Operations | Monitoring | ITSM | DevOps | Cloud

Engineering teams are great at innovating and delivering products, but the work that's required to maintain them over time and keep them running well tends to get deprioritized. Planning processes are designed to move features forward, not to catch whether those features are generating too many alerts, degrading in performance, or creating compliance exposure over time. As a result, that class of work accumulates quietly.

In early February, Martin Fowler and the good folks at Thoughtworks sponsored a small, invite-only unconference in Deer Valley, Utah—birthplace of the Agile Manifesto—to talk about how software engineering is changing in the AI-native era. They recently published a summary of key insights and themes from the summit, sorted into ten topical buckets.

A feature that used to work suddenly broke. The problem? There were 300 commits since the last time I knew it worked. Checking each commit manually would take forever. Fortunately, Git has a tool designed exactly for this situation: git bisect.

In Part 1, we looked at how AI has reduced the cost of building monitoring tools. Then in Part 2, we explored the operational and economic burden of owning them. Now we need to talk about something deeper. Because the real shift isn’t just economic; it’s structural. AI isn’t just helping engineers write code faster. It’s accelerating the entire software ecosystem; including how monitoring tools are built, maintained, and trusted.

Cloud adoption has officially crossed a tipping point. In 2026, the conversation is shifting from whether companies are moving to the cloud to how complicated things are getting once they’ve moved. Hybrid architectures, multi-cloud strategies, AI workloads, and rising security pressure are turning “the cloud” into a web of interconnected environments. For IT and network teams, that creates huge opportunity—and plenty of room for chaos if visibility doesn’t keep pace.

Most people end up with a photo storage service the same way they end up with a dentist: whatever was closest and easiest. Google Photos is already on Android. iCloud is already on iPhone. OneDrive comes with Microsoft 365. Amazon bundles unlimited photo storage into Prime. None of them are bad, but none of them made you read the fine print either. The fine print is access. Google, Apple, Microsoft, and Amazon all hold the encryption keys to your photos.

As enterprise ITOps teams monitor increasingly complex, cloud-based, containerized systems, traditional observability practices are struggling to keep up. As IT infrastructure complexity increases, the typical response is to layer on more monitoring, logging, and instrumentation.