Automate Incident Intake and Start Response in Seconds | Harness Blog
Manual intake eats the first 10 to 30 minutes of an incident. Harness AI SRE runs it as automation and gives those minutes back to your responders.
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Zero Day to Fix: Why Security Response Speed-Not Discovery-Is Your Real Bottleneck | Harness Blog
Here's the uncomfortable truth about the Mythos era: knowing about a vulnerability and being able to neutralize it are two entirely different problems. AI models like Mythos are finding vulnerabilities 10x faster than humans ever could. Project Glasswing participants discovered over 10,000 high and critical vulnerabilities in their applications. Firefox alone had 271 previously unknown zero-days exposed by Mythos. That's the good news.
When Your SQL Table Outgrows Itself: Lessons from Refactoring at Scale | Harness Blog
At Harness, we build an AI-powered software delivery platform, and test result data is core to how we help engineering teams ship faster. The table that stores it started small: one row per record, all the context right there on the row. Simple, readable, and it worked. Until it didn't. This is the story of how we refactored it, what we learned, and what I'd tell you to watch for in your own systems.
AI Models ESCAPE OpenAI, Target Internet! SCARY
What happens when AI agents can operate faster than humans can monitor them? In this clip, we discuss the risks of autonomous AI systems, why human oversight may not be enough, and the growing need for machines that can monitor other machines.
Claude Code + Harness | Software Delivery for the Agent Era
Claude Code changes how fast software gets written. Harness changes whether you can trust what shipped. In this video, watch how autonomous AI agents handle end-to-end bug fixing, security remediation, and deployment verification—all within an automated Harness pipeline. From reading a ticket to running canary deployments and self-healing broken manifests, see how engineering teams can deliver software faster without sacrificing quality or security.
Chaos Hub in docs, Prompt Library for MCP: what's new in Resilience Testing | Harness Blog
The latest Resilience Testing documentation update brings Chaos Hub directly into the docs, making it easier to discover and use fault, probe, and action templates. It also introduces a Prompt Library with ready-to-use AI prompts for Harness MCP, helping teams run resilience workflows faster using natural language.
AI SAST Explained: Why Traditional Application Security Is Reaching Its Breaking Point | Harness Blog
AI has fundamentally changed software development. Developers are writing more code than ever. AI coding assistants can generate features, tests, documentation, and infrastructure configurations in minutes. Engineering organizations are seeing meaningful productivity gains as AI becomes embedded throughout the software development lifecycle. But there is a catch. Security teams now face a difficult reality: application security was already struggling to keep pace with software delivery before AI arrived.
AI's BIGGEST Problem, They're Losing Money!
For every $1 you pay OpenAI or Anthropic, it's costing them about $1.60. AI is running at a loss — so is the whole business model broken? The full bill for AI hasn't landed yet. In this ShipTalk short, Field CTOs Adam and Martin break down the economics of generative AI: why the frontier labs lose money on every prompt, why they'd need to raise prices ~60% just to break even, and the bet the entire industry is making — that inference costs drop fast enough to catch up. Plus the Gartner forecast every CFO should see: by 2028, the AI bill could be bigger than the employment bill.
Why Cloud Cost Visibility at Scale Fails (And How to Fix It) | Harness Blog
Cloud cost visibility at scale usually works great… until it suddenly doesn’t. At first, everything feels manageable. You can track spend by service. You know which team owns which resources. Reports are clean, and the numbers make sense. Then one day, there’s a $47,000 spike spread across three AWS accounts that no one noticed for eleven days. Leadership wants answers. Engineering wants context. And your carefully designed tagging strategy?
How to automate artifact cleanup in Harness Artifact Registry without breaking production | Harness Blog
AI is changing artifact management in two ways at once. Every AI-generated pull request, dependency update, and automated build creates more container images, packages, and Helm charts than ever before. Registries are growing faster than engineering teams can manage them, driving up storage costs and leaving thousands of stale artifacts behind. At the same time, the cost of deleting the wrong artifact has never been higher.