Operations | Monitoring | ITSM | DevOps | Cloud

Escaping the AI Tokenomics Trap in Enterprise IT

AI adoption has accelerated faster than most organizations expected. What started with chatbots has quickly evolved into AI systems capable of making decisions across enterprise environments, with the promise of faster service and more efficient teams. But many organizations are discovering an unexpected challenge: as AI usage expands, costs become harder to predict. Most AI platforms operate on token-based pricing models.

Introducing Upsun Dispatch

AI has made writing code fast, and you can feel it. Commits are up, pull requests are up, new repos spin up over a weekend, and your engineers swear they are faster. But where are all the new products? If every team really got faster, the software you use every day should be getting visibly better. AI helped your engineers ship more code. It didn't help your team ship more products.

Stop Treating Coding Agent Plugins Like Settings: Introducing Agent Plugins Repositories

Your developers install agent plugins every day: pulling from unmanaged GitHub repos, copying Cursor commands out of Slack, pointing Codex at a personal Git fork. Each of those is a new, uncontrolled distribution channel inside your software development lifecycle, and your platform team has zero visibility into any of it. A plugin is not a preference file. It is executable software, and right now it’s arriving on developer machines with no versioning, no provenance, and no audit trail.

Stop Token Maxing The Future of Al Budget Management

The era of token maxing is over. When Claude Fable 5 launched last week at $10/$50 per million tokens - double the price of Opus 4.8 - it was a clear reminder that the most powerful model isn't always the right model. Not every task needs the Ferrari. The fastest way to burn your Al budget is sending every request to the most expensive model by default. The real question for the next phase of Al cost management isn't "can this model do the job?" — it's "is it the right model for the job?".

Anthropic Holds Safety Talks With U.S. Officials Following Mythos Launch

Advanced AI systems now present a new threat for governments seeking to protect their national security interests, and Claude Mythos, Anthropic's latest high-capability model, has reportedly drawn increased attention from U.S. officials. The White House is currently working to establish a safety agreement with the company, which would help address technology-related safety risks, according to reports from Reuters, Axios, and other news outlets.

Who's in Charge? The 4 Key Pillars of AI Governance in 2026

You hire an astute, hard-working, fresh graduate to run things for you. You hand them the keys to everything in your company; that includes every system, every endpoint, every file, and every password, all of it. Your only instruction to them? "Go ahead and improve things!" Then, trusting in their competence, you leave them to it. Doesn't that sound like a recipe for disaster? Yet that's precisely what's happening in IT departments across the world.

An introduction to Zebra's AI for the Frontline | Zebra

Zebra Technologies is at the forefront of AI innovation for frontline workers. In this video Daniel Park discusses how Zebra is integrating AI across devices and tools to guide employees to the "next best action" within their workflows, improving real-time efficiency and decision-making on the frontline. We explore how our brand-new fleet of mobile computers—including the TC501 and TC701—are designed from the ground up for on-device AI. Equipped with advanced memory and dedicated Neural Processing Units (NPUs), these devices process data locally at lightning-fast speeds.