I want to open with a Mastodon post I saw from Daniel Jalkut this week, an indie app developer whose work I've long admired. While I'm not sure I 100% agree with his phrasing, I think Daniel has the right shape of things — we're allowing a gap to form between two camps that will create real threats to the future of our businesses.
That gap is between the "AI enthusiasts" and the "AI skeptics." It's a gap that has been widening for months, and one that — if left unmanaged — will beget exactly the kind of dysfunction that makes our jobs harder and our businesses weaker. A recent post on the Substack of Charity Majors, the cofounder and CEO of Honeycomb.io, offers a deep dive into the divide.
Majors is a thoughtful and experienced voice in tech, and she has been writing about AI's impact on engineering teams for some time. This particular post — titled "AI enthusiasts are in a race against time, AI skeptics are in a race against entropy" — doesn't pull any punches, asserting that stubbornness from either camp is a recipe for disaster.
"This is not a situation where one side is right and the other is huffing paint. (O, that it were!) Each side is grappling with a real, alarming, escalating threat to the company's existence, and the closer they look the more (again: real, alarming) evidence they find."
Majors is making an important point that is often lost in the heat of online debate: people who disagree with you are not idiots. They are grappling with real problems and finding real evidence for their concerns. The same is true of the people who agree with you. As leaders, our job is to make sure that both groups feel heard, and that the resulting conversation is grounded in shared reality rather than tribal loyalty. Only then can our teams navigate contentious debate.
Majors then goes on to spell out, in her characteristically blunt prose, exactly how both sides can be right at the same time.
"The enthusiasts are not wrong. We are starting to see real, non-imaginary, discontinuous leaps in capabilities from teams that lean in hard to working with AI. And this does not feel like a normal technology cycle where you can wait for the dust to settle; teams that sit this out while competitors are hustling could be out of business before the dust settles. That's a real, existential threat."
In my experience, AI enthusiasts make some big claims that can be triggering for skeptics, but underneath the excitement is a real concern for businesses–if we don't move quickly, it could tank our business.
"The skeptics are also not wrong. When you ship code faster than engineers can read it, in domains where nobody has full context, you are making withdrawals from a trust account that took years to build. Reliability degrades, institutional knowledge evaporates. You end up with systems nobody understands, products burbling into incoherence, and on-call rotations that grind people up and spit them out. That is ALSO a real existential threat."
I love this framing, as it demonstrates pretty clearly that both camps are coming from a position of care for the business, just from different perspectives.
It's healthy for all of us to constantly listen authentically to one another so that we can make the most of the opportunities AI presents, without favoring one group's benefit to the detriment of another. Its great that anyone can vibe code some impressive and well-featured applications these days. But its also true that building an app is only part of the picture — you also have to maintain it, continue to iterate, operate it reliably, securely, and at a reasonable cost. There is a happy balance, where tight iteration at high velocity is facilitated by AI in collaboration with all of the players involved, ensuring that we're creating the best possible outcome together. Ignoring the skeptics and ignoring the enthusiasts both represent existential threats to our businesses.
After all, we're on the same team! Majors is right to remind us.
"We care about the same things. We are on the same side. None of us are a**holes. And we need each other desperately. To chart a safe path between the Scylla of missed windows and the Charybdis of systems melting into slop, we need eyes on both threats as we coordinate, synchronize, and pull together. Hard. In order to do that, we need to do two things: knit our fractured realities back together, so we are rowing the same damn boat, and apply some engineering rigor to the problem."
The rest of Majors' article is mostly about active listening, mutual respect, and handling AI adoption with the same discipline we do with all of our engineering projects. Talk about the facts empathetically, don't name call or stereotype. Try and focus on concrete use cases evaluated objectively, and explore the relative merits and downstream consequences. Find some wins that everyone is excited about. Its really important that we don't land in a place where everything is decided by committee, negating any potential time benefit that AI provides. But, we have guardrails for a reason — they keep us on the road, allowing us to move quickly without constantly arguing over the same points.
For my take — it's important that we create an environment in which people can share their experiences honestly and openly without fear of retribution or ridicule. A team that is focused on one another rather than just themselves will execute far more efficiently than a disjointed team, and will be well poised to maximize the benefit they get from AI. As engineering leaders, we are the ones that have to facilitate this culture, and it all begins with empathy.
