Buyer readiness
What to check before installing an AI capability
A practical framework for understanding fit, permissions, evidence, limitations, and recovery before adding an AI capability to a workflow.
Caporia Editorial Team
Writing, evidence review, and visual QA
6 minute read
Start with the job, not the feature list
A capability should solve a specific problem in a specific environment. Before comparing features, write down the workflow it would enter, the people or systems it would affect, and what a useful result would look like.
- • Who will use or supervise it?
- • Which environment must it support?
- • What would make the installation unsuccessful?
Understand the permissions
Permissions describe what a capability may reach, not what it will necessarily do in every run. Project or source-file access can expose confidential code, credentials accidentally committed to a repository, customer information, and trade secrets.
- • Does it read project or source files?
- • Can it write, delete, execute, or make network requests?
- • Can its access be narrowed or revoked?
Separate evidence from assertion
Publisher descriptions are valuable, but they remain publisher assertions unless another clearly identified process has independently observed or reproduced them. Look for the source, date, scope, and limitations of each important claim.
Plan for failure and removal
Installation is only one part of the lifecycle. A buyer should also understand updates, rollback, data retention, support, and removal before the capability becomes a dependency.
- • What changes during installation?
- • What happens when a run is interrupted?
- • How can the capability and its data be removed?
Claim boundary
This article explains an evaluation framework. It does not certify a capability, guarantee compatibility or outcomes, or replace security, legal, or professional review.