AI Developer Path Map

This is the public path from safe AI use to credible AI developer practice. Start with the manual AI-chat workflow, then add developer tools one layer at a time.

1. Safe AI chat foundation

Use ChatGPT, Claude, Gemini, or similar for non-sensitive drafts, explanations, checks, and learning loops. Learn no-secrets habits and PASS/HOLD review.

2. Source of truth

Keep current goals, examples, tool choices, constraints, red lines, and learning logs in one place so AI does not guess.

3. Developer workspace

Move into folders, files, an editor, Terminal basics, Git history, private repos, README files, and testable project structure.

4. Code foundations

Learn enough HTML, CSS, JavaScript/TypeScript, Python, JSON, HTTP, debugging, and tests to understand what AI helps you build.

5. AI-assisted building

Use AI to plan, explain, write, refactor, and review code while you inspect diffs, run tests, and keep owner approval for risky actions.

6. AI app patterns

Build small features with model calls, structured outputs, embeddings/RAG, tool calling, eval examples, logs, cost limits, and fallback behavior.

7. Owner-gated agents

Build specialist helpers and coordinators only with least privilege, step limits, logs, PASS/HOLD gates, and human approval before external side effects.

8. Portfolio capstone

Turn one real safe workflow into a small AI app with README, tests/evals, safety notes, demo evidence, and known limits.

The rule

Do not jump layers to feel advanced. Prove each layer with one useful project.

Important boundary

DWAI shares practical AI and AI-developer-path resources for thinking, drafting, organizing, researching, reviewing, learning, coding, debugging, testing, building small AI apps, and shipping owner-controlled projects. This is not therapy, counselling, diagnosis, ADHD or addiction treatment, medical advice, legal advice, financial advice, tax advice, crisis support, regulated professional advice, or a guarantee of clarity, productivity, income, saved time, business results, jobs, clients, or any personal outcome. AI outputs are drafts. The owner approves risky action.

How to use this download

Use this resource for: The path from safe AI chat to setup, code, Git, APIs, AI app patterns, tests, deployment checks, and portfolio projects.

If you are new, start with the 20-Minute AI Starter Workflow, then use the full book and workbook as your main path.
Keep the Owner Approval Checklist nearby before acting on anything risky.
Use PDF for reading/printing, HTML for browser reading, and Markdown/TXT for AI study sources where available.
Treat AI outputs as drafts. Use PASS / HOLD before money, accounts, public posts, deletes, deploys, customer/private data, code changes, or regulated claims.

Optional: learn it with NotebookLM

NotebookLM is a third-party Google tool. If you use it, upload only public DWAI downloads or copied public resource URLs. Do not upload private notes, secrets, customer data, account screenshots, or completed workbook pages.

Create or open a NotebookLM notebook.
Add the public DWAI PDFs, Markdown files, or public resource page URLs as sources.
Ask NotebookLM: "Using only these DWAI sources, explain the path in plain English, make me a 7-day study plan, quiz me, and flag anything involving secrets, accounts, money, public posting, deletion, deployment, customer or private data, code changes, or regulated claims as HOLD."
If your NotebookLM account has Video Overview, generate one for a video-style walkthrough. If Video Overview is not available, use Audio Overview, briefing docs, study guides, or source-grounded Q&A instead.
Check NotebookLM's answer against the source citations before acting. AI study aids are drafts, not owner approval.

Do not upload completed workbook pages, context cards, customer/private data, private business records, passwords, API keys, 2FA or recovery codes, medical, legal, financial, tax, crisis, or sensitive personal details unless you have intentionally replaced them with placeholders and accept the tool's data terms.