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Juggling AI tools works, until it does not

Sep 30, 2026 By Upsun In Upsun

This isn't a teardown. This stack is a genuinely reasonable way to start. An AI-first editor handles day-to-day writing. A terminal-based coding agent takes on tasks that need more autonomy: a full feature, a migration, a stubborn bug. A few scripts connect the pieces, trigger a run, and post a result somewhere. An observability tool checks what happened after the fact. Every part of that is a real, capable tool. For the first few months, on a small team, it works.

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Elevate Employee Digital Experience with ignio AI.Digital Workspace

Sep 30, 2026 By Digitate In Digitate

Every workday runs on digital experience, so what happens when logins are slow, devices lag and IT is buried in alerts? See how ignio AI.Digital Workspace from Digitate helps IT teams predict, prevent, remediate and assure a great digital employee experience.

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Realtime transaction fraud detection - with an LLM?

Sep 30, 2026 By Rob Gibbon In Canonical

Conversational AI with a chatbot is great for drafting emails or debugging code, but it’s less ideal for real-time application middleware. If you’re trying to inspect a financial transaction for potential fraud in the middle of a checkout loop, you don’t need an LLM to write you an essay about why a credit card transaction looks suspicious – you just need a probability score, and you need it as fast as possible.

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Watch this AI agent find and fix performance bottlenecks

Sep 30, 2026 By Upsun In Upsun

Anyone can claim an AI agent will fix your performance problems. This demo shows exactly what it looks at and what it hands back. In this Product Highlights conversation, Sylvain Guittard, Senior Director of Product at Upsun who leads the team behind the Upsun console and CLI, runs the Upsun Cloud Performance Agent live on a demo project. His take: "You have a patch that is already available, and a recommendation, so you can see if it fits or not to your context." We get into.

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5 Top Vendors for Building Production-Ready AI Agents

Sep 30, 2026 By OpsMatters In OpsMatters

Building an AI agent that completes an impressive task in a development environment is increasingly straightforward. Building one that an enterprise is willing to let operate repeatedly against production systems is a different engineering problem.

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OpenAI outage on September 14, 2026: "some tools are temporarily unavailable" errors hit ChatGPT worldwide

Sep 29, 2026 By Colin Bartlett In StatusGator

ChatGPT’s tools and workspace features failed for users around the world on September 14, 2026, with the message “Some tools are temporarily unavailable” blocking spreadsheet and document creation, Codex, Projects, file reading, and dictation while core chat largely kept working. StatusGator sent an Early Warning Signal at 14:41 UTC, 1 hour and 17 minutes before OpenAI publicly acknowledged the incident at 15:58 UTC.

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Map a Service in Your CMDB With AI Suggestions

Sep 29, 2026 By InvGate In InvGate

See how to create a Business Application in InvGate Asset Management and map the Configuration Items (CIs) behind any service using AI-powered relationship suggestions. Add one CI, let the system suggest what connects to it, and apply the suggestions to build your map in a couple of clicks. It also identifies the type of each relationship, so the map reflects how your infrastructure actually works.

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Big improvements to Seer Agent

Sep 29, 2026 By Peter McCarron In Sentry

Today marks exactly five months since we launched Seer Agent, our friendly AI agent for querying all things in your Sentry projects (well, five months and a day ago, but close enough). Since then, we’ve had a lot of chats with Seer Agent. You may have even seen a few of them popping up on social media recently. It’s become an integral part of our debugging workflows and feature iteration process.

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Agents Need Context: Introducing Canvas Connectors, Fleet-wide AI Agent Visibility, and More

Sep 29, 2026 By Dan Juengst In Honeycomb

Earlier this year, we introduced more capabilities to support agents in production, a more chaotic, complex environment that requires a tremendous amount of context to understand. Unlike tools that capture shallow, pre-aggregated metrics, or cannot join a metric, trace, and log in one query, Honeycomb retains the context and connective tissue from telemetry data to build a nuanced view of production.

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Introducing AI Ecosystem: Zoom Out to See Your Whole AI Agent Fleet

Sep 29, 2026 By Dan Juengst In Honeycomb

A few months ago, we launched Agent Timeline to close the gap between knowing an agent failed and understanding why. It took the tangled reality of a multi-agent, multi-trace workflow and rendered it as a single, readable conversation: every LLM call, tool invocation, handoff, and downstream system span laid out in the order they happened.

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