Show HN: I made 25 tech predictions and mass-published them
I did something that might be incredibly stupid. I made 25 specific predictions about what will happen in tech over the next 6 months — and published all of them with deadlines before I could chicken out. Not vague "AI will grow" predictions. Specific, falsifiable claims like:
Medical AI will face mandatory safety requirements within 18 months (regulatory signals are screaming) There's a ~6 month window in AI infrastructure before consolidation locks out new entrants Browser agents hit mainstream faster than current discourse suggests
Each prediction has a confidence score, a hard deadline, and what would prove me wrong.
Why would I do this?
Because I'm tired of pundits making unfalsifiable claims and retroactively declaring victory. "I predicted crypto would struggle" — okay, when? By how much? What counts as struggling?
So I'm doing the opposite. Public predictions. Specific deadlines. No editing after the fact.
The first verification check runs January 24. I'll publish results whether they make me look smart or completely delusional.
A few already make me uncomfortable — some have conviction scores above 75%, which feels overconfident for 6-month horizons. But that's the point. If I'm not risking being wrong, I'm not actually predicting anything.
All 25: https://asof.app/alpha
What's your most contrarian take on what happens in tech this year? Curious what predictions HN would make with actual deadlines attached. One pattern I’ve noticed across tech (and especially crypto) is that the hardest part to predict isn’t what will happen, but how quickly trust compounds once a narrative starts aligning with real behavior.
We’ve seen this while working on long-term visibility and adoption for Web3 products at AixBoost.com — short-term spikes almost never validate predictions, but slow, consistent signals tend to confirm or kill them pretty decisively.
Curious which of your predictions you personally feel most uneasy about being wrong on. The OpenAI platformization take feels like the safest bet here (imo it's already the consensus in most SF infra circles - my ttwo cents here: https://philippdubach.com/posts/how-ai-is-shaping-my-investm...).
The medical MLLM grafting is a much higher-stakes claim. Let’s see if "regulatory-grade" ever actually happens without a full retraining—history suggests the FDA isn't a fan of modular grafts. Yeah fair point on the medical MLLM stuff. FDA and modular approaches have never been best friends. That's actually why I'm most curious to see how it plays out - the ArXiv activity around safety grafting has been picking up but whether regulators actually buy it vs demanding full retraining... we'll see.
The OpenAI platformization one I'll admit feels safer. Curious though - do you think the window's already closing or is there still runway for the picks and shovels players?