4 ways loop engineering fails (and how to fix them)

This video explains four common failure modes in AI loop engineering: runaway loops that burn tokens, unverified autonomy leading to confirmation bias, vague goals that make progress uncheckable, and complexity overflow requiring graph engineering. It's aimed at developers building agentic AI systems who want to avoid common pitfalls in loop-based architectures.