@rohit4verse: Building dumb AI Loops that ship is the current MOAT in Agentic systems. 88% of agent pilots ship this exact pattern an…
Summary
The article discusses common failure patterns in agentic AI systems, specifically 'dumb AI loops,' citing issues like state poisoning and data leaks observed in Claude Code deployments.
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The AI world is getting ‘loopy’
The article discusses the rise of 'loops' in AI agentic systems, where agents continuously prompt other agents to perform tasks, as a major step beyond simple agent use. Boris Cherny of Claude Code endorses this approach at Meta's @Scale conference.
@akshay_pachaar: https://x.com/akshay_pachaar/status/2069118430582866051
This article explains the concept of loop engineering in AI agents, emphasizing that the core loop is trivial but the critical work lies in the harness around the model, including knowing when to stop and preventing context rot.
Agent loops are great until they learn from your worst code
This article discusses how AI coding agent loops can inadvertently learn and propagate deprecated code patterns from existing codebases, leading to technical debt despite appearing successful.
@akshay_pachaar: Andrej Karpathy: "Remove yourself as the bottleneck. Maximize your leverage. Put in very few tokens, and a huge amount …
A detailed breakdown of loop engineering for AI agents: moving from manual agent supervision to autonomous loops with triggers, makers, checkers, and persistent state. Recommends Zep's Graphiti for temporal knowledge graphs and Comet's Opik for observability to build reliable unattended agent systems.
@dmokafa: Most developers don't use agentic loops. But they are the best way to automate work with AI. Here's 8 tips on how to wr…
This article discusses the concept of agentic loops for automating work with AI, providing eight tips for writing quality loops, and introduces loop engineering as a method to reduce developer bottlenecks by designing systems that prompt agents automatically.