Thread by @dfinke

I just completed three Microsoft AI Agent modules:

• Memory, State, and Evaluation
• Multi-Agent Systems and Orchestration
• Governance, Guardrails, and Operations

One thing stood out.

We've spent years talking about prompts.

The real challenge is systems.

🧵

Memory = what the agent knows.

State = where the agent is.

Evaluation = how you know it succeeded.

A smart model without these is often just an impressive demo.

Then comes orchestration.

One giant agent is not always the answer.

Specialized agents working together can outperform a single agent trying to do everything.

Coordination becomes a first-class concern.

And then reality shows up.

Governance.
Guardrails.
Monitoring.
Auditability.

Building an agent is easy.

Operating one responsibly at scale is the hard part.

The industry spent years focused on:

"How do I write a better prompt?"

The next phase looks more like:

"How do I engineer a reliable AI system?"

Different problem.
Different skill set.

My takeaway:

We're moving from prompt engineering to system engineering.

Memory.
State.
Orchestration.
Governance.
Evaluation.

That's where things start getting interesting.

Modules:

Memory, State, and Evaluation
learn.microsoft.com/en-us/training…

Multi-Agent Systems and Orchestration
learn.microsoft.com/en-us/training…

Governance, Guardrails, and Operations
learn.microsoft.com/en-us/training…

#AI #Agents #AgenticAI #MCP #Copilot #MicrosoftLearn