Anthropic’s expansion of Claude’s enterprise “Cowork” plugins marks an important inflection point in the evolution of AI systems. Claude is no longer positioned solely as a conversational assistant but as an operational actor capable of interacting directly with tools like Excel, PowerPoint, Google Docs and Sheets, and internal enterprise systems. This signals a broader shift…
Is AI Math solved? Maybe you think it is if Math Olympiad results mean “solved.” But what if “solved” means ready for reliable, production scale utilization?
The First Shift: Capability Matt Shumer is right. Something big is happening. The acceleration in AI capability is not incremental. It is structural. Tasks that once required teams now require prompts. Work that once demanded weeks of coordination now compresses into hours. Intelligence, at least in its procedural form, is becoming abundant. That transformation will…
(This is a repost of Elia’s original blog post at eliainsider.com) When I started developing software, the operating system handed off control to an application, the application did its thing, and when done, handed back control to the operating system. These early systems were largely single-application and linear. Control flow was simple and direct. The…
When organizations try to operationalize AI without computation governance, the failures follow a pattern. The three failure modes When organizations try to operationalize AI using existing containers for logic, they hit the same three walls: 1. The reproducibility problem Six months ago, your pricing model calculated a specific rate for a specific customer configuration. Now…
AI is reaching production—but the infrastructure isn’t ready. This post explores the spreadsheet problem: why brittle tools like Excel are still holding critical logic, and why deterministic execution layers like TrueMath are becoming essential as AI shifts from predictions to operations.
We get asked a lot by investors, partners, friends, and family: “Won’t the LLMs just figure this out?” It’s a fair question. And since we started working on TrueMath, we’ve seen clear improvements in how language models handle math. They write better code, make fewer obvious mistakes, and in many cases, they sound more correct…
At the recent ICML 2025 conference, Mark Khoury from Hudson River Trading (HRT) described the firm’s development of foundation-style transformer models trained on decades of market microstructure data. The result is a trillion-token-scale dataset spanning equities, futures, and crypto. Matt Robinson from AI Street, provided some great coverage of the presentation. It’s a huge step…
Bill Kelly and I have known each other for over 20 years. Across countless conversations about software, usability, and the mechanics of getting things right, one thing eluded us: the right project to build together. Bill started playing with ChatGPT, Claude, and Gemini to write documents. Because old habits die hard*, I kept asking math…
Last April, Tina He asked a deceptively simple question that still echoes when we consider agent math: What happens when AI agents become your primary users? That question opened a clear line of inquiry. If AI agents are the ones clicking buttons, reading documents, and deciding what APIs to call, then a lot of software…
End of content
End of content