AI and LLMsComing soon
AI Agents & Agentic AI
Beyond a single prompt and response: planning loops, multi-agent orchestration, memory, and the guardrails that keep an autonomous agent from running away with your production system.
What you'll actually do
- Build a planning loop that reasons over multiple steps
- Manage state and memory across an agent's turns
- Orchestrate multiple agents that delegate to each other
- Design tool schemas an agent can't misuse
- Add guardrails and human-in-the-loop checkpoints
- Evaluate an agentic system, not just a single response
Tools and topics covered
Agent ArchitecturesPlanningMulti-Agent SystemsTool DesignGuardrailsEvaluation
Why it matters
An agent loop without a hard stop condition doesn't stop on its own.
Multi-agent systems fail in ways a single-agent system never does: agents can loop, contradict each other, or delegate forever.
Giving an agent a tool is also giving it a way to misuse that tool.
Career Path Edition
A working multi-step autonomous agent with real guardrails, tested against failure cases, not just the happy path demo.
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