Tap

Tap / Resources / Archive

Insights on AI Adoption

Articles, guides, and research on building effective AI adoption strategies for engineering teams.

Lead Story / No. 1

01

Building the AI Adoption Engine: Our Vision for Tap

Article/February 2026/8 min read

Most organizations measure AI adoption by counting licenses. We believe the real signal lives in the conversations you're not having. Here's why we built Tap — and where we're taking it.

Read article →

Archive / Back Issues

02
Article

Why Engineering Teams Are Losing the AI Adoption Battle

Engineering teams have more AI tools than ever — and less clarity on whether they're working. The adoption battle isn't about technology. It's about the feedback loops that don't exist.

February 2026/7 min read
Read →
03
Article

From Surveys to Conversations: Rethinking Feedback

Survey response rates have plummeted from 36% to 6% over two decades. The era of checkbox feedback is ending — and what replaces it will reshape how organizations understand their people.

February 2026/7 min read
Read →
04
Guide

The Engineering Leader's Guide to Measuring AI Adoption

License counts and acceptance rates don't tell the full story. This guide breaks down the metrics that actually matter for understanding whether your AI investment is working.

February 2026/9 min read
Read →
05
Article

5 Signals Your AI Rollout Is Failing Silently

The most dangerous AI rollout failures don't show up in dashboards. They hide in the gap between what metrics say and what your teams actually experience. Here are the warning signs.

February 2026/6 min read
Read →

End of archive / 5 issues published