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AI-Powered LMS: Personalization, Analytics & Automation for Corporate Training

AI-Powered LMS: Personalization, Analytics & Automation for Corporate Training

Feb 26, 2026 By OpsMatters In OpsMatters
Corporate training systems change operationally once AI is embedded into their learning logic. In LMS environments used for onboarding and workforce development, AI shifts training from scheduled delivery toward continuous adjustment based on employee performance and role context. This shift affects how companies assign onboarding programs, detect skill gaps, and maintain compliance readiness across departments.
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AI performance reviews for your app with the Flare CLI

Feb 25, 2026 By Freek Van der Herten In Oh Dear
The Flare CLI connects to your Flare performance monitoring data and uses AI to turn it into actionable insights, right from your terminal. In this video, you'll see how a single command pulls your real performance data from Flare, then generates a full review: identifying slow endpoints, spotting error trends, and suggesting concrete fixes. Links.
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observiq

Claude Code + OpenTelemetry: Per-Session Cost and Token Tracking

Feb 25, 2026 By Adnan Rahic In ObservIQ
I was looking at our Claude Code spend in the Anthropic console the other day. Aggregate cost, aggregate tokens — no breakdown by developer, no breakdown by session. I knew my Hackathon team had been using it heavily on building out new features for the OpenTelemetry Distro Builder. But heavily how? I had no idea. Turns out Claude Code has been emitting OpenTelemetry signals the whole time. Per-session cost, token counts, every tool call it makes on your codebase.
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upsun

AI infrastructure cost optimization for scaling teams

Feb 24, 2026 By Upsun In Upsun
This post is also available in German and in French. The 2026 AI landscape has shifted from "Can we build it?" to "How much will it cost to run it?" For CTOs and engineering leaders, the challenge is no longer just model performance: it is the underlying infrastructure sprawl that silently erodes margins. When AI workloads scale, they often inherit the inefficiencies of legacy cloud models: over-provisioned instances, fragmented data pipelines, and a lack of unified context.
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ivanti

How to Implement an AI Governance Framework Using Safe, Ethical and Reliable AI Guardrails

Feb 24, 2026 By Brooke Johnson In Ivanti
In my time at Ivanti, I've witnessed firsthand how AI acts as a force multiplier across enterprise organizations. When deployed strategically, AI accelerates decision-making and operational execution at scale in a way that teams simply can't sustain manually. However, without clear and enforceable AI guardrails, implementing AI opens organizations up to serious new risks.
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Secure by Design : Defend against AI-driven threats

Feb 24, 2026 By Ivanti In Ivanti
After several zero-day attacks on leading security vendors that left the industry reeling in 2024 and 2025, Ivanti redoubled our commitment to transparency, product development that prioritizes security and community awareness. The attacks galvanized our Secure by Design framework so that we could accelerate our transformation to kernel-level security — compressing a three-year roadmap into just 18 months.
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I let Claude investigate a production incident with Honeybadger's MCP server

Feb 24, 2026 By Honeybadger In Honeybadger
In this demo, Kevin shows how you can use Honeybadger's MCP server with Claude to investigate a production incident — going from a natural language prompt to a complete incident dashboard in minutes. Honeybadger is an application health monitoring platform that helps developers catch errors, track performance, and stay on top of incidents. The MCP server lets AI assistants like Claude query your Honeybadger data directly, so you can investigate issues conversationally without digging through dashboards manually.
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