Operations | Monitoring | ITSM | DevOps | Cloud

Setting up crash reporting is rarely the most exciting part of shipping a game. Paste a DSN, flip a few checkboxes in Project Settings, turn on symbol upload, package a build, crash it on purpose and check that the event shows up in Sentry… It’s not hard to do (and important), but it’s the kind of work you’d happily hand off to someone else. With Unreal Engine 5.8, that someone else can be your coding agent.

TL;DR Most of the time we understand the tasks we're working on, but inevitably something comes up that we don't know much about, and we need just enough skill to cope. That used to mean reading paper documentation, then searching vendor sites and the web. Now it tends to mean a dialog with an LLM that has already ingested the documentation we don't have time to find and read. That's only half the problem, though.

Komodor spent years building an AI SRE platform before the category had a name. With the launch of the Komodor Agentic Operations Platform, it’s opening that engine up so enterprises can build, run, govern and optimize their own agents in production. Following the launch, co-founder and CEO Ben Ofiri sat down to talk about why now is the right time for agentic operations, what breaks between prototype and production, and where operations will head next.

The "C" word is a controversial subject in the US, but we have to talk about "context", and what it means to an AI Agent. For starters, agents can only act on what's in their context window. Everything outside of it is a guess. In application code that limit is usually an annoyance.

Western Canada is becoming a live test of whether sovereign AI capacity can be built responsibly at scale, and the answer will depend less on what operators promise than on what they can measure and show. Meta’s planned C$13-billion Alberta data center, BCE’s expansion of its Saskatchewan project to a 1.2-GW hub, and the federal Responsible Data Centre Development Principles all point to the same requirement: operational transparency that regulators, utilities, and communities can verify.

Are your support teams spending too much time handling tickets and answering repetitive questions? As support requests increase, teams spend more time reading conversations, assigning tickets, finding relevant information, and preparing replies. These tasks can take attention away from complex issues that require human support. AI help desk software can help reduce this workload. It can answer common questions, summarize tickets, suggest replies, route requests, and assist with support tasks.

As AI accelerates software development and expands its scale, Deutsche Bank is taking a leading role in ensuring the technology can be adopted safely, securely, and responsibly across regulated industries. As an investor, Deutsche Bank’s Corporate Venture Capital arm participated in Kosli’s Series A funding round, reinforcing the bank’s view that automated governance will be a key enabler of AI-assisted software delivery in regulated industries.

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.