The Pulse
Entire Brings Continuous AI Code Evals to Trails
Entire’s Trails let teams configure review agents to score code changes on matching pushes. The scores, findings and agent-session history sit alongside the code as teams review changes.
AI.info Team · Written with AI · fact-checked ·
Entire’s Trails put review-agent scores at the center of a repeated review cycle for AI-written code. Agents run in cloud sandboxes and recalculate scores on matching pushes, rather than reviewing a change only once. Each agent returns a score and rationale, and the Trail displays the current run alongside the previous five. Teams can compare those runs to judge whether scores have stabilized before approving a change.
Trails Carry More Than the Diff
Entire frames Trails as an alternative to pull requests for agent-assisted coding. A pull request shows changed files, while the reasoning behind an agent’s changes may remain in a session on a developer’s local machine. A Trail can include the diff alongside agent sessions, checkpoints and a timeline of the work that produced it. That gives reviewers a view of both the code and the recorded process behind it.
The workflows differ in when they begin and how much code they can cover. A pull request starts when code is ready to push and covers one repository; a Trail can start before code exists, with intent and acceptance criteria, or from a branch, and can span multiple repositories. Each repository’s change is reviewed and merged separately. For repositories mirrored from GitHub, Entire reviews and GitHub reviews remain separate, and GitHub branch rules can still block a merge after Entire’s gates pass.
Preset Agents and a Migration-Risk Score
Teams can enable preset agents at the project level, then select the repositories and environment each agent should review. The presets described in the post include Code review, which flags work that needs fixing; Security review, which checks for changes that could lead to a breach; and Slop, which catches sloppy patterns and drift. Entire says presets can be enabled through its interface or CLI.
The post also walks through a custom agent for database migration risk. Its suggested review checks for destructive operations, long locks on large tables, compatibility between old and new application versions during deployment, and whether a down migration can restore the previous state without data loss. The agent is instructed to score risk from 0 to 100, with higher values indicating greater potential damage, and to cite the files and lines behind its rationale.
A push trigger does not run on every push by default: it runs when the trigger, repository selection, readiness condition and any branch or path filters match. The post says the default readiness condition is that a change is ready for review. Teams can also set an agent to run manually or on a recurring schedule.
Findings Need Review, Too
In the review loop, agents score the change and file findings; the coding agent then checks those findings, fixes serious issues and explains what can be dismissed before pushing again. Review agents rescore after that push. Entire’s interface shows the diff beside the findings, while the Trail’s sessions and timeline let reviewers inspect decisions made along the way.
Scores are one part of the merge signal, not a substitute for configured requirements. Entire describes that signal as stable scores, cleared findings and repository gates, which can include approvals and passing CI through its Buildkite and Depot integrations. The post also cautions that findings on changed code may become stale after a fix; stale findings are not automatically resolved or dismissed.