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Is jouw bedrijf al klaar voor de verplichte tijdsregistratie vanaf 2027? Tijdens ons gratis webinar op 27 oktober geven we je concrete handvaten om je organisatie hierop voor te bereiden. Schrijf je vandaag nog in via onze website. 👇

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See how Indeed turned its existing graph into a governed foundation for AI agents, without rewriting a single API.

See how N-able turned its existing graph into a governed foundation for AI agents, without rewriting a single API.

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CX ekipleri müşteri memnuniyetini ölçmekte zorlanmıyor. Zorlandıkları soru şu: bu memnuniyetin şirkete finansal karşılığı ne? CX & AI Day 2026'da tam bunu konuşuyoruz — müşteri deneyimi yatırımının yönetim kuruluna nasıl anlatılacağını, hangi göstergelerle savunulacağını. 24 Eylül 2026 · Shangri-La Bosphorus İstanbul · 13:00–18:00 Ekibinizle katılın: 3 ve üzeri katılımda kurumsal indirim uyguluyoruz.

Most companies already have a growing list of ideas for AI agents. The difficult part is working out which ideas are actually worth pursuing. In conversations with customers and prospects at Automation Anywhere, the challenge is rarely a shortage of ideas. It’s deciding where AI can make a meaningful difference. “Where can we use an AI agent?” sounds like a sensible question. But start there and you risk using expensive, variable technology for work that automation could already handle perfectly well. Or improving one task without changing the performance of the process around it. Before choosing the technology, there are four things I’d want to understand about the work: → The outcome matters Improving it would make a real difference to cost, revenue, risk, service or speed. → Exceptions keep changing the route The standard process works until something happens that sends it down a different path. → Decisions need context The next step depends on what has already happened, what the information means and, sometimes, a judgement call. → People are keeping the process moving They move between systems, bring information together and sort out what the standard process can’t handle. An important outcome may justify investment. It doesn’t automatically justify AI. If the work follows stable rules, automation may be enough. If the route keeps changing and decisions depend on context, that’s where AI reasoning could help. If people are carrying information between systems, the bigger need may be orchestration. And some decisions should still belong to people. Start with the whole workflow. Then choose the right approach for each part of it.

Deflection can improve the numbers without solving the problem. The conversation ends, but the employee may still be waiting for access, software or a fix. Download the Playbook to move ITSM from ticket deflection to end-to-end resolution.

Şikayet yönetimi kurulu olan şirketlerde bile müşterilerin çoğu yaşadığı sorunu hiç iletmiyor. Sessizce gidiyor. Oysa o sinyaller kayıp değil — çağrı kayıtlarında, sohbet metinlerinde, anketlerin açık uçlu cevaplarında duruyor. Yapay zekâ bunları duyabiliyor. CX & AI Day 2026'da nasıl yapıldığını gerçek örneklerle konuşuyoruz. 24 Eylül 2026 · Shangri-La Bosphorus İstanbul · 13:00–18:00 Ekibinizle katılın: 3 ve üzeri katılımda kurumsal indirim.

The response to Tuesday's release has made one thing clear: engineering teams are tired of AI agents breaking UI code they weren't asked to touch. With median PR review times surging and production incident risks tripling across the industry, teams are realizing you can't fix an AI code generation boom with manual reviews or fragile test scripts. As an engineering leader at a major European travel platform, put it: "Applitools gives our developers greater confidence that AI-authored UI code aligns with our designs and meets our visual quality standards before reaching production." Want to see how this works under the hood? Join CTO & Co-Founder Adam Carmi on Thursday, September 24 for a live, unvarnished walkthrough. He’ll demonstrate how the Eyes MCP tools give Claude, Cursor, and Copilot visual "eyes" to catch collateral bugs, fix CSS regressions, and resolve baselines—all without leaving the IDE. Reserve your spot: https://lnkd.in/e7fC6Fxv

Curious how Kafka and Axoniq work together? Kafka moves messages fast, but it doesn't keep them. Most topics roll off after a retention window, by design. Axoniq isn't here to replace that; it's just the other half of the equation. Keep Kafka as your real-time distribution bus. Let Axon Server hold the permanent, replayable history: every business decision, any system state reconstructable from any point in time. The Kafka Extension wires the two together, no duct tape required. It gives your team real-time speed, plus a memory that holds. 🤝 Read how they fit: https://lnkd.in/etq8tseR/?utm_campaign=August-2026-WV-Finance-Tier1-LinkedInEngaged&utm_source=linkedin&utm_medium=paid&utm_id=1188901356&hsa_acc=516475204&hsa_cam=1188901356&hsa_grp=864571366&hsa_ad=1584168486&hsa_net=linkedin&hsa_ver=3 #Kafka #AxonServer #AxoniqFramework #EventStore

Most agent frameworks give you a clean way to push session events into a vector store and run similarity search, which may be good enough for a lot of use cases. But as Marc Klefter put it: most memory implementations take you far, then miss the sweet spot in the middle. That sweet spot is episodic memory as a first-class artifact, modeled in domain terms by humans, not summarized from technical logs by an LLM after the fact. Which is exactly what event sourcing already produces. Marc walks through the event-sourced memory layer on the Axoniq stack: Axon Server as the canonical event store, projections (analytical queries, application views, context graphs) surfaced to the agent as MCP tools, plus four freshness guarantees (least latency, max age, read-your-writes, snapshot-at) so the agent can reason about how stale its data is instead of guessing. Worth a read if you're building agents into production systems: https://lnkd.in/g66HD3r7 #SoftwareArchitecture #EventSourcing #AxonServer #Axoniq #LLM

The absolute worst time to plan your work day is 9:00 AM. After 16 years of running a productivity company, people expect me to have a super sophisticated system for keeping track of what I need to do. You might expect to see automated multi-app pipelines, multiple AI agents, intricate tag hierarchies, and color-coded priority flags. After all, I do have a dozen or so patents in productivity tools. But my entire system runs on a simple kanban board named “Mise-en-place” bookmarked from my browser toolbar. The inspiration comes from professional kitchens. Mise en place means every ingredient is chopped, measured, and arranged at your station before you ever light the burner. I adopted it from a Trello template a few years ago and refined it since. The minute we built Kanban in GQueues, I migrated. It’s been the first thing I open every morning. Eight columns: Inbox, This Week, Tomorrow, Today, Review, Waiting, Done, and Reference. On Monday morning, I spend ten minutes scanning Inbox, where raw thoughts and incoming requests land during the week. I decide what actually needs to get done and move those items into This Week. Every afternoon before I log off, I run the shutdown routine: First, I move finished tasks into Done. Second, unfinished items. I try to not let tasks rot in Today overnight. They get scheduled for Tomorrow, pushed back into This Week, or sent back to Inbox if priorities shifted. Third, I stage tomorrow. I look at my calendar to see what the day allows, then pull tasks out of This Week into Tomorrow. Finally, I attach context. If a task requires a spec, a spreadsheet, or a customer ticket, I paste the exact URL into the task notes. This part is critical. You want your ingredients where you need them. I do use light automation here with our MCP integration. More on that in a later post. Then 9 am comes along, I open my laptop, and everything is in place. Mise-en-place. I drag Tomorrow into Today and start working. No email triage. No Slack scanning. No dithering around thinking “what should I do first?” On Friday afternoon, I run a five-minute review. I capture loose follow-ups, check Waiting for stalled projects, snooze what needs punting to a future date, clear out Inbox, and archive Done so Monday starts clean. Reference doesn’t seem that useful, but it holds the static, unglamorous logistics. Kids’ doctors, emergency contacts, company EIN. The exact things I used to waste ten minutes hunting for every time. The exact tool is secondary. You could run this on a whiteboard with sticky notes. What matters is consistency and not letting it rot. I believe simple and consistent beats anything brilliant and fragile. Easy to stick habits pay off because you’re not spending effort keeping up with the system. If you want to try it for a week, you don’t have to build it. My actual setup is shared as a template, already wired up with instructions. Import it and delete whatever you don’t use. Template’s in the comments.

Extracting text from PDFs usually means a server call or a third-party API. WebViewer pulls it from the browser, no server involved. Try it Live!

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A local HTML file dies in Slack. AgentGrid.io turns it into a live link with source and history. Download-share-repeat leaves everyone on a different copy. One cloud app artifact keeps the runnable view, the files, and who changed what in the same place. Try asking your ChatGPT/Claude to place your next HTML page or small web demo in AgentGrid.io. Full blogpost - https://lnkd.in/dUTJiYzH

Obsidian is great for a personal vault. AgentGrid.io is how that knowledge becomes something your team and agents keep working on. Notes stay local until someone else needs them. One shared artifact keeps the current brief and who changed what. Try asking your ChatGPT/Claude to place your next project brief in AgentGrid.io. Full blogpost - https://lnkd.in/db2RWqUd

We'll be at WebexOne, Oct 5–8 in Austin — let's connect at booth S6 while you're there.

Your people already ask for help in Teams. ALVAO turns those messages into tracked tickets automatically, so nothing slips through. See how the Service Desk works inside Teams.