Briefing #5: Hype Winter is Here
Why AI's cooldown is the best thing to happen to AI.
Note: This briefing was originally published on LinkedIn on August 22, 2025. It has been migrated to our new home on Substack to create a complete archive. Multi-format features like video and audio commentary are available for all new briefings published from April 2026 onwards.
The AGI-by-2025 prophecies have officially collapsed. In early 2025, OpenAI’s Sam Altman confidently predicted AI agents would soon “join the workforce.” This week, following the lukewarm reception of ChatGPT-5, he warns of an “AI bubble” and concedes the term “AGI” is becoming “less relevant.”
This whiplash has sent a chill through the enterprise world. The initial euphoria has been replaced by a creeping disillusionment, validated by Gartner’s confirmation that AI has entered the “trough of disillusionment.” We see the fallout in the data: S&P Global reports that the share of companies abandoning AI pilots has more than doubled to 42% this year. We see it in cautionary tales, as companies like Klarna, once champions of an “AI-first” approach, are now publicly admitting they went too far and are rehiring humans to mend the customer experience.
It would be easy to interpret this as an “AI Winter” — a sign that the technology has failed to deliver on its promise. But that is a profound misreading of the moment.
This isn’t an AI Winter; it’s a Hype Winter. And for serious, pragmatic leaders, it is a gift.
The technology’s core potential hasn’t vanished. What has vanished is the magical thinking that a single, all-powerful model could substitute for rigorous business strategy. The collapse of the AGI hype is a healthy, necessary market correction. It marks the end of the speculative frenzy and the beginning of the real work.
This is The Great Filtering. The companies that were chasing headlines are now being exposed. The projects built on the flimsy hope of a future technological leap are being abandoned. The leaders who mistook a technical output for a strategic outcome are facing the consequences.
What remains is the real opportunity: the unsexy, difficult, and deeply valuable work of fundamentally rewiring core business processes. The current disillusionment proves a thesis we’ve held all along: sustainable advantage isn’t created by adopting the fanciest model, but by applying today’s technology to your most critical business problems with strategic clarity.
The disappointment of ChatGPT-5 to be a magical solution is liberating. It frees leaders from the pressure of chasing an ever-receding technological horizon. It allows them to stop asking, “What is the next big model?” and start asking the more powerful question: “What is our most broken, high-value process, and how can the technology we have today begin to fix it?”
The path forward, out of the trough of disillusionment and onto the “slope of enlightenment,” is not paved with more advanced algorithms. It is paved with better business practices:
Focus on Process, Not Models: As research from Harvard Business School confirms, success comes from solving “bad data, bad results” problems first. Data quality and process optimization matter more than the algorithm.
Prioritize Augmentation, Not Replacement: The goal is not to replace humans but to augment them. The most resilient systems will be those that blend machine efficiency with human judgment, insight, and ethical oversight.
Build Trust Before You Scale: The hype cycle overlooked a fundamental truth: you cannot scale what you do not trust. The next five years will be defined by the development of robust governance, security, and trust frameworks. These are not brakes on innovation; they are the necessary foundation for it.
The tourists are leaving the AI landscape. The speculators are closing their books. For the pragmatic innovators who were focused on business value all along, the field is now clear. The Hype Winter is here, and the climate for building real, lasting AI-driven advantage has never been better.