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What if AI-assisted coding became more reliable by separating product planning, engineering review, release, and QA into distinct operating modes? That is the idea behind Garry Tan’s gstack, an open-source toolkit that packages Claude Code into 8 opinionated workflow skills backed by a persistent browser runtime. The tookit describes itself as ‘Eight opinionated workflow skills […]
Google DeepMind team has introduced Aletheia, a specialized AI agent designed to bridge the gap between competition-level math and professional research. While models achieved gold-medal standards at the 2025 International Mathematical Olympiad (IMO), research requires navigating vast literature and constructing long-horizon proofs. Aletheia solves this by iteratively generating, verifying, and revising solutions in natural language.
In recent times, many developments in the agent ecosystem have focused on enabling AI agents to interact with external tools and access domain-specific knowledge more effectively. Two common approaches that have emerged are skills and MCPs. While they may appear similar at first, they differ in how they are set up, how they execute tasks,
Stanford researchers have introduced OpenJarvis, an open-source framework for building personal AI agents that run entirely on-device. The project comes from Stanford’s Scaling Intelligence Lab and is presented as both a research platform and deployment-ready infrastructure for local-first AI systems. Its focus is not only model execution, but also the broader software stack required to
Managing the economics of multi-agent AI now dictates the financial viability of modern business automation workflows. Organisations progressing past standard chat interfaces into multi-agent applications face two primary constraints. The first issue is the thinking tax; complex autonomous agents need to reason at each stage, making the reliance on massive architectures for every subtask too
How multi-agent AI economics influence business automation Read More »
In this tutorial, we build a Streaming Decision Agent that thinks and acts in an online, changing environment while continuously streaming safe, partial reasoning updates. We implement a dynamic grid world with moving obstacles and a shifting goal, then use an online A* planner in a receding-horizon loop to commit to only a few near-term
The gap between proprietary frontier models and highly transparent open-source models is closing faster than ever. NVIDIA has officially pulled the curtain back on Nemotron 3 Super, a staggering 120 billion parameter reasoning model engineered specifically for complex multi-agent applications. Released today, Nemotron 3 Super sits perfectly between the lightweight 30 billion parameter Nemotron 3
Large financial firms have spent years testing artificial intelligence in small projects, often limited to data analysis or customer support tools. The next phase appears to involve something more operational: systems that can take action in business workflows. Canadian insurer Manulife is moving in that direction as it works to deploy agent-based AI systems inside
Manulife moves AI agents into core financial workflows Read More »
Google expanded its Gemini model family with the release of Gemini Embedding 2. This second-generation model succeeds the text-only gemini-embedding-001 and is designed specifically to address the high-dimensional storage and cross-modal retrieval challenges faced by AI developers building production-grade Retrieval-Augmented Generation (RAG) systems. The Gemini Embedding 2 release marks a significant technical shift in how
The landscape of Text-to-Speech (TTS) is moving away from modular pipelines toward integrated Large Audio Models (LAMs). Fish Audio’s release of S2-Pro, the flagship model within the Fish Speech ecosystem, represents a shift toward open architectures capable of high-fidelity, multi-speaker synthesis with sub-150ms latency. The release provides a framework for zero-shot voice cloning and granular
