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Why Most AI Pilots Never Reach Production

Most AI initiatives never make it out of the pilot stage. Gartner has forecast that 30% of generative AI projects will be abandoned after proof of concept by the end of 2025, undone by poor data quality, weak controls, unclear business value, and escalating cost. The problem predates the current wave of generative tools. RAND's study of experienced practitioners found that more than 80% of AI projects fail, roughly twice the rate of IT projects that carry no AI component.

Why Modern Data Centers Require Better Insulation Strategies for Continuous Uptime

From streaming platforms to banking networks, today's digital demands rest on advanced facilities that operate without pause. With companies relying heavily on constant connectivity, stability within these environments matters more than ever before. A short disruption might result not only in monetary setbacks but also slower workflows and weakened confidence among users. Although computing hardware, climate controls, and emergency energy sources typically dominate discussions, protective layering quietly contributes just as much to seamless performance.

5 Top Rated LEI Registration Services That Will Save You Money in 2026

Securing a Legal Entity Identifier is pretty much a non-negotiable step to prepare your business for growth if you plan on trading globally. But let's be honest, regulatory compliance isn't exactly anyone's favorite budget line item. The good news is that keeping things legal in 2026 doesn't mean you have to overpay. Finding the right registration partner can actually save you a ton of cash on annual upkeep.

The Future of Digital Experience in Companies: What Changes with DEX, AI, and the Employee at the Center

For decades, companies measured IT efficiency through technical indicators: servers up, systems online, equipment working. But does that actually mean a good experience for the people doing the work?

How Agentic AI speeds up troubleshooting application issues

One night, Daniel Rizzy was the only person awake on Zylker’s IT team, and the clock was already running. He was also the only thing standing between a P1 outage and 10,000 customers. Rizzy works nights for ZylkerXchange, Zylker’s foreign currency exchange app. He lives on the city’s outskirts, where the air is clean and quiet, and the night shift suited that life. Most nights, nothing happened. Some nights, everything did.

Fix flaky tests with AI, and track future test work in Jira

In January we launched Tests in Bitbucket Pipelines – a single place to track, organize, and understand your test health over time. In April we added automatic flaky test detection so unreliable tests get flagged before they slow your team down. But spotting a problem is only half the battle. Day to day, your team still needs to act on a test – track it as work, clean it up, or route it to the right person.

AI Agents Write Broken Code 49% of the Time #speedscale #AI #Coding #Tech #DevOps

AI agents write broken code nearly 50% of the time. By adding a traffic-based deterministic evaluation, Speedscale boosted unsupervised bug-fixing quality from 51% to 77% in just 5 minutes. This helped slash token costs and eliminate rework without human intervention. Learn more: speedscale.com.

Harness Agents

Today, we're launching Autonomous Worker Agents, AI agents that run as governed pipeline steps inside Harness. They inherit OPA policies, RBAC, audit trails, and scoped credentials from the first run. And because they live inside your Harness pipelines, they reason using the Harness Knowledge Graph: your services, deployments, incidents, and policies.