·6 min read
What business process automation actually costs
Almost nobody publishes a price for automation work, and the reason is not evasion. Here is the cost structure underneath a quote, and how to read one.
- ·4 min read
Installing an agent skill is running untrusted code
A skill looks like documentation, so teams install one like they trust a README. The audits say treat it like code you are about to execute.
- ·4 min read
Multi-agent systems fail at the seams, not the model
The largest study of multi-agent failures found the model almost never causes them. The leverage is cheap plumbing at the seams.
- ·4 min read
Palantir said the quiet part: the bottleneck is not intelligence
At DevCon 6, the biggest enterprise-AI name built its agent launch on reliability, not model capability. Note what still was not in the box.
- ·6 min read
AI Agents That Improve Themselves: What the Evidence Actually Supports
A viral paper says self-evolving agents are blocked by missing infrastructure, not algorithms. We verified it, then checked 40 years of self-improving systems. One rule survives.
- ·7 min read
A Frontier AI Model Went Dark for 19 Days. Build Like It Will Happen Again.
A podcast called June 2026 one of AI's most important months since ChatGPT. We checked every claim against primary sources. One thing is new, and it should change how you build.
- ·5 min read
Claude Fable 5 Moves to Usage Credits Tomorrow. Here Is the Part That Actually Matters to Builders.
The internet is full of leaked-prompt threads and architecture guesses about Anthropic's most capable model. Almost none of it is verifiable. The part a builder can actually use is four small API changes and one behavior worth watching, plus a working skill that handles all of them.
- ·9 min read
Should Your Website Be Ready for AI Agents Yet?
Mostly no, and the parts worth doing now are free. Here is the verified status of WebMCP and the agentic web, the readiness ladder, a ten-minute self-check, and the three trigger events that change the answer.
- ·7 min read
Why Does Your AI Know Every Fact but Fail the Combined Question?
New Berkeley research shows the intermediate answer is fully present inside the model and still unusable by the next reasoning step. Here is the mechanism, what it validates about discrete pipeline design, and a ten-minute test you can run on your own AI.
- ·10 min read
Why Does Your AI Keep Making the Same Mistake? We Audited Ours to Find Out.
Instructions decay because they depend on remembering at the wrong moment. Mechanisms remove the remembering. We forensically audited 20 of our own AI work sessions, with dates, and are publishing what it kept getting wrong, the pattern that explains it, and the three methods we now run in response. All three are published as copy-ready resources.
- ·8 min read
Claude Science Just Launched. The Useful Part Is How It's Built.
Anthropic's new research workbench is not a new model. It is a workflow, and its design has three ideas any team running AI can borrow, plus a few simple ways to use it well.