The Agentic AI Paradox: Why Your Agents Are Failing Before They Even Start

This is awkward but….. Companies that build evaluation and orchestration infrastructure first are successful, while those rushing to production with powerful models fail at scale.

Non-Deterministic Nightmares

Traditional software engineering approaches don't work for AI agents. You can't predict every possible input or write comprehensive test cases for natural language interactions. Unlike traditional software that gives the same answer 1,000 times, AI agents are probabilistic—ask the same question and get different responses.

Treat Evaluation Like Unit Testing

"Before you even start building it, you should have an eval infrastructure in place. A very simplistic way of thinking about eval is that it's the unit tests for your agentic system," says Shailesh Nalawadi from Sendbird.

This isn't just about technical rigor—it's about business confidence. Rocket Companies saw three times higher conversion rates and saved over a million team hours in 2024, but only because they built the evaluation foundation first.

Simulate at Scale, Test Relentlessly

You can only find out problematic behaviors by simulating conversations at scale, pushing agents under thousands of different scenarios, and analyzing how they hold up. This requires:

📊 Rigorous testing environments that define what "good" looks like

🔄 Continuous evaluation loops that catch edge cases before customers do

⚡ Real-time monitoring for non-deterministic behavior patterns

🎪 Orchestration systems that route requests to the right agents under pressure

So.......

Legal and product teams building agents without evaluation infrastructure are essentially deploying software without unit tests. In a world where hundreds of agents per organization will soon be learning from each other, the stakes couldn't be higher.

The companies winning at agentic AI aren't just building smarter agents—they're building smarter testing. Start there, and everything else follows.

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https://venturebeat.com/ai/confidence-in-agentic-ai-why-eval-infrastructure-must-come-first/