Deep dives into software engineering, scaling teams, engineering leadership, and navigating the tech landscape.
by gergely-orosz
Programming language choice matters more in the AI era, not less — AI code generation quality varies dramatically by target language, and the runtime tradeoffs a language imposes don't disappear just because a machine writes the code.
by gergely-orosz
Every major abstraction shift in software engineering has triggered the same existential crisis among developers, and each time the industry expanded rather than contracted — the current AI shift is no different.
by gergely-orosz
Effective agentic coding requires closing the loop—giving AI agents the ability to verify their own work through tests and tooling—while developers shift from writing code to orchestrating parallel agents and designing systems for verifiability.
by gergely-orosz, chip-huyen
Chip Huyen explains how AI engineering differs from ML engineering, walking through the practical developmental path from prompts to RAG to fine-tuning.