Operations | Monitoring | ITSM | DevOps | Cloud

Most companies have built AI into their product by now, and many consider it the central feature of what they’re building. But plenty of those same companies are still figuring out how to get their own engineering teams to actually use AI tools day to day. When Loïc Houssier joined Superhuman as CTO in early 2025, his team was in that exact spot. The company had been shipping AI email features for years, but internal adoption of AI dev tools was still early.

Quick answer: IT cost reduction strategies target waste across three categories — cloud infrastructure, SaaS applications, and software licensing — without cutting the investments that drive business value. The highest-impact tactics are auditing unused SaaS licenses, rightsizing overprovisioned cloud resources, automating non-production environment shutdowns, extending commitment coverage on stable workloads, and building cost accountability into engineering workflows.

Platform engineering teams have access to hundreds of metrics, yet over 40% of platform initiatives cannot demonstrate measurable value within the first year. Teams that cannot quantify their impact fail to obtain executive sponsorship, risk being defunded, and ultimately, face deprecation. To accurately calculate a platform’s ROI, platform engineering teams need to differentiate between signals that measure platform effectiveness and those that should be used solely for investigative purposes.

Why did your build fail? Ask Rovo, get a clear answer, and even a way to fix it, from anywhere in Bitbucket Pipeline debugging is one of the most common and most painful parts of the development workflow. In our Atlassian research: AI adoption is rising, but friction persists, over 50% of developers reported losing more than 10 hours each week searching for information, onboarding to new code, or toggling between apps.

Tamar Bercovici has been at Box for 15 years. She leads the core platform, the backend layer that storage, search, metadata, and AI capabilities all run on. When her systems go down, Box goes down. On a recent episode of the Braintrust podcast, she said the debate around AI-generated code tends to focus on whether the models will write clean code and/or introduce bugs. Tamar's focus is somewhere else entirely.

A Kubernetes single pane of glass is a centralized management layer that unifies visibility, access control, cost allocation, and policy enforcement across § cluster in an enterprise fleet for all cloud providers. It replaces the fragmented practice of switching between AWS, GCP, and Azure consoles to govern infrastructure, giving platform teams a single source of truth for multi-cloud Kubernetes operations.