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AI Agents Foundations

5 Labs · Foundations · Evaluation · Planning · Memory

Learn the agent/tool loop, evaluate recorded runs, manage explicit plans, then see how memory persists information across interactions.

Foundations → Evaluation → Planning → Memory

FOUNDATIONS

01Tool Calling
Guided
Watch the agent/tool loop: decide → call → observe → answer.
- Tool selection
- Observation
- Error recovery
15–20 min
Architecture · Guided Demo · Code
Open Lab →
01 Tool Calling
02Agent Loop
Guided
Build an application-owned loop that decides, acts, observes, and terminates safely.
- Agent state
- Termination
- Max turns
15–20 min
Architecture · Guided Demo · Code
Open Lab →
02 Agent Loop

EVALUATION

03Agent Evaluation
Guided
Score the recorded run: outcome, trajectory, interpretation, and cost stay separate.
- Outcome
- Trajectory
- Interpretation
15–20 min
Architecture · Guided Demo · Code
Open Lab →
03 Agent Evaluation

PLANNING

04Planning
Guided
Create a plan the runtime can track, execute, and revise — then stop honestly when it cannot complete.
- Plan state
- Revision
- Plan failure
15–20 min
Architecture · Guided Demo · Code
Open Lab →
04 Planning

MEMORY

05Memory
Guided
Store, retrieve, and use information across interactions — including miss and stale resolution.
- Store
- Retrieve
- Stale memory
15–20 min
Architecture · Guided Demo · Code
Open Lab →
05 Memory

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