Free
Agent Deployment
Every deployment path the AISL workshops have actually taken an agent through — FastAPI on Railway, AWS Lambda, Cloudflare Workers, Vercel, and vLLM on rented GPUs.
Topics
Topics
Topic guides on AI engineering, built from every AISL course, workshop, and article.
Topics turn the AISL material — courses, workshops, articles — into topic-oriented guides. Each page synthesizes what the material collectively teaches about one topic and links the canonical pages behind it. Start with the role, follow the roadmap, or jump straight to a topic.
Start here
- AI Engineering — the role, defined from experience and from job-description data now tracked monthly across 6,964 postings
- AI Engineering Roadmap — the route through all of the material, stage by stage
Foundations
- Python for AI — the course that closes the Python gap
- LLM APIs — one API shape, every provider
- Prompt Engineering — prompts as an engineering surface, and the handoff to schemas
- Structured Output — JSON instead of prose
- Vector Search — TF-IDF to embeddings, from first principles to SQLite and Turso
Building AI systems
- RAG — the classic pipeline, where it breaks, agentic search
- Agents — the loop, the frameworks, durable execution
- Model Context Protocol — tools behind a server any client can reach
- Building Coding Agents — tools, templates, skills, slash commands
- Agentic Development Environments — the remote box, persistent sessions, and autonomy boundaries agents need
- AI Coding Tools — the tool landscape and the daily workflow
Production
- Agent Deployment — Railway, Lambda, Cloudflare, Vercel, vLLM on rented GPUs
- Guardrails — input and output checks, SDK-native and DIY
- Evaluation and Monitoring — tests, judges, synthetic data, observability
Projects and career
- Portfolio Projects — the ten showcase projects, read as evidence for the selection framework
- AI Engineering Career — portfolio, CV, brand, interviews
- Take-Home Assignments — what the market assigns, how it grades, and a real assignment solved live
- Interview Prep — the hiring-manager hour and the theory question bank
The material behind the topics
Every topic page cites the canonical pages on aishippinglabs.com it is built from. Coverage today: 25 workshops, 3 courses, 22 articles, 10 showcase projects, and the published interview question sets — plus the job-market research from the AI Engineering Field Guide that grounds the career pages. Start with AI Engineering for the map, or jump straight to the topic that matches what you are building.
All topics
Free
Agentic Development Environments
Where coding agents run: a hardened remote box, sessions that survive disconnects, autonomy boundaries, and access from every device you own.
Free
Agents
What an agent is — a loop around tool calls — and how the AISL material builds, extends, and hardens them across frameworks, protocols, and modalities.
Free
AI Coding Tools
The tool landscape — chat apps, IDE assistants, project bootstrappers, agents — and how AISL members actually work with them day to day.
Free
AI Engineering
What an AI engineer does, how the role differs from ML engineering and data science, and how the AISL courses, workshops, and articles fit together.
Free
AI Engineering Career
Portfolio projects, CV tailoring, personal brand, and interviews — the career mechanics the AISL workshops and articles cover, aimed at AI engineering roles.
Free
AI Engineering Roadmap
A learning route through the AISL material: what to learn first, which course or workshop covers it, and what to build along the way.
Free
Building Coding Agents
How to build the agents that write code: tool sets, templates, skills, slash commands, and the remote environments they run in.
Free
Evaluation and Monitoring
Testing agents, evaluating them with judges and synthetic data, monitoring them in production, and paying less for all of it.
Free
Guardrails
Input and output guardrails for AI agents: the SDK-native way, the framework-agnostic way, and what streaming and cancellation add.
Free
Interview Prep
What AI engineering interviews actually test — the hiring-manager walkthrough, the theory question bank, and the AISL material that doubles as rehearsal.
Free
LLM APIs and Providers
One API shape, many providers — OpenAI, Anthropic, Gemini, Bedrock, Groq, Grok, Z.AI, Ollama — and the tool-calling layer that makes them interchangeable.
Free
Model Context Protocol
MCP — moving agent tools out of the notebook and behind a server any client can reach: FastMCP, stdio and SSE transports, Cursor and VS Code.
Free
Portfolio Projects
The AISL showcase projects — ten builds from reference to-do agent to hospital platform — read as evidence for the portfolio framework.
Free
Prompt Engineering
Prompts as the programming interface of AI work: system prompts, instruction strengthening, and the point where a prompt hands off to a schema.
Free
Python for AI
The Python foundation the rest of the AISL material assumes: the Python for AI Engineering course, built around one real project.
Free
RAG
Retrieval-augmented generation across the AISL material: the classic pipeline, where it breaks, and how agentic search fixes it.
Free
Structured Output
Getting JSON instead of prose from an LLM — Pydantic schemas, where prompting stops being enough, and streaming structured output to the UI.
Free
Take-Home Assignments
What AI engineering take-homes ask for, how companies grade them, what gets offers — and a real assignment solved live, end to end.
Free
Vector Search
Search from first principles — TF-IDF, boosting, embeddings — and the small-technology versions the AISL workshops actually deploy: SQLite, Turso, Cloudflare Vectorize.
Keep building with a membership
Every topic guide is free to read. Members get structured courses, live workshops, and feedback on real projects.