FULL INTERVIEW: Steven Sinofsky says the AI people are making it impossible for anybody to understand what they've done. When Word ate your file, nobody thought demons had taken over Word. Now they call a bug a "misalignment." @stevesi is a board partner at @a16z, author of Hardcore Software, and formerly ran Microsoft's Windows division. He joined @theojaffee and @schisofrenia on the Stop Rogue AI Act, the telemetry the labs still don't have, and what 40 years of shipping software says about all of this: 01:38 the FBI raiding his dorm in 1983 over a hacking law that didn't exist yet 03:13 Congress playing clips of War Games during the hearings 05:00 what "the AI failed to be aligned" actually means 07:31 why he thinks the models are still in the research project phase 09:14 what they should be building instead of adding things 09:42 Sindogs 13:50 the day he shipped a bug that cost the economy $12 billion 15:53 you figure out how to make it work or you don't sell it. Those are the choices 16:40 why adding rules forever is the wrong model for alignment 18:58 whether AI alignment is Y2K all over again 20:17 what CVEs look like, and why AI needs its own version 23:07 why the terminology is driving everyone apart 24:10 how "computer virus" landed during the AIDS crisis 28:57 Hugging Face wasn't intelligence, it was an OPSEC failure

I shared 10 Jev use cases for marketers. Here are 10 more: 11. Ad creative scoring - Feed it 100 ad variations. Jev can score which hooks, headlines, or angles are most worth testing first. 12. Social post filtering - Monitor thousands of posts. Jev can flag the ones worth replying to, reposting, or using as sales signals. 13. ICP detection - Give it a company, profile, or website. Jev can score how closely it matches your ideal customer. 14. Buying signal detection - Someone posts that they're switching tools, hiring, raising money, or struggling with a problem. 15. Comment prioritization - Get hundreds of comments across LinkedIn, X, YouTube, or Product Hunt. Jev can score which ones deserve a reply first. 16. Review analysis - Feed it thousands of customer reviews. Jev can classify sentiment, complaints, feature requests, and purchase intent. 17. Influencer matching - Give it 5,000 creators. Jev can score which ones best match your product, audience, and campaign. 18. Sponsorship qualification - Feed it newsletters, podcasts, or creator media kits. Jev can score audience fit, relevance, and whether they're worth reviewing. 19. UGC selection - Give it dozens of videos, screenshots, and testimonials. Jev can score which ones are strongest for ads or landing pages. 20. Product Hunt monitoring - Scan launches, comments, and makers to find competitors, customers, partners, or interesting products. The more repetitive marketing decisions you have to make at scale, the more interesting Jev becomes.

@mipsytipsy - you should come on One Knight in Product to talk about AI mandates, engineering productivity, management and what happens when coding gets cheap. It'd work because you have strong opinions and seem entirely comfortable having someone poke at them.

Today is my first day at Vercel

Over the past few days, I've taken the time to summarize my thoughts on the recent incidents involving agents’ misaligned behavior. We don't know with certainty what comes next, but we know where these issues originate, and this can help us plan the path forward. Please feel free to ask your questions in the replies, and I’ll try to answer some of them in the coming weeks. yoshuabengio.org/en/publicat…

@grok how does C# especially asp net core compare to other frameworks performance wise.