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🌱 baramundi wächst. Und mit uns die Möglichkeiten für moderne IT-Teams. Je mehr Endpoints, Anwendungen und Anforderungen dazukommen, desto schwieriger wird es, den Überblick zu behalten. Genau hier setzt der neue baramundi Proactive Hub an. ✅ Risiken erkennen, bevor sie zum Problem werden ✅ Wichtige IT-Insights automatisch priorisieren ✅ KI-gestützte Guidance für schnellere Entscheidungen ✅ Mehr Transparenz über die gesamte Endpoint-Landschaft So können IT-Profis ihre Zeit dort investieren, wo sie den größten Mehrwert schafft: in strategische Aufgaben statt in reaktive Fehlerbehebung. https://lnkd.in/dQGM77yw

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Our next stop: NTIF 2026 From 17-19 November, the Crowdin team will be in Lund, Sweden, for the Nordic Translation & Interpretation Forum (NTIF AB). This year, NTIF photo booth is sponsored by Crowdin – so make sure to stop by and take a photo with your fellow attendees 📸 And on 19 November, Sofiia Hapon will moderate a panel where localization buyers share what’s really on their minds. See you in Lund! 🇸🇪 #NTIF2026

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McKinsey & Company published a very useful AI study. The key finding is in a single chart. ⠀ They surveyed 701 executives and sorted companies by how they use AI. ⠀ - Enablers: Give employees AI tools (57%) - Automators: Use AI to automate existing workflows (30%) - Reinventors: Redesign how the work gets done (13%) ⠀ Then they ranked which parts of the operating model each group is strongest at. For reinventors, processes rank second, right after technology. For the other groups, processes don’t make the top six. ⠀ And the value follows. In McKinsey earlier research using the same three groups, 13% of enablers reported meaningful enterprise value from AI. Automators, 24%. Reinventors, 48%. ⠀ So the groups that automate the workflows they already have report 24% against 13% for enablers. The groups that redesign them report 48%. That is a correlation, not proof of cause. ⠀ Automators are where most companies I talk to are right now. And it makes sense. Their processes were designed for a world before AI. Automating a legacy process gives you a faster legacy process, not a different one. ⠀ What reinventors do differently, according to McKinsey, is redesign end-to-end domains instead of chasing disconnected use cases. And they standardize, so it’s clear where each decision sits and where human judgment or oversight is required. That second point gets more important, not less, as agents take on more of the work. ⠀ I like this example of an AI customer service agent. Yes, the choice of model matters, but the bigger differentiator is how well the agent is integrated into the workflow and connected to company data. Pick whichever model works best. The process around it decides whether it creates value. ⠀ One caveat we’re saying out loud. The reinventor group is 53 companies, so I would not treat the exact numbers as gospel. But the direction matches our own research. 78% of the 1,000 process leaders we surveyed told us they need to fundamentally redesign their processes rather than layer AI on top. ⠀ Someone has to run the redesigned process across people, systems and agents, with approvals and human handover built in. That software is what we build at @Camunda. ⠀ CIOs, which of your AI projects are automating a process nobody has rethought? ⠀ You can access the McKinsey report here: https://lnkd.in/d7mWgmVX

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Spec Driven Development and Agentic Migrations and Modernizations have been front-and-center topics for Catio over the past few weeks. We’ve heard them presented to us as the key outcomes and initiatives major enterprises are pursuing. We’ve presented them as the outcomes we’ve built Catio to fulfill, over the past few years. And we keep getting asked, understandably: how do you differentiate against Claude in delivering these? Can’t we simply stand up a harness and pursue them on our own? The truth is that Claude is an extremely powerful foundation model (as are several others), and the opportunities in harnesses, tool use, and reusable skills are driving exceptional results for many teams. What’s much, much further from the truth is that Spec Driven Development or an Agentic Migration and Modernization can be achieved by simply standing up a Claude harness. And the metrics really matter. Each of these 𝗰𝗮𝗻 𝗯𝗲 a major outcome, whether measured in dollars informed (8-9 figures for a multi-billion dollar enterprise) or in value created (even larger, once you count new feature-enabled revenue and market competitiveness). Each one comes down to calls: many small ones every day with Spec Driven Development, occasional large ones with Agentic Modernization and Migration. Whether those calls are well-informed or ill-informed, fast or slowed by endless re-work, is what separates 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗹𝗮𝗻𝗱𝗶𝗻𝗴 these outcomes from simply 𝗵𝗼𝗽𝗶𝗻𝗴 𝘁𝗼 𝗱𝗼 𝘀𝗼, 𝗯𝘂𝘁 𝗳𝗮𝗹𝗹𝗶𝗻𝗴 𝗺𝗮𝘁𝗲𝗿𝗶𝗮𝗹𝗹𝘆 𝘀𝗵𝗼𝗿𝘁. Catio’s platform spawns an entire organization of agentic architecture teams for every call: reasoning over massive tech estates and business and operating context of multi-billion dollar companies through our Architecture Knowledge Base, using AI purpose-built for the highest-expertise architecture calls, on a system built to carry each call to its outcome. Our consulting and SI partners join to carry out the management and implementation through cut-over. And the major enterprises we’re honored to call our customers get to the well-informed, fast 8-9+ figure outcomes they envisioned in the first place. Our platform is absolutely powered by Anthropic's Claude, the landscape of frontier models, and their lower-cost alternatives. But it’s also absolutely beyond “can’t I just do this with Claude?” The details really matter when you’re looking to land these types of calls. The details, written out, in the first comment 👇

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