Zebra Technologies Helps Sentinel Cut Defect Rates by Up to 15% for Automotive Customers
Car makers are securing higher levels of customisation and precision at a lower cost with 3D and AI solutions.
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Why AI-driven automation in incident response is viable now
This article explains why AI-driven automation in incident response is feasible now. Teams can finally safely delegate repetitive and time-critical response tasks to AI Agents, which operate with contextual awareness and human oversight. The result is faster response, higher service uptime, and less alert noise – without losing control.
Ship Smarter Session: Connecting Cursor to CircleCI with MCP
Learn how to connect Cursor to CircleCI using MCP in this short demo. This video shows the workflow end to end so you can see how the integration works in practice.
Scaling Autonomous Operations with Agentic AI demo with Resolve
What does autonomous IT actually look like? This clip shows it in action. In this moment from our Scaling Autonomous Operations with Agentic AI webinar, RITA meets users where they work. Inside Slack. No portals. No tickets. Just answers. Watch RITA pull personalized knowledge in real time, synced directly from systems like SharePoint. Updates publish once and are instantly available everywhere. Then the real power kicks in.
When AI Speeds Up Change, Knowing First Becomes the Constraint
In a recent post, I argued that AI doesn’t fix weak engineering processes; rather it amplifies them. Strong review practices, clear ownership, and solid fundamentals still matter just as much when code is AI-assisted as when it’s not. That post sparked a follow-up question in the comments that’s worth sitting with: With AI speeding things up, how do teams realise something’s gone wrong before users do? It’s the right question to ask next.
Your Cloud Economics Pulse For January 2026
Welcome to January’s Cloud Economics Pulse, CloudZero’s monthly look at cloud spend as AI moves from vibe to prod. And this related news flash — AI spend keeps hitting new highs. pilots to production. In last month’s Pulse, we explored the compounding effect of AI becoming part of everyday cloud operations. This month, we see that pattern harden into year-end results.
4 foundations you need to scale AI in engineering
As a baseline, engineering leaders need their teams to adopt AI tools to speed up velocity and ship faster. Most organizations have already rolled out AI coding assistants or are evaluating them, but there's a really big difference between buying a tool and successfully scaling it across an engineering organization. If you layer AI on top of a chaotic codebase or a disorganized service catalog, you accelerate the creation of legacy code.
Breaking the Iron Triangle: How AI-powered investigations change the economics of uptime
In engineering, there's a concept known as the Iron Triangle. With three sides—cost, quality, time—it's a framework intended to help you prioritize different aspects of project management Want fast, high-quality features? It'll cost you. Need to keep costs down while maintaining quality? That'll take time. And if you're trying to move fast and cheap? Well, good luck with quality. For years, this has been the brutal reality of running services on the web.
The Technical Architecture Behind Automated Video Generation Systems
I spent several weeks last year reverse-engineering how automated content pipelines actually work. Not because I wanted to build one necessarily. But because the proliferation of AI-generated video content raised questions I could not answer without understanding the underlying systems. How do these pipelines function? What are their actual capabilities and limitations? Where does technology stand today?
Top Realistic AI Image Generators for Practical Business Use
The gap between AI image generation demos and actual business deployment remains wider than most vendors acknowledge. Marketing materials showcase stunning outputs. Operational reality involves inconsistent results, workflow friction and outputs that require significant human correction before they reach production. For operations leaders evaluating these tools, the question is not which generator produces the most impressive single image. The question is which tool delivers reliable, realistic outputs at scale without disrupting existing workflows or requiring specialized technical expertise.