A frontier model can write a function. An agentic runtime can read a codebase, plan a migration, edit forty files, run the tests, fix what broke, and open a pull request. The difference is not intelligence; it is the system that …
Anthropic stopped shipping a chatbot and started shipping an ecosystem. From Artifacts to Cowork to Design, the through-line is the same: move the model out of the chat box and into the work. For marketing teams, that change is n…
One workflow, 150,000 tokens down to 2,000. A subagent that burns fifty thousand tokens and returns fifteen hundred. A hundred installed skills that cost two thousand tokens until one is needed. Four separate advances, four separ…
Training a frontier model is a one-time expense measured in millions. Serving it to users is a perpetual expense measured in billions of tokens per day. For most organisations, inference is already the larger number, and the gap …
The most consequential AI release of late 2024 was not a model. It was a protocol. The story of how a single open standard ended the N-times-M integration nightmare is the story of every standard that ever mattered.
The industry frames every LLM feature as an agent. Most production systems that work are pipelines with one or two LLM steps and clear handoffs. Default to a workflow, reach for an agent only when the problem demands it.
The frameworks that demo best are rarely the ones that survive in production. LangGraph wins where it matters by refusing to hide the thing every other framework tries to hide: the control flow.