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system designAgent Harness Explained: The Core of Reliable AI Loops

Learn what an agent harness is, why it matters, and how it supports memory, tools, loops, tracing, and evaluation.

reliability safetyAgent Loop Retry Patterns for Reliable Autonomous Systems

Learn how agent loop retry patterns work, when to use them, and how to avoid runaway failures in autonomous AI systems.

system designAgent Loop Stop Conditions: How to Make Loops End Safely

Learn how to choose stop conditions for agent loops, avoid runaway execution, and design reliable termination behavior.

system designAgent Loop Token Budget: How to Control Context Cost

Learn why agent loops get expensive and how to constrain context with pruning, resets, subagents, and summaries.

system designAI Agent Evaluation Loop: Build Reliable Systems

Learn how AI agent evaluation loops combine tracing, rubrics, and fixes to improve reliability and reduce guesswork.

reliability safetyAI Agent Loop Guardrails: Where to Place Them

Learn where to place guardrails in AI agent loops, what they block, and how to balance safety, context, and latency.

system designAI Agent Loop Memory: How to Design Reliable Agents

A practical guide to memory, loops, retrieval, evaluation, and traces in autonomous AI agent systems.

fundamentalsAI Agent Loop: How Autonomous Agents Iterate Safely

Learn what an AI agent loop is, how it works, and when to use it for reliable multi-step agent behavior.

system designContext Management for Reliable Agent Loops

Learn how to manage context in agent loops with state, store, tools, middleware, and lifecycle guardrails.

fundamentalsHow Loop Engineering Works: The Practical Model

A clear guide to loop engineering, its core components, and when autonomous agent loops are worth using.

reliability safetyHuman Approval in an AI Agent Loop: A Practical Guide

Learn when to insert human approval into an AI agent loop to improve safety, accuracy, and recovery from errors.

comparisonsHuman-in-the-Loop vs Autonomous Agents: Key Trade-offs

Compare human-in-the-loop and autonomous agents, including when to use each, safety risks, and how MCP supports safer autonomy.

fundamentalsLoop Engineering Benefits: Why Agent Loops Matter

Learn the main benefits of loop engineering, when to use it, and where it breaks down in real AI agent workflows.

reliability safetyLoop Engineering Failure Modes: A Practical Guide

Learn the main failure modes of autonomous AI loops and how to design safer, more reliable systems.

workflowsLoop Engineering in Claude Code: Reliable Agent Loops

Learn how Claude Code loop engineering works, when to use goals and loops, and how to keep long-running agents safe and reliable.

workflowsLoop Engineering in Codex: Building Reliable Agent Loops

Learn how loop engineering works in Codex and similar agent tools, including automations, worktrees, skills, connectors, and sub-agents.

system designLoop Engineering Observability for Reliable AI Agent Loops

Learn how observability makes AI agent loops transparent, debuggable, and safer to operate in real software systems.

reliability safetyLoop Engineering Security: Safe Guardrails for AI Agents

How to secure loop-based AI agent workflows with verification, isolation, permissions, and human review.

comparisonsLoop Engineering vs Context Engineering: What Changes

Compare loop engineering and context engineering, with clear use cases, trade-offs, and when each pattern matters most.

comparisonsLoop Engineering vs Harness Engineering: Key Differences

Learn how loop engineering and harness engineering differ, when each matters, and why reliable agents need both.

comparisonsLoop Engineering vs Prompt Engineering Explained

A practical comparison of loop engineering and prompt engineering, including when each approach fits and where the trade-offs begin.

comparisonsLoop Engineering vs Vibe Coding: What’s the Difference?

Compare loop engineering and vibe coding, with practical guidance on when each works and where each breaks down.

workflowsSpec-Driven Development for AI Agents

How SPEC.md, agent context, and MCP tools create safer AI-assisted workflows from build time to runtime diagnostics.

workflowsTest-Driven AI Agent Loops for Reliable Workflows

A practical guide to building, testing, releasing, and observing AI agent loops without treating them like deterministic software.

workflowsWhat a Ralph Wiggum Loop Is in Autonomous Workflows

A practical explanation of the Ralph loop pattern for single-task autonomous agent workflows.

fundamentalsWhat Is a Loop Engineer? A Practical Guide

Learn what loop engineering means, how it differs from prompting, and when to use it for reliable AI agent workflows.

fundamentalsWhat Is Loop Engineering? A Practical Guide

Learn what loop engineering is, how it works, and when to use it for autonomous AI agent workflows.