@seclink: Developers are shifting from "one-shot prompts" to "agentic loops"—where AI like Anthropic's Claude sets its own goals, uses tools to execute actions, observes results, and iterates until the task succeeds. Boris Chern, developer of Claude Code...
Summary
Developers are moving from one-shot prompts to an 'agentic loop' model, letting AI autonomously set goals and iteratively execute tasks using tools. Claude Code developer Boris Cherny has abandoned traditional IDEs entirely, now running hundreds of agents to monitor issues and merge PRs—even doing so from his phone.
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Developers are shifting from “one-shot prompts” to “agentic loops”—where AI models like Anthropic’s Claude set their own goals, use tools to execute actions, observe results, and iterate until tasks succeed.
Claude Code developer Boris Cherny has completely abandoned the traditional integrated development environment (IDE), instead running hundreds of such agents to monitor issues and merge up to 150 pull requests (PRs)—even doing all this from his phone.
Anthropic’s free video resources (such as Cherny’s 28-minute demo and a 24-minute “Prompting Primer” workshop) teach these techniques even better than paid courses, though critics note that without proper safeguards, this approach can carry risks like high token costs.
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@dotey: https://x.com/dotey/status/2074347810619543722
This article introduces the definition and classification of AI agent loops by the Claude Code team, including turn-based, goal-oriented, time-based, and proactive loops, and provides practical advice on controlling token consumption and ensuring code quality.