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Building with AI: Our Approach to Responsible Agentic Development in Open Source

The tech world has been building up towards the shift to a fully agentic development life cycle for a few years now. AI is changing how software gets built. Across the Puppet ecosystem, we’re seeing a shift toward more agentic engineering workflows. AI helps generate code, shape documentation, and accelerate how Puppet modules evolve.

Ensuring Business Continuity in Adverse Conditions

Businesses will always face disruptions. Whether it's a big storm, a broken supply chain, or a power outage, unexpected problems can bring operations to a halt, hurting your income, your reputation, and how much customers trust you. The companies that make it through these tough times, and those that don't, often come down to one thing: resilience. Being a resilient organization isn't about building an unshakeable fortress. It's about being flexible, thinking ahead, and having the right systems to bounce back when disruptions occur.

The Failure Mode Your Runbook Probably Does Not Cover

Operations teams rehearse plenty of scenarios. Failed deployments, database corruption, certificate expiry, a region going dark, the on-call engineer who cannot be reached. What gets rehearsed far less often is the building losing power for eleven hours, because that feels like somebody else's problem, filed under facilities alongside the air conditioning and the parking barrier. It stops being somebody else's problem at the moment the UPS batteries drain and everything still running on premises goes down at once.

How to Build a Reliable Review Gate for AI Generated 3D Assets

A creative team generates twenty 3D props in an afternoon. The files look acceptable in preview images, so they are placed directly into the shared asset library. Days later, developers discover inconsistent scale, missing textures, reversed normals and several models with unclear ownership or revision status. The generation process worked. The production process did not.

Imaginary Test Data. Real Token Bill.

Ask an AI for K-pop concert advice without saying the group, city, date, or budget. It may confidently send you to a BLACKPINK tribute night in Cleveland with a $400 resale ticket. The AI was plenty confident. It just had nothing real to go on. That is exactly what happens when developers test AI applications with invented traffic. The test may look reasonable. The result may even pass.

Why AI Governance Is Now the Biggest Challenge for Enterprise AI

For the past couple of years, most conversations about AI in business have centered on adoption. Which tools should organizations deploy? Where can AI improve productivity? How quickly can it deliver value? Those questions still matter, but they are no longer the most difficult ones to answer. AI is now appearing across business applications, employee workflows, development environments, and customer-facing services.

Dynamic MCP Server Demo | Connect Claude to Enterprise Automation in Minutes

See how the new Dynamic MCP Server in Resolve Actions Pro 8.1 lets AI assistants like Claude discover and execute approved Resolve runbooks through the Model Context Protocol (MCP). Watch enterprise automation happen in real time with secure, auditable execution.

The Near-Term Wins in AI for NetOps Rest on the Same Foundation

Walk into a network operations center this year and the useful AI is not running the place. It is doing three specific jobs, and doing them well: cutting an alert storm down to the one incident that matters, pointing at the likely cause, and deciding what deserves a human’s attention first. That is where AI in NetOps pays for itself right now. The part worth noticing is that all three jobs lean on the same thing.

Guardrails for shipping with AI agents, feat. Luca Rossi of Refactoring.fm

Code review has always been a time sink. AI just makes the dysfunction undeniable. Luca Rossi, founder of Refactoring.fm and builder of the open source tool Tolaria, has been running one of engineering's most-read newsletters for five years, with over 170,000 subscribers. He's also been doing what a lot of engineering leaders talk about but rarely do: building a real product with AI agents to pressure-test what's actually possible today.