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By Ritabrata Moitra
Rebuild AI API classification with Jev to cut costs, reduce latency, improve calibration, and make production decisions more efficient without sacrificing accuracy. Replacing the judgment step in a production classification pipeline with a purpose-built decision model changes the economics of the problem entirely.
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By Akshay Khole
Discover how software delivery knowledge graphs unify fragmented SDLC data, enable schema-as-code, and power deterministic AI reasoning across engineering teams. Software delivery knowledge graphs unify fragmented SDLC data across disparate tools by establishing explicit entities, typed relationships, and schema-as-code contracts. This transforms manual cross-system data stitching and non-deterministic AI reasoning into reliable, queryable knowledge. Key takeaways include.
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By Kelsey Rosen
Discover why engineers ignore cloud cost governance and how to build developer cost accountability. Learn how Harness helps empower engineering teams. Engineers often overlook cloud costs due to friction in traditional FinOps tools and a lack of real-time visibility. By embedding automated guardrails and shift-left cost insights into developer workflows, organizations can drive accountability without slowing velocity.
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By Renny Shen
SAST vs SCA vs DAST vs IAST: a clear breakdown of what each scan finds, when to run it, and how to combine them across your SDLC. Most AppSec teams don't run one type of scan - they run several, at different points in the pipeline, because no single tool sees the whole picture. This article breaks down SAST vs SCA vs DAST vs IAST: what each one actually tests, where it fits in the software development lifecycle (SDLC), and how to combine them without duplicating effort or drowning developers in findings.
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By Kelsey Rosen
Learn why engineers ignore cloud cost optimization and how to build a culture of FinOps governance. See how Harness helps. Engineers often overlook cloud costs due to lack of visibility, fragmented tooling, and competing delivery priorities. Organizations can fix this by embedding FinOps guardrails into developer workflows and providing real-time cost feedback during build cycles.
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By Renny Shen
Interactive Application Security Testing (IAST) finds vulnerabilities in running applications by monitoring code from the inside. Learn how it works and where it fits. Interactive Application Security Testing (IAST) is a method for finding security vulnerabilities in an application while it's running, by instrumenting the code and observing how it behaves during normal use or testing.
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By Eric Minick
Learn how to safely automate Oracle schema changes. Discover what makes Oracle database DevOps unique. Automating Oracle schema changes safely means considering what makes Oracle different. A real Oracle database DevOps practice pairs version-controlled changelogs and pipeline integration with policy-as-code protection, pre-flight checks, and tested rollback scripts, so schema changes deploy with the same speed and safety as application code.
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By Gabriel Acevedo
Compare LLM vulnerability scanners with AI SAST on precision, recall, speed, cost, and consistency to choose the right AI security approach.
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By Rohan Gupta
Harness Connector for OpenAI: Bring CI/CD Context to ChatGPT & Codex A pipeline fails while you are working through a change in ChatGPT or Codex. To understand what happened, you need the execution details, the failed step, and the relevant pipeline configuration. Gathering that context can interrupt the work you were doing before you can even begin to solve the problem. The Harness Connector for OpenAI brings that delivery context into your AI workflow.
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By Harness
Citrix NetScaler customers were pulling devices offline as attackers moved faster than the traditional patch and response cycle. What happens when cyberattacks move faster than security teams can react? In this episode of ShipTalk, Martin Reynolds and Adam Arellano are joined by Starr Brown, Director of Open Source Projects at OWASP, to break down the latest Citrix NetScaler ADC and Gateway security vulnerabilities, active exploitation, and the rapidly shrinking window between vulnerability discovery and attack.
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By Harness
An Alibaba-affiliated AI agent went full crypto bro. During reinforcement learning, the agent autonomously started mining cryptocurrency, downloaded the tools it needed, and created a reverse SSH tunnel to get around network restrictions. What starts as a funny story about an AI vaping and mining crypto gets a lot more serious when you realize how sophisticated the behavior actually was.
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By Harness
What happens when an AI agent can do more than suggest a fix — and actually take action inside your CI pipeline? See Harness Worker Agents in action as an AI agent identifies a failed CI build, determines what went wrong, creates the fix, and gets the pipeline moving toward production again. Worker Agents bring AI-powered reasoning directly into your software delivery pipelines while maintaining the controls enterprises need, including sandboxed execution, scoped credentials, policies, and RBAC.
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By Harness
Jev is a new AI model from Type Safe built around a very different idea: instead of generating long answers, it makes fast, simple decisions. The team reportedly even demoed it playing Doom using nothing but split-second choices. After years of teaching AI models to talk, could the next breakthrough be teaching them to simply decide?
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By Harness
See how Harness helps teams move from AI-generated code to production at machine speed. In this demo, Nick Durkin walks through a fully autonomous software delivery workflow inside Harness, showing how teams can review code, enforce policy, run security and LLM scanning, test intelligently, deploy agents, and use Change Advisor to automate approvals with human oversight when needed. You’ll see how Harness helps teams.
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By Harness
The “paperclip maximizer” was supposed to be a thought experiment about what could happen if AI relentlessly pursued a goal without understanding the consequences. Then Hugging Face showed us what that can look like in the real world. In this ShipTalk clip, Adam explains the famous AI paperclip maximizer thought experiment and connects it to what happened when an AI system needed more resources and found a way to get them.
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By Harness
AI for Development Isn't New. AI for Delivery Is! AI coding assistants have transformed how teams create software. But innovation only delivers business value when code moves quickly and safely from commit to production and into customers' hands. In AI-Native Software Delivery, Harness Field CTO Nick Durkin and DevOps veterans Eric Minick and Chinmay Gaikwad present a practical guide to applying AI across the entire software delivery lifecycle.
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By Harness
Organizations everywhere are racing to modernize DevOps and elevate the developer experience, but how close are they to actually delivering?We surveyed over 650 engineering leaders to find out. The result is The State of Software Engineering Excellence 2025, a report that uncovers the hidden challenges, gaps, and opportunities shaping today's software teams.
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By Harness
This comprehensive whitepaper shows you how modern software delivery platforms solve these challenges.
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By Harness
Modern systems are more complex-and more fragile-than ever before. Whether it's scaling challenges, dependency failures, or unpredictable outages, reliability is no longer optional. It's a competitive edge. This eBook provides a practical blueprint for successfully adopting Chaos Engineering, with strategies proven to work across engineering, SRE, and QA teams. Learn how to overcome internal blockers, align ownership, and embed resilience testing directly into your software delivery lifecycle.
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By Harness
You're adopting AI code generation tools to enhance your engineering team's output, but how do you quantify the real return on investment? Without precise measurement, you're navigating in the dark, unable to identify true productivity gains or pinpoint areas for optimization. Justifying these critical AI investments becomes difficult.
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Harness delivers intelligent AI automation, so your team ships code faster, safer, and smarter.
Don't let your pipeline become the bottleneck as developers and AI coding agents generate more code. Harness AI intelligently automates, safeguards, and accelerates software delivery at any scale.
- AI for DevOps & Automation: Unleash developer productivity with AI that understands your DevOps ecosystem. Harness combines the industry's fastest, most secure CI/CD with developer self-service to automate pipelines, infrastructure, and the entire path from code to production.
- AI for Testing & Resilience: Release software confidently using AI-powered predictive analytics and testing. Make every change fast, safe, and resilient, so your teams can focus on shipping quality code instead of chasing bugs and triaging outages.
- AI for Security & Compliance: Make secure software your new default. From application and API discovery to AI-powered threat prevention, Harness uses contextual insights and agentic workflows to detect and mitigate risks from build to post-deployment.
AI for Everything After Code.