — SQL and relational databases. NoSQL and document stores. Data lakes, warehouses, and the analytics stack. Pipelines and ETL.
  5. Cloud & Infrastructure — What "the cloud" actually means. Servers, containers, and serverless. Scaling. Monitoring and uptime.
  6. Security & Privacy — Authentication vs authorization. Common vulnerabilities in plain English. Privacy and compliance.
  7. Product Management & Agile — Sprints and how teams actually work. Roadmaps, backlogs, and prioritization. User stories and acceptance criteria. The PM-engineering relationship.
  8. AI Products Are Still Software — Probabilistic models vs deterministic systems. Prompting, workflows, and agents. MCPs. RAG, structured output, and grounding. Why demos lie.
  9. Inside AI Agents — What people mean by "agent". The three layers: brain, menu, hands. The agent loop. Tool routing and how agents fail. Vocabulary lock-in.
  10. How to Talk to Technical People — Good questions vs bad questions. Signals that build credibility. Signals that destroy credibility. Knowing when you're out of your depth.
  11. Putting It All Together — How everything connects. Where to go from here.

Features

  • Dark editorial theme designed for focused reading
  • Sidebar navigation with module and lesson progress tracking
  • Mark-complete per lesson with progress saved to localStorage
  • Inline SVG diagrams for key concepts
  • Keyboard navigation (arrow keys, j/k, spacebar)
  • Mobile responsive with hamburger menu
  • Single HTML file — no build step, no dependencies

Live Site

greg-oyan.github.io/tech-fluency

About

Interactive technical fluency training for non-engineers. 43 lessons, 11 modules, single HTML file. How software, data, and AI agents actually work.

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