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Fabio Lauria
Per-token prices keep collapsing. Reasoning models burn multiples more tokens per task. Net effect: your usage bill rises while unit compute falls — and essentially no contract has a downward repricing clause.on BlueskyOutcome-based pricing isn't vendors caring about your ROI. It's vendors who can no longer afford to eat a 23%-of-revenue inference bill. Same 94% of CEOs who say seat pricing still matches their value are killing it anyway. That's not a value decision. It's a margin decision, dressed up.on ThreadsEveryone treats latency like a speedometer, a number to shave down when they get around to it. It is not a spec — it is a tax on every interaction, and your users pay it whether or not your feature ever lands. @electesrlon InstagramEveryone assumes the shift away from seat-based SaaS pricing is a fairness revolution. 97% of SaaS CEOs plan to retire seat pricing within two years — while 94% admit seat pricing still matches their product's value. That gap is the entire story. — Fabio Lauria (@fabiolauria92) Sep 7, 2026View on X17.7% of US small firms have actually paid for an AI tool. 55% say they use one. That gap is free-tier ROI, unpriced. Gartner sees SMB entry cost hitting zero by 2027. Free is acquisition cost, not price.on BlueskyThe dubbing industry as we know it has maybe eighteen months left, and almost nobody in localization is ready. The winners will be the voice actors who stop selling sessions and start licensing their cloned voice like real estate, collecting rent on every language they never actually spoke. @electesrlon InstagramSmall businesses aren't behind on AI. They're just too small to waste money on it properly. 95% of enterprise pilots produce nothing while the median SMB spends 8k a year and gets real gains. The catch: most of that ROI is running on free tiers nobody has priced yet.on ThreadsYou can delete a contact, unfollow a friend, wipe your whole account — and the platform still knows who you are, because it never needed your permission to connect the dots around you. This week I wrote about the social graph: you consent to what you share, but the inferences built from everyone else's data outlive anything you erase, and that's the privacy problem nobody wants to own. @electesrlon InstagramField note from a year of SME implementations, and the data now backs what we kept seeing.The conventional framing is that small firms are catching up to enterprises on AI. The numbers say the opposite.MIT's NANDA study found 95% of enterprise generative-AI pilots deliver no measurable P&L impact. Enterprises spent $37B on generative AI in 2025. The median AI-adopting small business spent $8,200 for the year, and 80%+ of AI-using SMBs report productivity gains. By August 2025 the SBA measured large-firm production AI use at 10.5% against 8.8% for small firms, down from a 1.8x gap in early 2024.Small firms aren't winning because they're clever. They're winning because a five-person team can change a process on Tuesday. A 5,000-person org needs a change board.But here's what most commentary skips. JPMorgan Chase Institute transaction data shows only 17.7% of US small businesses have actually paid for an AI tool, versus 55% claiming to use one. Most of that celebrated SME ROI is running on free tiers, and Gartner expects SMB entry cost to trend toward zero by 2027. Free is the acquisition cost, not the price.So the real question for European SMEs isn't which tool, it's what you own when the meter turns back on.Which of your AI-driven gains survive a vendor swap? And who in your business owns the process documentation, not the prompts?on LinkedInEveryone says SMEs are falling behind on AI. Then MIT's NANDA report found 95% of enterprise generative-AI pilots produce zero measurable P&L impact. The median AI-adopting small business spends $8,200 a year and gets results. Scale isn't the advantage here. It's the handicap. — Fabio Lauria (@fabiolauria92) Sep 4, 2026View on XThe AI Act's real SME clause is Art. 25: substantially modify a high-risk system and you inherit provider duties. So SMEs don't fine-tune. That's not safety, that's a moat.on BlueskyWe spent years shaving milliseconds off response time, then watched users trust the slower model that showed its work. Turns out people do not want the fastest answer, they want to believe the answer was earned. @electesrlon Instagram