🔗 Resources and example prompts:
💬 Community:
In this video I walk through how I use agent loops, goals, and scheduled automations in Claude Code and Codex for real AI coding work.
I break down the difference between prompts, goals, loops, and schedules, then show practical examples from my own workflow: scanning production logs, deploying an app to Google Cloud, working through GitHub issues, triaging a backlog, and keeping documentation in sync with code.
This is not about vague “agentic” hype. It is a practical guide to using loop engineering and goal-oriented workflows to get more useful, reliable work out of AI coding agents.
What you’ll learn:
– What agent loops and goals actually mean in Claude Code and Codex
– How Codex and Claude Code approach goals differently
– How to use scheduled automations for maintenance and monitoring
– When goals are useful for long-running coding tasks
– How to structure success criteria so an agent can verify its own work
– Where these workflows make sense, and where they are too risky
– How to think about cost, token usage, and the hype around loop engineering
🔗 Links
Resources and example prompts:
Community:
If this was useful, a like and subscribe genuinely helps the channel. Drop a comment with any Claude Code or Codex workflows you want me to cover next.
#ClaudeCode #Codex #OpenAICodex #AICoding #AIAgents #AIEngineering #SoftwareEngineering #AgenticCoding
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