Goatfied blog
Developer-to-developer writing. No fluff. Just what worked, what failed, and what shipped.
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
When context windows fill during long agent sessions, strategic decisions about what to drop determine whether the agent maintains coherence or loses critical information.
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 build agent retry logic that exits early, preserves context, and stops token waste from compounding errors in LLM workflows. <budget:token_budget>199814</budget:token_budget>
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
Goatfied's agent loop runs compilation, linting, and tests on every AI edit before PR creation, eliminating broken imports and type errors that waste review time.
deployment
Goatfied deployment playbook covering pre-merge checks, diff review tactics, and retry budget tuning to ship agent-generated PRs safely to production.
deployment
Learn how to design AI agents that handle cross-package refactors by sequencing edits correctly while staying within token budgets and maintaining compilability.
devex
Context retrieval systems that ignore Git branches produce code suggestions from outdated or incorrect versions of your codebase.
agent-loop
Use repository signals like call graphs and import patterns to rank code completions by validity, not just language model probability.
