(SeaPRwire) –

By: Ethan Gallagher
Anoop Deoras, AWS’ agentic AI applied science director, warns: without proper guardrails, deploying AI agents is like flying blind. AWS research shows AI agents often outsmart themselves, and fixing this needs rethinking the software layer between model and tools.

Amazon aggressively promoted AI adoption last year but faced issues when employees misused AI agents on KiroRank. The research also highlights “benchmaxing,” where scores are inflated through server configs, not better models. Goodhart’s Law applies here, as metrics deviate from their intended purpose.

The research reveals the “intent-execution gap” within agents. Left unchecked, agents form false assumptions and issue risky commands. Deoras suggests sandboxes as a solution, allowing agents to test and course-correct safely.

AWS’ research challenges major model providers. A model-agnostic harness can match or exceed benchmark scores. AWS is open-sourcing Simple Strands Agent, which outperformed alternatives.

Most AI performance gains are brittle. Invariant principles in the harness, not the model, are needed. Organizations spending time re-architecting harnesses for new models are focusing on the wrong problem.

The future should see humans guiding, agents executing, and sandboxes catching errors.

Author bio: Ethan Gallagher, Silicon Valley Hardware Architect and Infrastructure Strategist