AXIOM
AI Engineering Sandbox

From Concept to Production

A complete AI engineering practice sandbox — process flows, interactive model chains, hands-on code, and a comprehensive 5-day course reference guide grounded in real production patterns.

Open AI Studio Course Guide AI Concept Guide
End-to-End Process

AI Agent Engineering — Full Lifecycle

10 stages from goal definition to production monitoring — click any stage to practice in AI Studio

1
Define Goal
Requirements, success criteria, quality rubric
2
Select Model
Benchmark on your task; match tier to importance
3
Build Knowledge
RAG pipeline, vector store, embeddings
4
Design Tools
MCP servers, API wrappers, function schemas
5
Agent Loop
ReAct: Thought → Action → Observation
10
Deploy & Scale
Canary rollout, CI/CD gates, observability
9
Guardrails
Input/output filters, safety classifiers
8
Evaluate
LLM-as-Judge, Golden Set, trajectory review
7
Orchestrate
Multi-agent: Coordinator, Supervisor, A2A
6
Add Memory
Sessions, context engineering, memory ETL
1. Define Goal
2. Select Model
3. Build Knowledge
4. Design Tools
5. Agent Loop
6. Add Memory
7. Orchestrate
8. Evaluate
9. Guardrails
10. Deploy & Scale