AI Engineering
Platforms:
claudeopenaigeminim365-copilot
What AI Engineering Is
Section titled “What AI Engineering Is”AI engineering is the discipline of designing, building, and optimizing systems that use AI models effectively. It goes beyond writing prompts — it’s about architecting the entire information environment that shapes how AI behaves.
The Agentic Building Blocks describe what the components of an AI workflow are. AI engineering describes how to work with those components — the practices, techniques, and principles that make the difference between a demo and a production system.
Practices
Section titled “Practices”| Practice | What It Covers | Status |
|---|---|---|
| Context Engineering | Designing and optimizing the entire context window — system prompts, instructions, tools, memory, and state | Available |
| Evaluation | Measuring AI system quality, building test suites, comparing outputs | Coming soon |
| Observability | Monitoring AI systems in production — tracing, logging, debugging agent behavior | Coming soon |
How AI Engineering Relates to Building Blocks
Section titled “How AI Engineering Relates to Building Blocks”The building blocks are your vocabulary — prompts, context, projects, skills, agents, MCP. AI engineering is the craft of assembling them well.
A useful analogy: the building blocks are like construction materials (wood, steel, glass). AI engineering is architecture and structural engineering — the discipline of designing with those materials so the result actually works.
Related
Section titled “Related”- Agentic Building Blocks — the components that AI engineering practices operate on
- Patterns — reusable approaches across building blocks
- AI Use Cases — what teams build with these practices, organized by six primitives