Goatfied blog
Developer-to-developer writing. No fluff. Just what worked, what failed, and what shipped.
agent-loop
A validation checklist for autonomous AI coding agents covering constraint checks, testing gates, and code review steps before shipping to production.
agent-loop
Analysis of 10,000 agent failures reveals three core error patterns and the recovery strategies that prevent cascading failures in autonomous coding systems.
agent-loop
Deterministic validation layers prevent agent failures by checking tool call arguments, resource states, and operation compatibility before execution happens.
agent-loop
Learn how LLM context compaction selectively removes or summarizes information when token limits are reached, keeping AI agents effective during long tasks.
agent-loop
Agents need clear escalation rules to avoid wasting time on stuck tasks - this post covers detection signals and handoff patterns that prevent expensive retry loops.
agent-loop
Comparing AI coding agent architectures that plan changes before execution versus those that edit first and validate afterward, with tradeoffs for each approach.
agent-loop
Learn how to implement exponential backoff, retry budgets, and circuit breakers to build resilient AI agents that recover from failures without wasting tokens.
agent-loop
AI coding agents fail on sequential edits because they lack validation checkpoints between changes, causing cascading errors that compound across multi-step modifications.
agent-loop
Learn how agent loop verification gates systematically validate AI-generated code between creation and deployment to prevent hallucinations and incomplete implementations.
agent-loop
Inside Goatfied's autonomous agent loop — plan, constrain, edit, validate, retry — and why a compile-first gate is what makes AI-written code trustworthy in real repositories.
