The emerging skillset of wielding coding agents — Beyang Liu, Sourcegraph / Amp

AI Coding Agents: Efficacy and Usage - Coding agents are substantively useful, though opinions vary on their best practices and applications [1] - The number one mistake people make with coding agents is using them the same way they used AI coding tools six months ago [1] - The evolution of frontier model capabilities drives distinct eras in generative AI, influencing application architecture [1] Design Decisions for Agentic LLMs - Agents should make edits to files without constant human approval [2] - The necessity of a thick client (e.g., forked VS Code) for manipulating LLMs is questionable [2] - The industry is moving beyond the "choose your own model" phase due to deeper coupling in agentic chains [2] - Fixed pricing models for agents introduce perverse incentives to use dumber models [2] - The Unix philosophy of composable tools will be more powerful than vertical integration [2] Best Practices and User Patterns - Power users write very long prompts to program LLMs effectively [4] - Directing agents to relevant context and feedback mechanisms is crucial [5] - Constructing front-end feedback loops (e.g., using Playwright and Storybook) accelerates development [6] - Agents can be used to better understand code, serving as an onboarding tool and enhancing code reviews [9][11] - Sub-agents are useful for longer, more complex tasks by preserving the context window [12][13]