Leadership Evolves to Ecosystem Architects

Joined the Zurich-hosted inaugural Insight Talks by Next Industries panel this week - remotely from #Luxembourg, which meant I had the best seat and the worst coffee ☕ Couple of notable highlights from the discussion: 𝗪𝗵𝗮𝘁'𝘀 𝗼𝘃𝗲𝗿𝗵𝘆𝗽𝗲𝗱 𝗶𝗻 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗔𝗜? Fully autonomous systems replacing engineers overnight. The demos are impressive. The production deployments are rare. 𝗪𝗵𝗮𝘁'𝘀 𝘂𝗻𝗱𝗲𝗿𝗿𝗮𝘁𝗲𝗱? Legacy documentation. PDFs, scanned drawings, handwritten records - decades of engineering knowledge locked in formats no system can universally and reliably read. Making that machine-readable isn't flashy. But it's where the real ROI is hiding. 𝗪𝗵𝘆 𝗱𝗼 𝗔𝗜 𝗽𝗶𝗹𝗼𝘁𝘀 𝗳𝗮𝗶𝗹 𝘁𝗼 𝗿𝗲𝗮𝗰𝗵 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻? They're built to impress a demo, not to survive messy real-world data and the engineer who just wants to get their job done. I'm drawing on this at my daily work at Octave, building production AI - and it matches everything I've seen across previous roles in building enterprise software. What's your experience — is the pilot-to-production gap getting better, or are we still stuck? Thanks Gabriel Krummenacher and Philip Hauri for the invitation and insightful talks and discussions. 

🎙️ In this episode of Leaders of Code, our Chief of Product and Technology Jody Bailey sits down with Netlify's CTO Dana Lawson to explore her insights on leading lean, global engineering teams, and how AI is lowering the barrier to entry for builders everywhere. https://lnkd.in/eUbCMxis

Orbiting the Giant Hairball vs. EOS: Two Operating Models Every Engineering Manager Should Understand Gordon MacKenzie’s “Beyond Measure” offers a reminder many engineering leaders need to hear: not everything that matters can be captured in a dashboard. His message, aimed at large organizations, warns that too much process, too many KPIs, and too much control can choke the creativity and problem‑solving we expect from engineers. Gino Wickman’s EOS, built for small and scaling teams, argues the opposite: without clear metrics, priorities, and accountability, even brilliant engineers spin in circles. Tools like the Scorecard and quarterly Rocks bring clarity that keeps teams shipping. Two environments. Two pain points. Two different cures. Where they overlap: A clear purpose (MacKenzie’s “orbit” ≈ EOS Core Focus) Investing in the right people Balancing innovation with execution Where they differ: MacKenzie reduces structure to protect creativity. EOS adds structure to channel creativity. For engineering managers, the takeaway is simple: Measure what matters, but don’t let measurement replace judgment. Leave room for experimentation, deep work, and the kind of engineering intuition no metric can quantify.

We were asked to build a robot. We built a flashlight instead. A client wanted full robotic retrieval inside mobile service vehicles. Through early concept iteration, we discovered the bottleneck wasn't physical—it was informational. Operators didn't need a robot arm. They needed to see which item to grab. The pivot to a vision-assisted system delivered 60–70% less effort, 25–35 minutes saved per route, and major accuracy gains—without a single moving part. The lesson: Define → Simplify → Then automate. I break down the full story here 👇 https://lnkd.in/eYiMHjaN

Steve Sobolevsky named our company Nimble for a reason. Small decisions, made fast, that compound into something bigger. That same thinking is behind what we're bringing to engineering teams right now. The agentic AI gap is real, it's widening, and it isn't about motivation or tools. It's about the absence of a system. Read this if you lead or work with an engineering team. #AgenticAI #AgenticEngineering #EngineeringLeadership #AITransformation

It's been wild to be a part of this. Gaining advantage using AI tools is so much more than "Use Claude, and work on two things at once." When you're ready to blow up the way you think about development and really re-examine how the work flows through your software engineering assembly line, you're ready to see the real possibilities. In our case, after about a year of experimenting with AI tools and seeing only marginal gains, we retooled and changed our processes to focus on our AI stack, and we instantly doubled throughput. Then we hit 3x. And more recently, 4x. For a company that was already out-shipping every other shop I've worked in the past decade, that's impressive.

This is such a great talk from Uber. As you probably already know, Uber has a lot of depth in AI and Data engineering and associated open-source projects (Ludwig, Horovod, Pyro, Petastorm, CausalML, etc). They have a proprietary system (Michaelangelo) that is something of a Blueprint for MLOps in the Industry. They recently developed a CLI (AIFX) that provides a central ability to build and deploy Agents and manage their Agentic infrastructure. And they recently developed an Agentic orchestration system (Minion) to allow Engineers to manage a fleet of autonomous background Agents on Uber's infrastructure (vs LLM provider infrastructure), with an integration to Slack, no less! If you make it to the end, then you will come to an interesting talk on Uber's Engineering Culture, which includes an openness to Buy vs Build, as well as some great words of wisdom on how to help team members manage through this fast changing world of ours (theirs) and how to help leaders understand the positive Business outcomes of AI, which is not always as easier to articulate as the costs of AI. https://lnkd.in/e7VAiBTF

Enterprises rethink their foundations as Rohan Cherian, Vice President at Pet Valu Canada, explores how treating AI as an architectural principle – not just a feature – can transform application and product engineering, enabling scalable, agent-ready ecosystems with governance and human-in-the-loop design. #MillenniumLive

✈️ Federal missions don’t wait for perfect conditions. Neither do we. At SteerBridge, we invest early, embed deeply, and execute with discipline — whether that’s deploying AI readiness systems, modernizing Fleet Data environments, or building VA medical infrastructure. We’re not chasing contracts. We’re driving outcomes. 🎥 Watch how our Veteran-led culture turns complexity into mission advantage. 👉 https://lnkd.in/eUfmWKdW