Anthropic on Tuesday released Claude Sonnet 4.6, a model that amounts to a seismic repricing event for the AI industry. It delivers near-flagship intelligence at mid-tier cost, and it lands squarely in the middle of an unprecedented corporate rush to deploy AI agents and automated coding tools.
OpenAI on Thursday launched GPT-5.3-Codex-Spark, a stripped-down coding model engineered for near-instantaneous response times, marking the company's first significant inference partnership outside its traditional Nvidia-dominated infrastructure. The model runs on hardware from Cerebras Systems, a Sunnyvale-based chipmaker whose wafer-scale processors specialize in low-latency AI workloads.
In this video, I look at Web MCP and how it could have a huge impact on how agents operate on the web and work with websites.
Chinese AI startup MiniMax, headquartered in Shanghai, has sent shockwaves through the AI industry today with the release of its new M2.5 language model in two variants, which promise to make high-end artificial intelligence so cheap you might stop worrying about the bill entirely.
It's also said to be "open source," though the weights (settings) and code haven't been posted yet, nor has the exact license type or terms. But that's almost beside the point given how cheap MiniMax is serving it through its API and those of partners.
Chinese AI startup Zhupai aka z.ai is back this week with an eye-popping new frontier large language model: GLM-5.
The latest in z.ai's ongoing and continually impressive GLM series, it retains an open source MIT License — perfect for enterprise deployment – and, in one of several notable achievements, achieves a record-low hallucination rate on the independent Artificial Analysis Intelligence Index v4.0.
With a score of -1 on the AA-Omniscience Index—representing a massive 35-point improvement over its predecessor—GLM-5 now leads the entire AI industry, including U.S. competitors like Google, OpenAI and Anthropic, in knowledge reliability by knowing when to abstain rather than fabricate information.
RAG isn't always fast enough or intelligent enough for modern agentic AI workflows. As teams move from short-lived chatbots to long-running, tool-heavy agents embedded in production systems, those limitations are becoming harder to work around.
In response, teams are experimenting with alternative memory architectures — sometimes called contextual memory or agentic memory — that prioritize persistence and stability over dynamic retrieval.
One of the more recent implementations of this approach is "observational memory," an open-source technology developed by Mastra, which was founded by the engineers who previously built and sold the Gatsby framework to Netlify.
I was curious if Block's Goose agent, paired with Ollama and the Qwen3-coder model, could really replace Claude Code.
Goose, developed by Jack Dorsey's company Block, is an open-source agent framework, similar to Claude Code. Qwen3-coder is a coding-centric large language model similar to Sonnet-4.5.