// consistency & standards
Why does every team use AI differently?
Because good practice lives in people, not in the system. Sage turns your standards, prompts and approval steps into shared workflows — so every team delivers the way your best engineer would.
// sound familiar?
Three signs quality depends on who’s on the project.
- 01Same task, very different output.Two engineers, two prompts, two levels of quality.
- 02Prompts live in personal setups.Or scattered across repo files nobody owns or reviews.
- 03Reviewers catch the same issues again and again.Your standards are checked by people, every time.
Why it happens: individual AI tools are built around one developer and one session. Nothing makes a team’s know-how shared, versioned or enforced.
// how sage fixes it
Your standards, encoded once and applied everywhere.
- prompt & skill storePrompts as owned, versioned assetsImproved once, published to every team, rolled back if needed.
- workflowsSame steps and gates for every teamStory to PR runs the same way across projects, configured per team where it matters.
- criticScored before anyone reviews itOutput is checked against your definition of done first, so reviewers focus on judgment.
Prompt library
// versioned org-wide · owners per prompt
promptversionowner
story-decompv1.5 publishedplatform
story-qualityv1.2 publishedquality
pr-critiquev0.9 publishedquality
diff-genv2.0 publishedplatform
Workflow Library
// shared across all projects
Add New Requirement
Linear issue → INVEST-checked stories
96%PR Review
project policy + team conventions
91%Modify Existing Logic
safe diff + regression tests
88%// from the Sage Runner demo · demo data