Fine paths of evidence brought into focus through a glass lens

Help your agent improve
with every iteration.

A specialist shows where your agent falls short and what better looks like. Turn those findings into repeatable tests, automated changes and a focused follow-up review.

Start with an Expert Review. Add tests and automation when they fit your workflow.

Make decisions deliver resultsIXO Expert Reviews / For developers

Give the next version
a clearer target.

A useful review explains the task, the failure and the behavior a specialist expects. That gives your development agent something concrete to improve.

Keep the findings linked to the tested version and observed interactions. Reuse approved cases to check that each new change preserves what already works.

Human judgment.
A repeatable improvement loop.

Automate the experiments between reviews. Bring the specialist back to assess the changed behavior and identify the next useful improvement.

  1. Review real tasks.

    A specialist tests an agreed agent version, records what happened and explains what should change.

  2. Make the feedback testable.

    Translate findings into test cases and expected behavior. The specialist approves what a successful result means.

  3. Run bounded experiments.

    Your coding agent proposes changes. Evaluate them against fixed tests, regression checks and a budget you control.

  4. Review the difference.

    The specialist compares the results. You decide what to release. New findings inform the next cycle; resolved cases become regression tests.

See how a finding
becomes a better behavior.

A retail specialist tests a returns agent. The customer paid US$80 for a discounted item, but the agent attempts a US$100 refund before the customer confirms.

The feedback gives the developer two precise things to fix—and two tests to keep.

Illustrative example · not a measured result

From observation
to acceptance criteria

Expert finding
The amount is wrong. The action happens before confirmation.
Repeatable tests
Use the eligible paid amount. Do not execute the refund before explicit confirmation.
Target behavior
Propose US$80, explain the amount and wait for confirmation.
Follow-up review
Check the corrected behavior, its explanation and other scenarios that could be affected.

Build on tools
you can use today.

Keep your existing agent runtime. Add an evaluation harness and a coding agent around it, using open-source frameworks.

The developer guide shows what IXO supplies and what you connect in your own environment. Start with a manual review, add regression checks, then automate experiments when you are ready.

Inspect AI
Run the scenarios, score observed behavior and save the evidence for each experiment.
OpenHands
Propose code and configuration changes in an isolated development workspace.
Autoresearch pattern
Constrain the change, evaluate it, keep or reject it, then repeat within a fixed budget.
GEPA
An optional route for optimizing prompts and skills from scores and approved feedback.

Know what was reviewed.
Keep control of what ships.

Each finding belongs to a named specialist, a tested version and supporting observations. Check provenance and agree how the feedback may be used before feeding it into an optimizer.

Test the selected candidate on fresh cases outside the optimizer's workspace. A passing score supports the next review; you retain release approval.

The current pilot includes one review and one follow-up within the agreed scope. Automation setup, additional cases and further review cycles are agreed separately.

Put expert feedback
to work in your next iteration.

See what you receive, what to implement and how to connect the optional feedback loop.

Start with an Expert Review