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#Multi-agent

0 items today
10/4Sun
  1. DEV Community · Vibe Coding38

    Coding agents are like steroids: what bodybuilding can teach us about the risks of AI coding tools

    Some developers have drawn the analogy that coding agents are like steroids in bodybuilding: they let beginners achieve with ease what used to take enormous effort, and let experienced professionals produce workloads that were previously impossible. But these code-generation agents carry medium- and long-term risks, and amateurs and beginners should wait until they hit their own "natural limit" before considering using them.

9/5Sat
  1. Ryan Lopopolo66

    An agent platform built for inventing agents: decoupling capability interfaces from their implementations

    Author Ryan Lopopolo argues that an agent is a parameterized program built on top of a set of capabilities: models and configurations, reasoning and tool-call loops, computers, disks, context, Skills, tools, connectors, runtimes, network policies, identity, IAM, guardrails, I/O channels, and system prompts.

    Why it matters: Drawing on his experience building multiple agents, the author proposes a platform architecture that decouples capability interfaces from their implementations — a useful reference for teams building Agent platforms.

7/22Wed
  1. Augment Code · Blog62

    What is loop engineering, and how are leading software engineering teams using it?

    Augment Code proposes loop engineering: designing agent loops that run from trigger to execution to validation to outcome, with agents handling the intermediate steps and humans stepping in only at checkpoints that require judgment. The article compares loop engineering with prompt engineering and context engineering as distinct layers, lays out five stages—trigger, execution, validation, outcome, and improvement—and describes four team-level loops already running in production: code review, ticket-to-PR, vulnerability remediation, and incident response.

    Why it matters: Augment Code breaks loop engineering into five stages—trigger, execution, validation, outcome, and improvement—and lays out four team-level loop patterns already running in production.