Learn AI roadmap (simplified): what to learn first, what to build, and how to stay consistent
A simple roadmap that works
Most people fail by jumping between tutorials. The win is consistency and projects.
Phase 1: Foundations (2–4 weeks)
- Basic Python
- APIs + JSON
- Git basics
Phase 2: LLM basics (2–3 weeks)
- Prompting patterns
- Evaluation mindset (don’t trust outputs blindly)
- Safety basics (PII, secrets)
Phase 3: Build (4–8 weeks)
Projects that prove skill:
- A small RAG app over docs
- A workflow tool that calls APIs
- A content pipeline (draft → edit → publish)
Phase 4: Specialize (ongoing)
Pick a domain:
- SEO automation
- security tooling
- customer support
- dev productivity
How to stay consistent
- 30 minutes daily beats 5 hours once.
- Build something that helps you or your team.
Roadmap for Laravel developers learning AI (2026)
If you already ship PHP apps, learn AI in this order:
- Prompting + evaluation — write tests for LLM outputs like you test code
- Embeddings + RAG — add document search to your own codebase (Graphify, Laravel Scout, etc.)
- Tool calling / MCP — let agents call your APIs with Sanctum abilities and audit logs
- Fine-tuning — only after you have data; most apps never need it
Build projects that teach
| Project | Skill |
|---|---|
| Markdown blog assistant | Prompting + editing |
| Internal docs Q&A | RAG |
MCP content_upsert publisher |
Tools + auth |
| Queue summarizer job | Laravel Horizon + APIs |
FAQ
Do I need a math PhD?
No. You need statistics intuition and debugging discipline.
Local vs API models?
Start with APIs (OpenAI, Anthropic). Add Ollama when privacy or cost forces local inference.
How does this tie to Aviwebsquad?
This site documents each layer as I implement it—Boost, MCP, Graphify—not as abstract hype.