“I get the skepticism. A lot of what fills my timeline is fundraising theater and attention arbitrage, not real capability. But I would separate the hype from the actual shift: LLMs really do automate information processing we could never specify by hand, and the question for your roadmap is whether your workflows are verifiable enough to train against.”
“I’ve seen teams at Dropbox and in my own companies treat AI like a feature multiplier, betting the roadmap on demos that collapse under real usage. The ones that survive start with one workflow, prove the AI can consistently deliver the outcome, and only then scale. If your gut says hype, force the bet to pass that test before it eats the roadmap.”
“A mandate is not an AI strategy. I have watched enterprise teams deploy agents, get a quick win, then stall because nobody owned the upkeep, the data controls, or the integration into a real process. If your roadmap is just add AI everywhere, the hype will eat you. Pick one workflow where AI changes a decision your users make every day, and prove that before you bet the rest.”
“I watched teams at Google ship GenAI features that looked magical in demos and fell apart on real queries, and others that quietly cut support costs by 30%. The difference was never the model; it was whether the use case had a feedback loop that made the product better the more people used it. If your roadmap bets on AI without that loop, the hype will eat you.”
“I have lived through this exact pressure. At Narrative Science, investors hammered us to make our AI self-service, and we spent years and capital chasing that ideal with mixed results. What I actually believe now is that most enterprise AI bets are currently more air cover than real ROI, and the real value comes from embedding AI deeply into a workflow customers already have, not bolting a model onto a roadmap.”
“I think the hype is real in some places and fake in others, and the teams that get burned are the ones that treat AI as a feature instead of a solution to a specific user problem.”
“I have watched teams burn months on AI strategy that produced nothing but demos, and I have also built agents inside Project and P6 that actually claw back schedule risk hours. The difference is whether the use case is narrow enough to survive the hype.”
“I’ve been saying for a while that the AI hype has obscured how little it has actually penetrated corporate value chains, so your instinct is not wrong. The teams I see winning are the ones running small, measurable pilots before they bet the roadmap, not the ones renaming strategy slides AI-first.”