How to Build an MVP That Attracts Investors

AI agents are here, and they’re changing how organizations work! In Episode 3 of our AI Momentum series, Principal Technology Strategist Jeremy Bierlein and Microsoft Partner Technology Strategist Soumya Bhatt explain what makes an AI agent different from a copilot and where they deliver the most impact. From policy Q&A in financial services to predictive maintenance in manufacturing, they highlight the spectrum of use cases across industries and the three practical on-ramps to get started: buy, configure, build. Watch the full session: https://loom.ly/wme1vNQ

Highly requested, brand new track: AI Agent Fundamentals! In just four hours, gain real-world skills to move past the AI hype and see why agents are becoming vital for modern workflows. Learn how AI agents can power automation, coding assistance, and advanced support bots—going far beyond GenAI prompts that keep many toiling in the first gear of AI application. Through interactive exercises, you'll: 💰 Understand the role of GenAI in business 🤖 Discover what AI agents are (and aren't) 💡 Explore frameworks like TAO and ReAct to see how agents make decisions 🚀 Learn why so many agents fail in production—and what it takes to scale them 🛠️ Build your first agentic systems with step-by-step, hands-on practice ✨ To future-proof your skills, set aside a few hours a week on DataCamp and start building. 👉 Start now for free: https://ow.ly/ArHB50X1sbR

⭐ Build AI Agents with LangGraph Learn to build a startup intelligence agent in this video guide, showcasing LangGraph's stateful workflows with planning capabilities and SingleStore integration for vector storage. Watch the tutorial: https://lnkd.in/ea4AyHwS

After more than a decade working at the intersection of design, data, and strategy, I’ve noticed something consistent across every technology wave — especially with Generative AI: Most organizations don’t need more hype about what’s possible. They need more clarity about what’s practical. My work today focuses on helping public sector and industry leaders explore AI responsibly — understanding where it can create real public value, and where caution or policy need to catch up first. Over the coming months, I’m planning to share some reflections from this work: what’s working, what’s not, and what’s worth watching. If you’re thinking about how to apply GenAI in a mission-driven or highly regulated space — I’d love to hear what questions you’re asking right now.

I recently sat down with Birgitta Boeckeler, who’s been leading our efforts around AI in software delivery for the past two years. We talked about one of the hottest (and trickiest) topics from our recent Technology Radar discussions: how AI is reshaping developer workflows, the rise of coding agents, and what emerging practices we’re seeing as teams experiment with incorporating them into the development process. Some of these ideas are still taking shape, which is why we say they’re “too complex to blip” just yet. There’s so much change happening in this space from how teams use AI to how we define good engineering practices. Watch our chat to hear Birgitta’s thoughts on what’s emerging, what’s still unclear, and why experience still matters when working with AI tools. Be the first to explore the latest trends and insights from the Technology Radar. 👉 Subscribe now - https://ter.li/tvn5yj

Great insight. I'm completely aligned with this perspective. The paradigm shift isn't about AI writing code—it's about developers learning to think in prompts and iterations. This fundamentally changes how we decompose problems. We aren't just accelerating old tasks; we're redefining where human judgment is most vital in the software development lifecycle. #AI #SoftwareDevelopment

95% of AI initiatives fail. That’s the headline from MIT research, and it probably won’t surprise many. But it does raise the question: what makes Origin different? In this conversation, our co-founders Chris Bruce and Peter Craghill explore what sets successful AI initiatives apart from the rest: 👉 Building AI into the core architecture of the platform, not bolting it on later. 👉 Tackling a real, unsolved problem that only AI could address. 👉 Combining deep domain expertise with the guidance of our incredible co-creators. The result? While so many AI projects stall, Origin is delivering real value to some of the world’s most complex organizations. 🎥 Watch the full conversation 

Why Origin is in the 5% of AI projects that are delivering value. Great insights from our founders, Chris and Pete, in this conversation. A standout quote for me: "LLM's are the most confident liars you'll ever see, and they will back it up. It's too unguided." Relying on GenAI for accurate answers to benefit questions is like "flipping a coin" - which is why a more guided approach is needed.

Great Video Deep Diving on how 95% of AI initiatives fail, and how it can be done differently putting problem solving and client needs at the centre.

MIT recently shared that 95% of AI initiatives fail. Not exactly a surprise… but it made me stop and think about why Origin is in the 5% that’s working. For me, the answer is clear, we didn’t start with AI and look for a problem it could solve. We started with a problem that had gone unsolved for decades, that only AI could solve it. From there, we built Origin with AI at the core, guided by deep benefits expertise and our brilliant co-creators. Good to talk it through Peter Craghill Origin. #AI #artificialbenefitsintelligence