Glue for Engineering Leaders
See technical debt, knowledge risks, and team dependencies across your entire codebase. Make the invisible visible — without another meeting.
Your codebase, fully visible
Scroll through to see how each capability serves engineering leaders.
See where technical debt actually lives
23-42% of development time goes to tech debt maintenance, but you can't quantify WHERE it lives or WHO owns it. Glue makes the invisible visible — hotspots, complexity, churn, and ownership mapped across your entire codebase.
Map knowledge risk before it's a crisis
When a senior engineer leaves, the team's efficiency drops for six months. Glue maps who knows what across your codebase — commit history, file ownership, and contribution patterns — so you see bus factor risks before they become emergencies.
Onboard engineers in weeks, not months
New developers take 3-6 months to be productive. They spend weeks reading outdated docs and asking "just ask Sarah" questions. Glue gives new hires a living guide to the codebase — ask anything, understand anything — from day one.
Plan sprints with real data
Sprint planning without dependency visibility is a "scientific, wild-ass guess." Glue shows the exact files a change will touch, the dependencies involved, and the patterns to follow — before anyone estimates.
Visualize your architecture
Understand how everything connects. Interactive dependency graphs, call chains, and module boundaries — all auto-generated from your actual code. No manual diagramming required.
The engineering productivity gap
on maintenance toil
Developers spend 17 hours per week on debugging, refactoring, and understanding existing code.
Source: Stripe Developer Coefficient
speed reduction from debt
Technical debt reduces development speed by 30%.
Source: Kong
of IT budgets on maintenance
Almost 40% of IT budgets consumed by technical debt maintenance.
Source: Kong
feel undertrained at onboarding
63% of remote workers report feeling undertrained during onboarding.
Source: Jellyfish
searching for solutions
Developers spend 30+ minutes daily searching for solutions to technical problems.
Source: Stack Overflow 2024
of work hours on documentation
Only 11% of developer work hours go to documentation — the rest is tribal knowledge.
Source: Stack Overflow
Everything you get as an EM
Complexity scoring
Cyclomatic complexity, file size, and nesting depth scored per file.
Churn analysis
Files changed most frequently are often the most fragile. Track churn patterns.
Leadership-ready reports
Communicate tech health to non-technical stakeholders with data they understand.
Bus factor = 1 alerts
See which modules depend on a single person — before they give notice.
Contribution analysis
Understand team strengths across features, languages, and system layers.
Knowledge transfer planning
Proactively spread knowledge before it walks out the door.
Self-serve answers
New engineers ask the codebase directly instead of interrupting senior staff.
Living documentation
Feature discovery and code intelligence update automatically as code changes.
Cut ramp time 4x
From 6 months to 6 weeks. Onboarding cost drops from $240K to near zero.
File-level impact analysis
Know exactly which files a feature touches before the sprint starts.
Dependency visibility
See upstream and downstream dependencies before committing to timelines.
AI dev plans
Implementation plans with specific files, patterns, and risks.
Interactive graphs
Click through dependency trees and call chains visually.
Auto-generated
No manual Mermaid diagrams. Architecture maps come from real code analysis.
Always current
Re-index and your diagrams update. No stale architecture docs.
Stop flying blind on your own codebase.