🛠️Microsoft Open-Sources ASSERT for Spec-Driven AI Tests
TL;DR
Microsoft released ASSERT, an open-source eval framework that turns plain-English policies into scored regression tests for AI agents. It generates adversarial scenarios, runs them against the system, and logs every tool call so failures are diagnosable.
Microsoft released ASSERT, an open-source eval framework that turns plain-English policies into scored regression tests for AI agents. It generates adversarial scenarios, runs them against the system, and logs every tool call so failures are diagnosable.
Key Points
ASSERT = Adaptive Spec-driven Scoring for Evaluation and Regression Testing
Input is natural-language behavior specs; output is a graded suite with acceptable/unacceptable expectations
Records intermediate tool calls and agent paths so engineers can pinpoint the failing step
Targets app-specific behavior that public benchmarks miss
Why It Matters
Most AI teams ship evals as throwaway scripts. A reusable spec-to-test framework from Microsoft moves agent evaluation toward the discipline of unit testing, with regression catches built in.
Quick Facts
Frequently Asked Questions
Why does this matter?
Most AI teams ship evals as throwaway scripts. A reusable spec-to-test framework from Microsoft moves agent evaluation toward the discipline of unit testing, with regression catches built in.
What happened?
Microsoft released ASSERT, an open-source eval framework that turns plain-English policies into scored regression tests for AI agents. It generates adversarial scenarios, runs them against the system, and logs every tool call so failures are diagnosable.
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