Exploring AI-native architecture where reasoning becomes infrastructure - from DAG execution to agentic systems that rethink how software works when thinking becomes cheap.
Moving beyond prompt engineering to context engineering - systematic optimization of LLM inputs through retrieval, memory systems, and RAG for maximum performance within context windows.
How reinforcement learning with adversarial training and domain randomization enables AI to master flight through trial and error - just like human pilots.
27 AI and ML terms explained for developers and everyone else.
A framework for explosive growth combining behavioral psychology, viral mechanics, and data-driven optimization.
Why disk-based orchestration beats fancy state management for multi-agent systems.
How we built a neural-symbolic hybrid system to control manned aircraft in real-time.
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