A good AI Agent has less AI than a bad one

Say that three times fast... it's basically a tongue twister.
Let me explain:

A few weeks ago, a CIO looked at me like I was running a scam. I'd just told him his team didn't need AI for a task: it was a logical process, no decisions to make, nothing to invent.

So here's the clarification:

An AI Agent is built from three components:
🔌 Connectors: what it can access and use
🧠 Skills: what it knows how to do
💾 Memory: what it remembers and can draw on

AI's real job sits on top of those three: understanding what needs to happen, whether it knows how, where to find the information, and what from the past is worth pulling in.

Which brings me to my point 🥁

Right now, a lot of AI providers put AI everywhere. Less engineering, less tuning
BUT more mistakes, and users who walk away thinking the agent is dumb.

A genuinely impactful agent looks different:
✅ Skills that are well-trained and specific
✅ Memory that's rich enough to actually leverage
✅ Only the connectors it truly needs (extra ones just add confusion)

Breaking it down further:
🔌 Connectors: A well-built integration, solid API or clean RPA, will always outperform an improvised one.
🧠 Skills: No AI is often the smartest choice. It avoids guesswork and approximate answers.
💾 Memory: No AI here either. Just real historical data = your best guardrail against hallucination.

So if you're building an AI Agent, or evaluating one to buy:
more AI isn't the goal.
Smarter AI is. That's what every expert in this space is trying to get people to understand right now.

Welcome to my self-promoted technical week, I missed doing these.
Credits to Tsonyo Atanasov for the inspiration.

Have a great week,
Alexis

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Originally posted on LinkedIn:

https://lnkd.in/p/dVJPvN2F