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Coffee and Claude: How Honeycomb MCP Makes AI Work for You

If you caught our recent Introducing Honeycomb MCP: Your AI Agent’s New Superpower webinar, you know it was a lively mix of big ideas, demos, and a few laughs about the messy, fast-moving world of AI. Hosted by Austin Parker, Morgante Pell, and James Bland from AWS, the conversation explored how Honeycomb’s new Model Context Protocol (MCP) is changing the way developers and AI agents interact with data.

Building Smarter AI Products #Datadog #DASH #AI

AI capabilities are advancing faster than ever — transforming how teams design, build, and ship intelligent products. In this teaser from Building Successful AI-powered Products at Datadog DASH, experts discuss the rise of agent-based systems, evolving model capabilities, and how to stay ahead in the new era of automation.

Breaking down AI adoption barriers feat. Ivanti's Scott Hughes

ivanti.com/itsm-automation Unlock the secrets to successful Agentic AI deployment and widespread AI adoption in your organization with insights from Scott Hughes, SVP of Revenue Operations and Corporate IT at Ivanti. This video explores why IT-business alignment is critical, the importance of high-quality data, and how legacy infrastructure poses challenges for effective AI integration. Key insights.

Role of Vehicle Technology in Post-Crash Assistance

Modern vehicles do more than prevent crashes. They now help drivers and passengers after impact, guiding first responders, preserving evidence, and speeding up recovery. The most useful systems work in the minutes that follow a collision, when clear information and fast decisions matter most. Automakers, app makers, and cities continue to link cars, phones, and emergency networks, which turns a chaotic moment into a coordinated response.

Bridging the Gap Between AI Writing and Human Expression

Never before has AI dominated the content we read every day as much as today. As each day passes, the online and offline worlds are being filled with AI writing, and soon, it will become difficult to find the human touch in any content. With AI being so prevalent, it has raised an important question: Will the human essence in writing just disappear as we let AI generate more and more writing each day? Does it really have to be an ongoing fight between human creativity and machine algorithms?

Fintech: The Next Frontier for Global Investors

Financial technology has moved far beyond simple payment systems - it now stands at the intersection of innovation, inclusion and investment, connecting startups, established financial institutions and emerging markets. According to an article on Gulf News, fintech is emerging as a pivotal force reshaping the global financial landscape.

AI Agent for Proactive Problem Management: A Shift Toward a Ticketless Future

As organizations rely on increasingly complex IT infrastructures, incident management often turns into a constant cycle of alerts, escalations, and fixes. While reactive responses may keep operations running, they rarely address the deeper systemic issues that slowly erode performance. Recurring incidents, silent failures, and hidden patterns are usually symptoms of unresolved root causes that traditional approaches struggle to uncover.

Building dbRosetta Using AI: Part 1 of Many

Like many of you, over the last couple of years, I’ve been using AI, or, well, let’s just name it appropriately, Large Language Models (LLM), as a part of my job. I’ve also used it in my hobby. With it, I’ve generated snippets of code, tested data conversions, even built a small database for a presentation. However, to date, I haven’t tried doing everything through the LLM. Now, I’m going to.

Why AI Coding Assistants Fail (And How to Fix Them)

Why do developers stop using AI coding assistants? According to Carnegie Mellon research, the top reason is unhelpful suggestions. Tabnine's Principal Architect John Feeney explains how context transforms AI coding tools from generic to genuinely useful. Learn the 4 Cs framework for maximizing AI assistant value: Context (workspace indexing), Connection (repo integration), Coaching (rules-based guidance), and Customization (fine-tuning). Discover how Retrieval Augmented Generation (RAG) helps AI understand your codebase, not just open source patterns.