Blog
What the Top 1% of Developers Build With Claude Code Dynamic Workflows
Multi-agent orchestration is here. HoneyBook collapsed 10 Jira round-trips to one. incident.io runs 4-7 concurrent agents. Anthropic engineers no longer write code. Here is what they are all doing.
Google's New Lighthouse Audit Scores How AI Agents See Your Site
Lighthouse now has an Agentic Browsing category. It audits llms.txt, WebMCP integration, and AI accessibility — not for humans, but for the agents navigating your site.
The Best Agent Evals Come From Production Failures, Not Design Sessions
Most teams spend weeks designing agent evals from scratch. The ones that build better agents discover them from real traces and real failures. Here is what that actually looks like.
OpenAI Just Went Full Palantir
OpenAI's Tomoro acquisition is not a consultancy buy. It is the Palantir model applied to frontier AI, and it is the smartest enterprise move OpenAI has made.
AI Models Are Now Copying Themselves Across Machines. Here Is What I Check Before Any Agent Gets Shell Access.
The Palisade self-replication finding was not a surprise. This is the five-point pre-production security checklist I use before any agent goes to production, including a specific hardening guide for Microsoft Semantic Kernel and Azure AI Agent Service.
Context Window Engineering: How Anthropic Thinks About Production AI Agents
Brad Abrams, Anthropic Head of Product for Claude Platform, shares three context window engineering techniques that cut agent costs by 90% and boost model intelligence. Here is what I took away.
Context Window Engineering Implementation: A Production Guide to All Five Anthropic Techniques
Context window engineering implementation guide covering all five Anthropic techniques: prompt caching, tool search, programmatic tool calling, compaction, and the advisor strategy. Real SDK code included.
The 90-Day Playbook for Teams That Shipped AI Agents Too Fast
64% of enterprise teams deployed AI agents before they felt ready. Here is the practical 90-day sequence to harden what is already running — inventory, guardrails, observability, and attribution.
From Prompt Engineering to Programmatic Optimization: A Practical DSPy Primer
DSPy 3.2.1 ships optimizer chaining — you can now chain prompt and weight optimizers in a single pipeline. This is what that means for your LLM stack and when you should use it.
Graphify Hit 450K Downloads in 26 Days. Here's Why the Economics of AI Coding Just Changed.
Knowledge graph context retrieval using Leiden community detection claims 71x fewer tokens per query. If that holds at enterprise scale, the cost problem that has been quietly killing agentic coding programs is solved.