Recommender Systems 101 (2) Recommendation Strategy
A practical overview of recommendation strategies, from matching objectives to ranking and user experience tradeoffs.
Archives
Archives
A language-filtered archive view with dates, summaries, and topic cues.
Recommender Systems 101 (1) Introduction to Recommender Systems
A map of modern recommendation systems from retrieval and ranking to re-ranking, data layers, and evaluation.
Context Management
*Earlier in this chapter, [How Coding Agents Work](how-agents-work.md) showed you the agent loop: read context → plan → act → observe → repeat. The quality of that loop depends almost entirely on the "read context" step. Get context right, and agents produce remarkable work. Get it wrong, and no…
How Coding Agents Work
*In [Chapter 1](../01-prompt/README.md), you learned to communicate with coding agents — giving them context, writing clear prompts, and building persistent memory systems. Now, let's look under the hood: what actually happens when you press Enter?* *From simple autocomplete to autonomous digital…
Human-Agent Collaboration Modes
Coding agents do not remove engineering judgment. They amplify it. The practical skill is knowing when to explore with an agent, when to turn intent into a spec, when to let the agent execute, and when to slow down for verification. The old question was whether you should "vibe code" or "spec…