Gaia 2.10 — Evals v2 Make Quality Repeatable

Quality decisions should be explainable and repeatable. That only happens when evaluation workflows are built into daily operations.

With Gaia 2.10, Evals v2 moved from basic scoring into a fuller quality system.

The Problem: Evaluation Needed Better Structure

Teams frequently struggled with:

• uneven evaluation schemas,
• noisy metric interpretation,
• and limited generation workflows for realistic task sets.

Gaia 2.10 addresses these gaps with stronger evaluation foundations.

Richer Evaluation Schemas and CRUD Workflows

What shipped

Gaia 2.10 introduced expanded schemas and broader CRUD coverage across evaluation assets and runs.

Why this matters

Consistent structure keeps quality checks stable across projects. It also improves comparability between iterations.

Better Task Set and Generation Flows

What shipped

Task generation and test-set workflows were expanded to support more practical evaluation pipelines.

Why this matters

Reliable quality control needs realistic datasets. Improved generation flows lower the overhead of maintaining useful eval coverage.

Metrics Handling That Supports Decisions

What shipped

Gaia 2.10 improved metric handling and surfaced clearer quality signals through evaluation workflows.

Why this matters

Metrics are only useful when they lead to decisions. Clearer signals help teams decide when to iterate and when to ship.

Looking Ahead

Gaia 2.11 built on this with tool-use grading, user simulator generation, error analysis improvements, and stronger operator support through live tutorials, a reorganized user guide, and the new AI Engineer Handbook.

Gaia 2.10 makes quality workflows repeatable. Gaia 2.11 makes them easier to operate, explain, and teach.