About Machine Learning One
Technical writing at the intersection of AI research and software engineering.
Machine Learning One is implementation-level writing about AI systems. Not surveys or literature reviews — the kind of detailed engineering writing that comes from building real systems and learning where they break.
Each series picks one problem space and goes deep: architecture decisions, working code, failure modes, and the trade-offs that only become visible when you build the thing for real. The reader is someone who writes code, reads source, and cares about understanding why before choosing an approach.
What to expect
Long-form technical series. Real code, real failure modes, real trade-offs. Each chapter builds on the last.