The expectations for the engineer of the future will shift — not just in what we build, but in how we communicate it.

My biggest takeaway from Gartner's D&A Summit wasn't actually about AI.

As I sit at this boarding gate, I keep thinking about the word interdisciplinary. But not in the sense of domain interdisciplinarity. Rather, the renewed importance of being both hands-on technical and personable.

I was actually talking to my brother about this last Friday. For as long as I can remember, engineers have been able to hide behind the complexity of their work, using that as a shield in a way that never forced them to hone their interpersonal skills. On the other end, "sales" people often went the opposite route. They've been able to hide behind the perceived complexity of the sales lifecycle and put aside developing deeper domain or technical knowledge.

Of course, I'm generalizing. But that's the point. Leaders are the ones who operate on the edge of this generalization.

AI at scale will shift repetitive work away from us. It will not replace engineers, but it will heavily accelerate the SDLC.

That silly JIRA task: change the banner color from blue to green. 90% done.

The Redis out-of-memory Sev-1 issue? That still needs your attention.

The expectations for the engineer of the future will shift with that extra capacity — not just in what we build, but in how we communicate it. The value of a good handshake. Knowing how to carry a conversation. The right pauses and emphasis when explaining your ideas. Charisma.

The same thing will happen on the sales side.

Sales teams' repetitive work will also compress. Market research? Quick web search prompt. Notes from the meeting? Teams will do that. Does the MSA support this new engagement model, or do we need to edit it? Done in five minutes, ready to send to legal. And these aren't even revolutionary use cases.

The expectations for this cohort will also change. The shift will be toward real thought leadership — meaning deeper technical conversations, or at the very least being able to explain why what they're selling actually matters for the business.

Many of the vendor reps my colleagues and I spoke with on the floor still haven't caught up.

If you've walked a conference floor recently, you probably know the script.

"We make your data AI ready." "Agentic platform." "Observability."

But one follow-up question and the tone changed.

We asked one, "So, can I deploy your solution on AWS?" Just smiles. No answer.

We asked another, "What does governance mean to you?" Nothing.

Another: "Who are your marquee clients?" Silence.

The right application of AI will free individuals from repetitive tasks so we can do our jobs better.

My question is whether the definition of "better" will change once it's all said and done.

As an engineer turned client-facing, I'm still figuring out what that balance really means in practice.