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Agentic NetOps: How to beat the cloud monsters at their own game

Feb 6, 2026 By Avi Freedman In Kentik

The secret to hyperscaler success isn’t magic. Kentik Co-founder and CEO Avi Freedman explains how organizations can adopt the same operating principles and empower network teams to drive results that far exceeds their headcount.

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How we built Grafana Assistant - a conversation about AI development for observability

Feb 6, 2026 By Grafana In Grafana

This conversation with Grafana Labs engineers, Mat Ryer, Cyril Tovena and Sven Großmann, dives deep into the engineering behind Grafana Assistant, exploring how agentic AI is transforming the observability landscape. From hackathon origins to sophisticated backend agents, the team shares candid lessons on building, scaling, and refining AI tools for engineers.

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How AI is democratizing video and what it means for your brand

Feb 6, 2026 By OpsMatters In OpsMatters

Video stopped being optional years ago. In 2026, 95% of marketers say video increases brand awareness, and 60% report it directly drives sales. But for small businesses and solo entrepreneurs, there's always been a gap between knowing video matters and actually making it. The costs, the learning curve, the time-it adds up fast.

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OpsMatters

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Operational Risks and Controls When Deploying Legal AI

Feb 6, 2026 By OpsMatters In OpsMatters

A law firm recently found that its AI tool had misread "limitation of liability" clauses for 6 months. No one noticed the mistake. The error only came to light when a client faced a huge insurance claim that the firm had promised was capped. The cost? That firm is now dealing with a malpractice lawsuit and a damaged reputation. Using AI in a law office poses risks beyond simple computer bugs. These tools mix technical errors with professional responsibility. As AI becomes a standard part of the job, firms without strict rules will face quality issues and legal trouble.

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OpsMatters

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Upsun's AI story: the 5% path from pilots to production value at scale

Feb 5, 2026 By Upsun In Upsun

Here’s the uncomfortable truth: most companies do not have an AI problem. They have a delivery problem wearing an AI costume. MIT’s Project NANDA research has been widely cited for a brutal headline statistic: roughly 95% of corporate generative AI pilots fail to produce measurable business impact or returns, while only about 5% break through to meaningful outcomes. (Yahoo Finance) The models are impressive. The demos are dazzling. The budgets are real.

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Intelligent FinOps: AI-Informed, AI-Enabled

Feb 5, 2026 By Thalia Elie In CloudZero

AI is the new frontier for FinOps maturity. It introduces fresh spend patterns and new opportunities for value. As GPUs, inference, and retraining reshape costs, FinOps maturity grows through visibility, forecasting, and shared mindset about how these workloads drive business impact. In this 2025 post, I gave my guidelines for implementing AI tagging to give business context and clarity to vague AI invoices. Now, I’m sharing the next level up: how to drive FinOps in AI with AI.

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Building an AI GitHub Maintainer

Feb 5, 2026 By Sentry In Sentry

In this stream, we're going to be building an application together from scratch using ShadCN, AI SDK, and Sentry. Today's goals.

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(Tech Talk) Shipping with Context Knowledge Graphs as the Backbone of AI-First Software Delivery

Feb 5, 2026 By Harness In Harness

Knowledge graphs are essential to solving the context bottleneck in AI-First software delivery, which occurs because workflows, policies, and dependencies are siloed and invisible to AI agents. In this Tech Talk, Prateek Mittal ((Product Director of AI Core and Data Platform at Harness)) discusses the key concepts: Knowledge Graphs vs. Observability: Observability tells you "what is happening," while knowledge graphs tell you "what does that mean" by modeling structured relationships. They work together to link live signals to affected services or SLAs.

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DevOps

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We Built an MCP Server

Feb 5, 2026 By Kubex In Densify

When I joined Kubex last year, the company was already well aware of the growing power of Large Language Models. As a company focused on intelligent resource optimization for Kubernetes, GPUs, and cloud infrastructure, generative AI didn’t feel like a threat so much as a natural extension of where the industry was heading. Kubex had already invested heavily in machine learning, but it was becoming clear that foundation models could unlock an entirely new class of capabilities for our customers.

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Densify

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Voice AI: The Missing Link in Your Agentforce Strategy

Feb 5, 2026 By iOPEX Technologies , In iOPEX

Despite the enterprise-wide pivot toward digital deflection, voice remains the primary escalation channel for high-complexity customer issues. Yet, while organizations rigorously optimize digital touchpoints, telephony frequently remains a siloed legacy endpoint, disconnected from the broader CRM architecture. This integration gap creates a strategic blind spot that fundamentally undermines your digital roadmap.

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