Skill Distillation
How a personal AI agent built on markdown skills lets a frontier model teach smaller, local models to do real work, without retraining.
How a personal AI agent built on markdown skills lets a frontier model teach smaller, local models to do real work, without retraining.
Software is no longer about UX & data. It is about the harness, the layer that turns an LLM into a reliable agent. Seven components define the new stack.
If data gravity defined the last decade, agent gravity will define this one. As AI agents become the primary interface to enterprise data, the platforms that run them will capture an outsized share of value — & they're already locking the doors.
Salesforce and others are going headless. AI is making the user interface plastic — malleable to whatever the user needs, when they need it. The head isn't disappearing, it's becoming formless.
Three years of LLM pricing data: flagship prices dropped, then flipped upward, while budget models bounced back. Tokenizer efficiency softened the headline, but real costs are rising.
Why AI editorial councils fail & what makes writing authentic in an age of machine-generated prose.
The fastest growing companies in AI & software all share one property. They are either selling AI directly, or they are reselling inference. At worst, the first derivative of inference.
State-of-the-art AI email costs $22-130/month, but smaller models & local inference can cut costs by 100x. The next 12-24 months will be defined by matching models to workloads.
Email volumes will explode. The inbox will disappear. Email will persist as an API.
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