Instructions that guide.
Examine how the project explains conventions, boundaries and commands. Identify what needs to be accessible to guide the work.
Explore the platform
Your AI needs context. Is your codebase ready?
Releezy Advisor helps identify what makes agent work harder in your repository. Turn gaps in instructions, documentation and validation into engineering priorities.
Agent capability meets project reality.
Make the knowledge execution depends on explicit. Repository preparation is part of AI adoption.
Validation that gives direction.
Look at the tests and checks that help assess a change. Discuss gaps that make technical feedback harder.
Documentation that connects.
Find opportunities to connect architecture, decisions and code usage. Give the team priorities for improving that context.
From a gap to preparation work.
Releezy Advisor helps organize the assessment. Technical leadership chooses what to address first to support AI-assisted work.
Choose a repository.
Start with a project where the team wants to expand agent use.
Examine the foundations.
Investigate instructions, documentation and ways to validate changes in the code context.
Prioritize preparation.
Turn areas of concern into tasks and agree with the team on how to assess improvement.
Prepare the project for its next step.
How does Advisor differ from Reviewer?
Releezy Advisor looks at repository preparation. Releezy Reviewer analyzes changes presented in a pull request.
How does this analysis help AI adoption?
It helps identify missing context and checks in the project. The team uses that reading to better prepare work delegated to agents.
Where do we start?
With a repository and a concrete team difficulty. Let’s discuss the context and analysis scope that makes sense for your project.
Prepare the ground for better AI work.
Bring a repository and the challenge your team faces when using agents.