@awxjack Congress posed 11 pages of questions you have ignored and still refuse to answer. If you are subject to National Law 50, you pose a national security threat to Americans. FYI The Australian media has widely covered all of your distortions.

I twice agreed to appear on a podcast w you moderated by one of your investors and you backed out twice. There are also 11 detailed pages of questions that the Congressional Committie w expertise asks about which you constantly fail to respond to—including why do your contracts explicitly state that you are proceeding US transactions through a Chinese subsidiary and why you are hiring multiple global remit roles in China still?

AI spend is measured in tokens, model calls, and dollars. However, none of these fields describe the actual work being done. At Ramp, we built a semantic layer that attributes agent spend to objectives and outcomes. This allowed us to go from monitoring AI spend to understanding AI ROI. Here's how we built it 🧵

Ep #274# of The High Flyers Podcast is live! Re-imagine a high flyer with Keith Rabois (@rabois) -- in arguably his most personal conversation yet. We explore: ▪️ The childhood not widely shared before ▪️ Online Keith vs real Keith ▪️ How Peter Thiel’s criticism transformed him ▪️ The overlooked years after PayPal ▪️ Handwritten notes, banned laptops & Assistants ▪️ Real product-market fit vs corporate curiosity in AI today ▪️ How he would build his own VC fund today ▪️ The five people he’d spend two hours with and why ▪️ One thing he's learnt from @jacobhelberg -> LISTEN HERE: Thx for the research help: @kevinhartz, @zebulgar, @mike_sheb, @justindross, @geoffdonaker, @vhankes Ppl mentioned include: @DavidSacks, @winstonweinberg, @reidhoffman, @mlevchin, @sama, @danielgross, @t_xu

I first met @matanSF following a kind intro from @MattEvantic.   We went for a walk in Hyde Park. I was in my trusty short shorts and it was kinda awkward as a walk.  It was awkward because after 5 mins, he was clearly a genius and for the next 55 mins, I just had to pretend like I had more questions to ask before saying with intense eagerness, “can I invest”.  Thank the lord he let me. And through that I got to spend time with his co-founder, @EnoReyes.  Eno is this insane combination of a truly brilliant technologist with an intense awareness of what it takes to build an insanely high-margin, efficient business in AI.  I sat down with Eno when he was in London recently (episode in comments) and have added my handwritten notes below.  Special thanks to @rabois @shaunmmaguire @byersblake @Sabina_Smith_ @laurenmhreeder for some amazing question suggestions. -- 1. The Frontier in AI Right Now The true frontier of AI is building verification systems where no benchmarks exist. Creating systematic frameworks for what “good” looks like allows AI to reliably execute complex, high-friction human tasks that were previously difficult to automate. Is this the true beauty of Instinct @noahrshinn @saranormous 2. The Two Ways That Large Language Models Will Win Frontier model providers face two paths: dominate infrastructure through high-volume inference or move up the stack into high-margin applications. But model-locked applications can conflict with what enterprises actually want: the best possible outcome across multiple models. Love to hear your thoughts on this specifically @AnjneyMidha @mmurph 3. What Is Required to Get the Most Out of Models? Simple gateway routing outside the execution layer delivers only basic cost savings. Maximizing agentic performance requires operating statefully inside the workflow itself, dynamically understanding context, execution history, and what needs to happen next. How do you think about this @alexatallah @shensi @ThibaultJaigu @rauchg @koblovinamerica 4. Why 80% of Neo Labs Will Die and What Separates the Winners From the Losers The winners will anchor themselves to durable enterprise workflows that do not disappear as underlying frontier models improve. Single biggest advice to VCs on investing in neolabs today @LiamFedus 5. Why the Harness Is So Valuable and Who Ultimately Is the Sovereign of Your Intelligence Continuous learning and workflow optimization happen at the harness layer, not inside closed model APIs. True enterprise sovereignty requires owning your harnesses and learning loops so critical intelligence remains proprietary rather than being ceded to third-party labs. 6. Why We Should Not Be Scared to Use Chinese Open-Source Models Labeling open-source weights as dangerous “Chinese models” can obscure the distinction between model provenance and actual security risk. Open models can reflect creator biases, but their risks should be evaluated technically rather than by origin alone. As open weights improve, they could power a growing share of standard enterprise workflows.

Factory has a super nova on their hands rn. OMG!! I think these guys are going to crack long running agents by the end of the year. Extreme alpha in this article. “The single agent didn't lack skill. It lacked a standard of completion. An independent standard, authored by the same model, drove the implementation much closer to behavioral parity with the reference. What generalizes to real software work is the need for an external, executable standard of completion - one derived from the outcome, before implementation narrows attention, and kept current until the work meets it.”