Validity Is What You Need
What is "Agentic AI" really? Sebastian Benthall and Andrew Clark argue it’s best seen as a software delivery mechanism—like SaaS—that lets an application work autonomously inside complex enterprises.
- Applications first: Agentic AI systems should be judged as products, not as foundation models.
- Validate with users: Success depends on measures that principal users and stakeholders can check in real workflows—very different from LLM benchmark scores.
- Simpler can win: Once you have solid validation, the core logic can often be handled by simpler, faster, more interpretable models.
- LLMs are a means, not the end: They’re one option to reach validated performance—not a requirement.
When it comes to Agentic AI, validity is what you need.
Bottom line: Build for operational validity, then choose the simplest tech that passes the bar.
Paper: http://arxiv.org/abs/2510.27628v1
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