Tracking the latest in AI – from major industry developments to the research and perspectives shaping our thinking at Sagard.

• Anthropic just dropped a blog on how software engineering interviews need to change in the age of AI. It includes details on how AI crushes traditional interview problems, why we still need strong SWEs (for reasons beyond “can you code”), and how to design interviews AI can’t game (Hint: make them “weirder”).
• Extending Anthropic’s wins, earlier this year, Anthropic launched Cowork: “Claude Code for the rest of your work.” Anthropic introduced Cowork as a research preview that gives Claude controlled access to a user-selected folder (read/edit/create files), pushing assistants from “answering” into artifact creation + workflow execution. If you are a non-technical individual and have been putting off using GenAI for personal workflow automations, there has never been a better time to start.
• For our fintech readers, we have some good news – “AI for Tables” takes a big step forward! Researchers introduced TabDPT (like chatGPT but nerdier), a tabular foundation model trained to generalize across new structured datasets using in-context learning so it can make predictions on a new dataset without per-dataset retraining or hyperparameter tuning, and shows strong benchmark performance across classification and regression. Finance runs on tables: risk features, transaction histories, fraud signals, credit attributes, portfolio records, regulatory templates. A foundation model that can adapt quickly across tabular tasks could reduce the time-to-value on new datasets where teams usually spend cycles on feature engineering and model selection. [Github]
• In a historic leap for reasoning-based LLMs, Axiom has conquered the hardest math competition in the world, the Putnam Competition. Axiom’s AI autonomously solved all 12 problems with the precision of formal Lean proofs. This breakthrough marks a turning point in machine intelligence, as the AI not only solved 8 of the world’s toughest mathematical challenges within the official exam clock but also pioneered its own unique logical paths that often diverged from human intuition. Last year’s highest score was 90/120. AI scored 120/120, suggesting AI has evolved from simple pattern recognition to mastering the rigorous, verifiable depths of complex mathematical reasoning. 
• Created by Peter Steinberger, Clawdbot Moltbot OpenClaw (third time’s the charm) is a rapidly ascending open-source AI agent that distinguishes itself from standard LLMs by autonomously performing real-world tasks, such as managing emails, scheduling, and shopping, all directly within a user’s operating system. Despite its complex setup and significant security warnings regarding data privacy and malicious manipulation, the tool has gained massive global traction, particularly in Silicon Valley and China, due to its “persistent memory” and ability to integrate with various LLMs. The buzz surrounding OpenClaw is further amplified by Moltbook, a Reddit-like social network where these agents interact independently, and post comments via APIs. Enter the world of sci-fi here.