The Contradiction of AI Agent Workflows: Why Your Systems Might Be Breaking

The Agent Workflow Paradox

In this episode of Old School New Tech, host Ran Aroussi explores the inherent contradiction in building AI systems with agent workflows. He argues that combining autonomous agents with predetermined workflows creates complexity and brittleness, making these systems difficult to scale. Ran provides examples that highlight the pitfalls of this approach and advocates for a shift toward giving AI agents context and knowledge to enable reasoning and adaptability within defined guardrails, rather than rigid workflows. This episode is sponsored by Automaze, offering CTO-as-a-Service for startups and businesses.

00:00 Introduction to AI Contradictions
01:31 The Oxymoron of Agent Workflows
02:42 Concrete Example: Financial Service Incident
03:54 Guardrails vs. Workflows
05:24 The Alternative: Context and Knowledge
07:19 Evaluating Your AI Systems
09:19 Conclusion and Final Thoughts

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🎧 Brought to you by Automaze

This podcast is sponsored by Automaze, the fractional CTO partner for founders and operators. Whether you’re building a high-tech MVP or modernizing internal ops with AI and automation, Automaze can help you scale without the overhead of a full-time team.

Learn more: automaze.io