ngLover

On August 1, 2026, OpenAI announced Astra, calling it their next major model family. They didn't release a product. They dropped a GitHub repo containing Lean 4 certificates formally verifying ten solutions to open problems in mathematics, some unsolved for over a decade. The standout: a construction proving non-sofic groups exist, a question Mikhail Gromov posed in 1999 that sat open for 27 years. The estimated token cost to find all ten solutions: roughly $2,000 at Sol API rates. That's about $200 per problem spanning group theory, von Neumann algebras, quantum complexity, and lattice cryptography. Sit with that number for a moment. What Astra Actually Is Astra is not a public product yet. OpenAI is positioning it as a model family built for long-horizon multi-agent work. The design is explicit: multiple agents working together on a single task for hours or days, not seconds. The system plans, tests its own output, revises, and keeps going without needing you to steer ea...

n8n shipped a significant update on July 29 that I've been waiting for since they announced MCP integration earlier this year. The headline: n8n now works as both an MCP client and an MCP server. That's not just a configuration option. It changes how you think about the workflows you've already built. What the July 29 Release Actually Shipped Four things worth paying attention to (full details in n8n's release notes ): Native MCP server mode. Any n8n workflow can now be exposed as a callable tool to external AI clients. Claude Desktop, a custom agent, your own LLM-powered interface. If the client speaks MCP, it can call your workflow. You toggle this at the workflow level, or bulk-enable it across an entire project folder from the new folder actions menu. Native MCP client mode. n8n's AI Agent nodes can now discover and call external MCP-compliant tools directly, without you writing a custom API wrapper or an HTTP request node. The agent resolves the tool lis...

Most experimentation teams I talk to are more worried about concurrent tests than they should be. They treat isolation as the default, queue up experiments sequentially, and then wonder why velocity is low. The interaction effect problem is real in theory. In practice, it barely shows up. What Interaction Effects Are (and Why People Panic) When two A/B tests run simultaneously on the same user population, there's a risk that they interfere with each other. Test A changes the header. Test B changes the checkout button. A user sees both. The concern is that the combined effect is different from what you'd expect by adding the individual effects together. In statistics, this is called a qualitative interaction: the direction of one test's result reverses depending on the state of another. That's the scary version. What actually happens is almost never that dramatic. What the Data Actually Shows Microsoft's experimentation team ran a rigorous analysis across four...

On July 28, Anthropic published research showing that Claude Mythos Preview, their unreleased frontier model, found two previously unknown cryptographic attacks in roughly 60 hours of autonomous work. One of them helped take down a NIST post-quantum signature candidate that had survived two rounds of expert human review spanning two years. That is not a prompt engineering trick. That is AI doing original mathematics. To be clear about what this is and is not: the production systems you depend on are not at immediate risk. Full AES-256 is fine. The attacks target weakened or candidate schemes. But the more important story is how fast this happened, and what it tells us about where AI fits in the research pipeline going forward. What Claude Mythos Actually Did Claude Mythos Preview ran for approximately 60 hours on cryptanalysis work targeting two algorithms: HAWK, a lattice-based post-quantum signature scheme that was in NIST's additional standardization process, and a weakened...

Google pushed an update to Gemini API Managed Agents on July 28 that I've been waiting for. It's not a new model. It's the production scaffolding that makes running agents as background workers actually viable: budget caps, cron triggers, environment hooks, and a proper API to manage the sandboxes. None of this is conceptually new, but it fills the gaps that made me nervous about committing to the platform for anything beyond a demo. What They Shipped Six things landed in this release. Gemini 3.6 Flash is now the default model for managed agents, with no code changes required. But the parts that matter operationally are the new production primitives. Cron triggers. You bind an agent, a prompt, an environment, and a cron expression into a single persistent resource. The trigger fires on schedule without you doing anything. Each run reuses the same sandbox, so files written in one execution are visible to the next. If a run fails five times in a row, the trigger pauses i...

Last week at SIGGRAPH 2026 in Los Angeles, six major professional creative applications announced Model Context Protocol server integrations at the same conference. Blender, Unreal Engine, Adobe Creative Cloud, SideFX Houdini 22, Boris FX Silhouette, and Foundry Griptape. Not demos or research previews. Announced and demonstrated, shipping or in active preview. That is the story. The protocol that started in AI coding assistants just crossed into the professional DCC (digital content creation) ecosystem all at once. If you have been building with MCP on the AI tooling side, this should get your attention. Not because Blender and Houdini suddenly matter to your agent pipeline, but because of what it means when a standard connection layer starts showing up in professional software categories at scale. What Each Integration Actually Does Let me be concrete, because the announcement headline does not tell you much on its own. Unreal Engine now exposes editor capabilities through an M...