
Wax On, Weights Off: Knowledge Distillation Explained
What it is, how it works, why it saves money, and why it is rapidly reframing the US-China AI race
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What it is, how it works, why it saves money, and why it is rapidly reframing the US-China AI race

Fighting digital wars in virtual orbits with knowledge transfer into capital markets.

When Letting LLMs Write the Simulator Matters More Than Letting Them Play

A guide to tokenmaxxing AI costs in your organization

Recursive AI & neurosymbolic memory: how RLMs and symbolic architectures solve long-context reasoning for production AI agents.

A feedback loop that closes on the system's own implementation, not just its outputs. Five levels of self-correction. META, reinforcement learning, Q-learning

How intent-based filtering and RegEx-driven context extraction deliver 40–70% token reduction and better answers in agent systems.

I haven’t written about space for too long a time.

this essay explores how we truly learn, by doing, and why that insight matters for the future of AI and knowledge work. As the shift from search engines to answer engines accelerates, a new paradigm emerges: cowork engines powered by “skills.” These structured, procedural workflows transform AI from passive responder to active collaborator. Using real-world examples like evolving developer tools,…

The Value of Software Development Is (near) Zero