Did you know there were recently 4 AI supply-chain security incidents in 50 days? They hit OpenAI, Anthropic, and Meta-adjacent infrastructure.... things like elease pipelines, CI runners, and dependency hooks. It got almost zero coverage, which is unfortunate. The attack surface for AI systems is turning out to be the software factory around the model... not necessarily the model, itself. Red teams test for things like jailbreaks and system card violations, but they don't typically test the publish gates, package managers, and CI pipelines that ship the models into production. While I wish this were a coincidence, four incidents in 50 days across three major labs is systematic. When something breaks publicly (and it will soon) this will suddenly get all the coverage it deserves. Check out the @VentureBeat article for a bigger breakdown. venturebeat.com/security/sup…

Notion just opened its workspace to outside agents. Anthropic just locked Claude's agents inside your own infrastructure. Same week, opposite architectures. One of them is wrong about where enterprise trust lives. @NotionHQ's bet: the platform is the trusted intermediary. Any agent, anywhere, can plug in. @AnthropicAI's bet: enterprise buyers need control at the perimeter. Your data never leaves your environment. Whichever architecture wins will eventually set the default for how AI agents integrate with corporate workflows through 2028. It's governance philosophy masquerading as a product decision.

Two different AI papers this week made the same point from opposite directions. @thinkymachines says the real frontier is real-time interactivity over static output quality. Josh and Palmer at @AICollectiveCo say it's recoverability, no matter if failures are visible and bounded. Both are right. Neither shows up on a benchmark. The field has been measuring the wrong things. Deployment is forcing the issue. The practical implication: If you're evaluating AI tools using vendor benchmarks or public leaderboards, you're selecting for performance in conditions that don't exist in production. The model you pick because it aced MMLU might be the one that wipes a folder without telling you, or breaks when your users don't communicate in tidy, complete prompts. For anyone making AI purchasing or deployment decisions, the honest criteria aren't "what's the benchmark score?" They're: "What does this model do when it's wrong? Does it tell me? Can I recover from it?" Almost no vendor answers those questions directly, because almost no benchmark has required them to.

This was a very fun Easter egg to see! #GMG @MeanGreenFB @UNTsocial

I'm sitting in a startup pitch session, wishing more of these companies with good ideas made an effort to differentiate between standalone and presentation decks. So much text! What are your go-to slide deck resources for effective presentations?

This was very cool to conceptualize and film. @CompassDCs is the best. Take a look for a few fresh perspectives on connectivity and emerging technology.

Making it a TBOY today. @tboypod

"We're launching a brand new enhanced offering that we couldn't be more excited about! As part of this invigorating new chapter that will definitely make us more competitive in our market, ALL of our customers can GTFO right now. And we do mean immediately. Kthxbye." -@BlooomInc

There's still 3 days left to apply for #SXSWPitch. Great reason to take your startup to Austin on March 11-12. Apply by Sunday, Nov 13 at 11:59 pm PST. There will be NO extension. sxsw.com/pitch/

I had a great @lunchclubai call today w/ @aBroidy, and this easy productivity gut-check makes a lot of sense to me. I bet something like @pomotodo and a good binaural beats flow state album would help keep me on track -- and even maybe begin quantifying productive time. Thoughts?

This #NFT micro-summit today by @Tech_in_Motion is pretty cool. First time I'm hearing someone finally talking about tokenization away from simple art and referencing real-world (virtual-world?) utility. techinmotion.brandlive.com/f…