As was perhaps inevitable, AI seems to be losing some of its luster. In last week’s Shimmy Says, I asked the question of whether we’re living in an AI bubble. That doesn’t mean AI is a failure, or that it won’t scale some of the great heights its champions project for it. But the hype machine has been running at full throttle, so overheated that keeping up with it is impossible
What we’re witnessing now is a natural correction. The technology hasn’t collapsed, but the narrative around it has begun to wobble. And some are mistaking that wobble for a fall. Let’s look at a few recent articles that feed into this growing chorus of skepticism, and then consider why the reality is both more measured and more hopeful.
The AI Hype is a Dead Man Walking – LinkedIn
In this LinkedIn commentary, AI hype is painted as unsustainable, a “dead man walking.” The argument boils down to math: The expectations outpace the technical and economic realities. It’s a familiar refrain — we’ve seen it with the dot-com boom, crypto, even cloud in its early days.
But here’s the counterpoint: Hype cycles don’t dictate actual innovation. AI, for all the froth, is already woven into enterprise workflows, cybersecurity tooling, consumer applications, and more. Dismissing AI as a bubble overlooks the fact that, unlike vaporware fads, AI is delivering real value every day. Yes, the math may not support infinite growth curves, but incremental gains at current levels are still revolutionary.
Futurum’s research echoes this point: 91% of organizations currently implementing AI report measurable improvements — often operational, but increasingly strategic. Even as headlines cool, AI’s steady progress continues quietly in the background.
AWS CEO Matt Garman Just Said What Everyone’s Thinking About AI Replacing Developers – ITPro
Matt Garman of AWS stirred conversation by voicing what many developers quietly fear — that AI won’t replace software engineers wholesale. Instead, it will augment and accelerate them. The headline, though, reads like a letdown: The dream of “AI eats software jobs” is recast as a myth.
But is that bad news? Hardly. The more pragmatic view — that AI amplifies human talent — is both more believable and more useful. We’ve seen this movie before with DevOps and automation. Did automation replace sysadmins? No. It created a new breed of engineers who work at higher levels of abstraction. AI is set to do the same, elevating developers from code monkeys to orchestrators of intelligent systems. If anything, this is more exciting than a fantasy about replacing humans outright.
In fact, Futurum intelligence finds that 69% of organizations deploying AI for software engineering see the greatest gains in team productivity and velocity — not workforce reduction. The consensus emerging from real-world data: Augmentation, not replacement, is the near-term future.
The Hidden Costs of Coding with Generative AI – MIT Sloan Review
MIT Sloan Review digs into the downsides of AI-assisted coding: Errors, technical debt, loss of deep understanding, and the risk of over-reliance. These are valid critiques. Anyone who has worked with AI coding copilots knows the thrill of rapid progress and the chill of realizing your code compiles but is subtly wrong.
Yet let’s zoom out. The history of software engineering is the history of hidden costs. Object-oriented programming had hidden costs. Open source had hidden costs. Cloud-native architectures had hidden costs. But in each case, the net benefit outweighed the drawbacks. Generative AI is no different. Yes, we must invest in governance, training, and tooling to manage these risks. But the productivity and innovation it enables will dwarf the costs—just as every prior evolution in development has done.
Beyond the Headlines: Incremental Progress is Still Revolutionary
Here’s the thing: Even if AI progress were to slow to a crawl tomorrow, the tools we already have would remain transformative. Generative AI has democratized access to knowledge, reshaped customer service, accelerated coding and enabled nontechnical users to build solutions that once required specialists. That’s not a plateau — that’s a leap.
We may be spoiled. The pace of breakthroughs over the past two years — transformer models, multimodal systems, agentic AI — created the illusion of perpetual exponential growth. But technology rarely moves in straight lines. Plateaus, pauses, and recalibrations are part of the journey. If all we get in the near term are refinements and efficiencies on today’s systems, that is still enough to transform industries. Imagine if we stopped right here. No GPT-6, no quantum leaps. Even then, AI is already reshaping healthcare, logistics, and education in ways unimaginable just a few years ago.
