© 2026 Glue. All rights reserved.
Blog
AI agents, engineering automation, product intelligence, and how teams ship faster when their tools finally talk to each other.
Not all technical debt is created equal. Learn the 7 distinct types - from code debt to architecture debt to documentation debt - with real examples, detection methods, and remediation strategies for each.
Arjun Mehta
AI coding tools scale your existing patterns. They don't reduce debt. Here's what actually works: explicit refactoring, ADRs, and strategic modernization.
Principal Engineer
AI coding tools boost output 30% but increase defect density 40%. The math doesn't work. Here's what the data shows and what engineering leaders should do about it.
Why teams using GitHub Copilot, Cursor, and Claude ship 20% faster but see rising incidents. How to fix the architectural coherence problem.
Move beyond ticket-based technical debt tracking. Implement a full lifecycle approach: continuous detection, triage, prioritization, remediation, and verification.
Glue Team
Editorial Team
Stripe data: 17% of engineering capacity goes to debt. McKinsey: 25% slower velocity. Here's what it means for your team.
Calculate debt cost in dollars: velocity tax, incident cost, attrition risk. A framework and examples for engineering leaders and CTOs.
Vaibhav Verma
CTO & Co-founder
Track technical debt with structural, operational, and velocity signals. Measure debt continuously instead of one-time audits to manage engineering capacity.
How lack of codebase clarity compounds: opacity creates more opacity, slowing incidents, onboarding, and feature development. A quantified view.
A practical guide to reducing technical debt continuously. Avoid failed "debt quarters" with the strangler fig pattern and continuous improvement.
Measure code health through understandability, modifiability, and resilience. Learn metrics that correlate with engineering velocity and incident rates.
How to make technical debt measurable and tradeable in prioritization conversations with stakeholders.
Priya Shankar
Head of Product
Recognize the 7 concrete technical debt patterns that slow down engineering teams: dependency tangling, god objects, implicit contracts, test debt, configuration sprawl, parallel implementations, and documentation lag.
