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Your Questions About AI-Assisted Development Answered

We recently hosted a webinar on AI-assisted development with DORA, and the audience had a lot of questions—far more than we could get to in an hour. I picked out six that get at the stuff people are wrestling with day to day. These aren't the easy questions, and I don't think there are necessarily easy answers, but I've spent the past year building and shipping with AI coding tools and observing (literally) what happens when that code hits production. Here's what I have.

Scaling AI Workflows With Proxy Infrastructure

AI workflows require consistent access to diverse data sources to maintain accuracy. How do teams guarantee that their systems do not go dead when rate limits are reached? The scaling of these processes is based on a stable connection layer that eliminates interruptions during retrieval. Writers are likely to have difficulties with their automated scripts triggering blocks on social sites. This article discusses the process of establishing a trustworthy machine learning and automation environment.

The Future is Faceless: Why Stock Footage is Dying in 2026

Remember the last time you searched for "diverse business team laughing at laptop" on a stock footage site? You scrolled past the same forced smiles, the same generic office backgrounds, and the same overacted "eureka" moments that have been circulating for a decade. Then you paid a subscription fee for the privilege of looking like every other brand on the planet. That era is ending. In 2026, stock footage is dying-not because we need fewer visuals, but because creators have finally found something better: total creative freedom without the cheesy middleman.

How to Build AI-Native Security Resilience (And Finally Get Developers And Security On The Same Team) | Harness Blog

Developers and security professionals have struggled to get on the same page for what seems like forever and AI is only making that divide larger, according to results from our State of AI-Native Application Security 2025 research report.

Hot Takes: What the AI Hype Gets Wrong About Software Engineering Excellence | Harness Blog

Ahead of the DevOps Modernization Summit, Matthew Skelton, CEO & CTO of Conflux shares his takes on output-driven AI, how DORA metrics aren’t enough, and why governance and compliance must be built into the platform. ‍ Matthew Skelton is the CEO & CTO of Conflux and a featured speaker at this year’s DevOps Modernization Summit. Ahead of our annual summit, Matthew has shared his hot takes on AI, DORA, and the key to successful automation.

7 Real Ways to Modernize NetOps with Kentik AI Advisor

Kentik’s AI Advisor acts as a virtual network engineer, helping teams of all skill levels troubleshoot, manage, and optimize their infrastructure with unprecedented speed and context. We explore seven practical NetOps use cases, from rapid incident triage and capacity planning to upcoming live-device command support, that demonstrate how using AI as a collaborative teammate dramatically reduces manual investigative work.

Skills vs. MCP: You're probably reaching for the wrong one

Everyone is adding Model Context Protocol (MCP) servers to everything right now. And I get it. MCP is clean. It’s standardized. You write a server, expose some tools, and suddenly your LLM can query your log platform, pull a dashboard, and fire an alert. It feels like the right abstraction. But I’ve watched teams at serious companies burn weeks building MCP integrations for workflows that should have been skills, and build skills for things that genuinely needed MCP.

Inside Pandora's Box: How CloudZero AI Hub Cracks Cloud Cost Intelligence

Years in the FinOps trenches taught me one thing: The data has never been the problem. The data exists. It’s out there, scattered across provider invoices, buried in tagging gaps, locked behind dashboards that maybe three people in your org actually know how to navigate. The real problem? Nobody can get to it when they need it. Engineers ship features without understanding what they cost the business, let alone whether they improved margin.

How does AI enhance search?

Explore how artificial intelligence enhances search engines through semantic understanding, vector embeddings, and contextual retrieval. Learn how AI-powered search delivers faster and more accurate results. Additional Resources: About Elastic Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform — the development platform used by thousands of companies, including more than 50% of the Fortune 500.