Isolating Risk: Why 5,000-Line PRs Are Dead (Even With AI)
The real unlock is flagging what actually needs human review, not shipping 5,000-line PRs and hoping for the best.
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Canonical announces live kernel patching for Arm64
Canonical Livepatch now officially supports Arm64, further expanding its security patching automation capabilities. For the first time, Ubuntu on an Arm64 machine can apply critical kernel updates, without service interruption or rebooting. Starting with Ubuntu Core 26 for Arm64, and for Ubuntu Core 20 and onwards for AMD64 machines, a wider range of devices and cloud virtual machines can achieve timely vulnerability remediation through Canonical Livepatch.
Inside the Buyer's Decision: Governance, Trust, and Production-Ready Agentic AI
Why do so many AI pilots succeed in testing but fail to reach production? In this webinar, Resolve and IT leaders from RisePoint explore one of the biggest challenges facing enterprise AI adoption today: trust. While organizations are investing heavily in AI agents and automation, many initiatives stall before deployment due to governance concerns, compliance requirements, risk management, and lack of operational visibility.
The software supply chain threat landscape - 2026 and beyond
AI is accelerating both sides of the supply chain problem. Developers ship faster using it. Attackers use it to find vulnerabilities, create malicious packages, and automate social engineering.
What is an AI software factory?
Ask a software engineer what they do and the answer, for years, has been some version of "I write code." That assumption is unwinding fast. AI agents can now write code, review pull requests, run tests, and ship to production, and they're taking on a fast-growing share of that work. As agents absorb more of the execution, the human role shifts.
The New Software Creator: Why AI Changes the Governance Problem, Not Just the Speed Problem
The conversation about AI and software development has mostly been about velocity. Developers write code faster. Pull requests ship sooner. Backlogs shrink. That part is real, and it matters. But there's a bigger shift happening underneath it, and most engineering leaders I talk to are only just starting to feel its weight. AI hasn't just made developers faster. It has fundamentally expanded who can create and ship software. That changes things in ways that velocity metrics don't capture.
Cut your environment setup time in half with Chunk sidecar snapshots
When you’re building with AI, you can get a lot done in 30 seconds. Waiting minutes for CI feedback on your latest change can feel like an eternity. Chunk sidecars are designed to give you feedback fast, running your full test suite against the same Linux environment as CI, directly inside the agentic loop. Traditional CI pipelines can take five or ten minutes to catch a basic lint error or failing unit test.
Featured Post
From firefighting to forward planning: a practical route to operational innovation
Operational innovation is often treated as a back-office efficiency exercise, but in practice, it is becoming a strategic discipline. As AI moves deeper into day-to-day operations, technical leaders need a clearer way to cut toil, reduce risk and build the capacity to innovate. For many operations teams, it starts with incident management. When responders are trapped in noisy alert streams, manual escalations and fragmented workflows, innovation is pushed aside by the urgent work of keeping services available.
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Five things your logs will never tell you
A customer escalation hit my queue when I was on the customer smoke jumpers team at an observability vendor. My team was the group that parachutes into Fortune 500 accounts one bad week from churning and usually after a big customer outage. The customer had filed a billing dispute three weeks earlier and their on-call engineers were stuck. They had our full stack: logs, metrics, traces, end-to-end instrumentation, every product we sold and some we didn't. They could see the request came in. They could see it returned a 500. They could not see the body. The trace was sampled out. The log line was truncated at 4KB.
How to track business expenses in 2026: methods, tools, and AI spend
How to track expenses for a business: categorize expense types (operating, software, cloud, travel, capital), choose a tracking method (spreadsheet, accounting software, expense management tool, or cost intelligence platform), connect data sources (bank feeds, cloud billing APIs, SaaS invoices), assign ownership per cost center, set a reporting schedule, and audit quarterly.