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cortex

Policy as code for AI coding: How to turn engineering standards into guardrails for AI agents

Oct 22, 2026 By Mike Vanbuskirk In Cortex
Key Takeaways Engineering standards exist in every organization. They cover how services communicate, how secrets are managed, who reviews changes before they merge, and what "production-ready" means. The problem is where those standards live: wiki pages, onboarding docs, the memory of whoever happens to review a pull request that day. Conventional enforcement depended on reviewer knowledge, which varied across teams.
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From iPhones to AI Servers: Foxconn's Second Act

From iPhones to AI Servers: Foxconn's Second Act

Oct 22, 2026 By OpsMatters In OpsMatters
The AI boom continues to redistribute revenue within the technology industry. If previously the main investment interest was focused on chip manufacturers and model developers, now companies that serve the infrastructure supporting this growth are becoming increasingly prominent. One of the main beneficiaries has been Foxconn, which is gradually transforming from the largest assembler of Apple devices into one of the key suppliers of server hardware for artificial intelligence.
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qovery

Where to Find GPU Capacity in 2026: Hyperscalers, Neoclouds and Regional Clouds

Oct 21, 2026 By Romaric Philogene In Qovery
Google, CoreWeave and Nebius all say they are short of GPUs. Here is where capacity still exists in 2026, which GPU clouds offer managed Kubernetes, how to connect a second cloud to your first one, and how to run GPU services on all of them from one platform. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.
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How to Actually Test AI Agents Before Production

Oct 21, 2026 By Resolve In Resolve
Fran Fernandez and Pramin Pradeep, co-founder and CEO of BotGauge AI, delve into how AI is changing software development, quality assurance, and enterprise IT. Pramin explains why faster AI-assisted coding has created new pressure on testing, why companies need visibility into every agent operating in their environment, and how red teaming, tracing, production observability, and human oversight can help organizations deploy agents safely.
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appsignal

AppSignal MCP Is Now a Claude Connector

Oct 21, 2026 By Serena Chou In AppSignal
AppSignal MCP went generally available last month. Until now, adding it to the Claude app meant pasting our endpoint URL into a custom connector form. Now you search for it like any other connector. Open Settings, go to Connectors, select the Discover tab, and search for AppSignal. That's the whole setup. For more detail on each step, follow the Claude app section of the setup guide. It works the same way in Claude on the web and in the desktop app..
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cloudzero

Shipped: Break down AI spend by your projects and teams, within minutes

Oct 21, 2026 By Kaitlin Woo In CloudZero
Your company talks about AI spend in its own terms, like projects, teams, and products. Now AI Signals can show AI spend in those terms, too. Write a CostFormation rule in CloudZero that groups AI spend by categories you care about, and the new breakdown appears in AI Signals the same day you decide to track it. There’s no waiting for a full processing cycle.
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harness

Bring Your Own Identity Provider to Harness MCP

Oct 21, 2026 By Piyush Patel In Harness
Learn how Harness MCP OAuth proxy mode enables enterprise developers to use their own identity provider without static tokens or shared credentials. OAuth proxy mode lets enterprises run Harness MCP behind their own identity provider, with no static tokens anywhere in the chain. Coding agents write the change. Harness agents take it through production, running the builds, tests, scans, and deployments that follow, with policy enforced on every action.
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Cycle

AI Changed How We Work. It Didn't Change What Your Platform Needs to Do.

Oct 21, 2026 By Cycle In Cycle
If you've spent any time in an engineering Slack lately, you've probably noticed that AI comes up in just about every conversation. Someone's using an assistant to scaffold a new service. Someone else has an agent triaging alerts overnight. And at least one person is asking whether all of this means the team can finally skip the "platform stuff.".
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iOPEX

Agentic AI Projects Die in the P&L Review. Here's How Revenue Leaders Can Keep Them Alive

Oct 21, 2026 By iOPEX Technologies , In iOPEX
‍‍Gartner expects more than 40% of agentic AI projects to be canceled by the end of 2027. Its reasons read like a budget memo: escalating costs, unclear business value, and inadequate risk controls. For revenue leaders, the stakes run in both directions. MGI Research estimates that at least 3% to 5% of revenue leaks between contract and cash, through missed renewals, unbilled usage, and pricing errors. Agents are well suited to close those gaps.
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logz.io

Introducing AI Observability: Trace Every AI Agent Request from Prompt to Pod

Oct 21, 2026 By Amos Etzion In logz.io
TL;DR Logz.io AI Observability provides end-to-end tracing for AI agents and LLM applications. Built on OpenTelemetry, it lets you trace every request from prompt to backend service, visualize multi-step agent execution, isolate root causes across models and infrastructure, and track token usage per step, all alongside your existing logs, metrics, and traces.
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