Models keep improving on long-horizon tasks, but splitting work across many agents doesn’t suit every problem. We walk through the setup for a single agent working sequentially on a task where mistakes compound: modeling the early universe. Read more:

"Foundation models are now better technically than most people." "OpenAI and Anthropic can subsume any business that only relies on technical talent." "Regulatory moats take years and a lot of trust. There's a lot involved beyond just technology that cannot be vibe-coded." @neerajprasad on why @MoonPay acquired Helio, Iron, Sodot, and Dawn in 18 months: "There are four moats in launching any product today. Technical talent, capital, regulatory licensing, and distribution. At MoonPay we have all four." "We genuinely are playing to win." Neeraj's full thesis on the un-vibe-codeable moats in crypto infrastructure:

Best models - May Edition Coding - GPT 5.5 xHigh Seeking truth - Grok 4.3 Video - SeeDance 2.0 Image - GPT Image 2.0 Voice - Gemini Live Hermes - m2.7 Cheap coding - Kimi 2.6 Cheap fast - Gemini Flash Best open source - DeepSeek v4 Pretty much everything will change after Google I/O

AI models aren’t yet general-purpose alignment scientists. Progress isn't as easy to verify on most alignment research tasks: our AARs would find “fuzzier” research much harder. But our experiment does show that Claude can increase the rate of experimentation and exploration.

The models work. Now what do we build with them? Introducing the AIA Ecosystem Fund. 🌀 Backing AI Agent + Physical AI, two seed investments already live: 🔹 @TheAliceAI : A decision assistant. It takes fragmented signals across crypto, sports, and politics, and gives you one clear call. On-chain, uneditable, executable. 🔹 ASIC AI Chip: custom silicon designed specifically for inference, not training, because most of the cost is in running models, not building them More coming soon. Full story 👇

AI models are getting faster (#GTC#), but conventional on-chain data is still lagging. To unlock true Agentic trading, you need purpose-built infrastructure. That’s why Derivio engineered a high-performance data engine from the ground up. Better data → Better signals → Seamless execution. 📊⛓️