Kevin Sonney

Microsoft certainly had a head start with early access to OpenAI tech (through their investment) and we are starting to see the strategy come together with tooling that people can use and an established user base to get usage data and product development information from. Important at this point as people are getting overwhelmed of AI or have yet another model syndrome. What can AI do to make my company more competitive? How can I use it to reduce the costs of good ideas? (ideas that may have required hiring 30 people, now can be done with existing staff and is now viable) How can I deliver on these ideas sooner? (copilot and AI in skilled resource hands can deliver faster) or other goals that the company may have.

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Exciting times Sundar Raghavan for sure... my humbled take on the next generation of an AI start-up... Rethinking Execution Layer Ownership: Compiler-Inspired AI for Startups   Foundation Capital's article hits home: Model providers like OpenAI are climbing the value stack, threatening startups that own messy legacy systems. But does owning the "execution layer" really create a moat, or just isolation?   My take: Restructure it dynamically with AI agents. Drain the moat, clean up, and evolve—drawing from compiler theory for structured adaptation. This isn't survival; it's innovation.   A potential path: Abstract via APIs, microservices, and clouds. Embed simple expert agents, build feedback loops with dynamic intent tables, let agents lift the load in an automated fashion on the assumption there will be more error than success. Given resources in this approach, it’s a matter of time before there is more success than error in the Reinforcement Learning (RL) layer effort. This empowers the startup amid model dominance—"compile" once, adapt forever with dynamic semantic data sets. This will shorten the cycle times of the learning loop.  The solution is multi-dimensional.  Exciting times! Who's refactoring legacy processes with dynamic intent graphs?

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If you’re a CEO/founder or PE operator and your tech org is: ❌ Shipping late ❌ Stuck in reactive mode ❌ Struggling through the Series A/B jump, or post-acquisition integration or after a major release It’s not “a delivery problem.” It’s an operating model problem. At the inflection point, the old playbook breaks: what worked at 10 engineers fails at 40… and breaks again across multiple products/teams. That’s where I come in as a fractional CTO: - Spot platform and delivery risks before they hit revenue and retention - Rebuild execution rituals (prioritization, ownership, release confidence) without derailing the roadmap - Align architecture + team structure to your value-creation plan (growth, margin, or exit timeline) If you’re feeling the strain of growth, I can help you turn “busy and reactive” into predictable shipping, and a platform that scales. #CTO #SaaS #StartupScale #PrivateEquity #TechStrategy

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We are in the middle of a major transformation in software engineering. It's also a harbinger for what's coming for white collar work. A few key questions I've been debating with friends and colleagues are: - What's overhyped, what's coming, and what's here? - What does this mean for white collar work generally? - Which areas are most ripe for disruption? - How should we approach optimally incorporating AI into these functions? I've compiled the answer to these questions, along with some sweet memes, in my latest article. I've been cooking this for a few weeks now, and I believe it's one of my best contributions. One of the key takeaways is that the pace of AI disruption in a white-collar domain is determined by where it lands on a scale across four dimensions: 1. Fidelity to simulation 2. Reversibility + feedback velocity 3. Verification speed 4. Digital centricity Software engineering scores high on all four, thus it is ground zero for disruption, but other industries will not be too far behind. Read more at: https://lnkd.in/gNeH9MUv

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I have seen a lot of RFP's. Most are run poorly. And most of them are set up (by accident, or the best intentions) to not provide any significant improvements to the business over what the business is currently doing. There are alternatives to the procurement process that is an RFP selection. But if you really want to run a RFP, watch this first, from Jeremy and Allie H. at CBS NorthStar.

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Commerce & Revenue Optimization ​ Today, recommendations are the default in commerce—guests expect relevant options, not generic offers. Onboard is no different. ​ ​ Ascendion helps cruise lines use AI-driven personalization to make it easy for guests to discover, explore, and buy—whether it’s dining, retail, or excursions. With predictive offers and tailored recommendations, every interaction has the potential to increase spend and satisfaction. ​ ​ When commerce feels natural and helpful, it becomes part of the experience, rather than a distraction. ​ ​ Learn more: https://lnkd.in/guDUnmNc ​ ​ #CruiseLine #Ascendion #FutureOfWork #EngineeringAI #DigitalCommerce ​

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Most digital transformations fail not because of technology, but because of this missing ingredient... Purpose. I learned this while building Pier 1's e-commerce business from the ground up. We had some lofty goals: integrating a 50-year-old company with 1,200 stores, rebuilding antiquated systems, launching new capabilities. But several months into the grind, our team was drowning in the details of technical requirements, system integrations, and tight project timelines. We were building something, but we had lost sight of why we were building it. Then we began shifting our mindset. Instead of focusing on what we needed to accomplish, we asked a different question: "Who are we really serving, and how?" The answer brought us back to our customers: people who wanted to make their HOUSE a HOME. That simple reframe changed everything. Suddenly, every technical decision had meaning. Every integration challenge became an opportunity to better serve someone who was trying to create a space they loved. This was the birth of the APP Framework: Purpose comes first—the deeper "why" that drives everything Passion naturally flows from meaningful purpose Accountability becomes easier when everyone understands what we're building toward When we reconnected with our purpose of helping customers transform their houses into homes, our team found unity we'd been missing. The work didn't get easier, but it got more meaningful. I've seen this pattern repeat across organizations: the companies that thrive during transformation aren't necessarily the ones with the best technology—they're the ones that never lose sight of who they're serving and why it matters. What's your organization's "WHY" that drives everything else? #DigitalTransformation #Purpose #Leadership #Ecommerce #TeamAlignment

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I am extremely impressed by how quickly people who have never coded before can come up with solid, useful local SPA apps when I onboard them to Claude Code. The "Tier 3" of my training program CSC Generation is (previously) non-technical people live-build their first SPA in NextJS, run it locally, and get their own LLM API key. I instituted the pilot 1 month ago. So far just over 5% of the (non-engineering) corporate population at the company has built at least 1 fully functional tool to help them with their workflow, with a success rate of above 80% within 7 days of onboarding. They run the applications on their client, and have an API budget. Many of the apps are quite simple, and hyper-specific to the user. All that their apps have access to, are the same things their client laptops already had. One user, live, in front of the class, in a 1 hour session, finished a novel data normalization app, where the LLM proposed new normalization mappings and presented them to him, as a gamified "Yes/No" using the keys on the keyboard. After the class: added a feature where, once the Accept rate got above significance indicating the LLM could accurately predict at human level, we allows a mass accept. What would have been a labor intensive spreadsheeting exercise on 100's of thousands of items, became a 3 hour project building a game and playing it. Pretty neat example of "Personalized Software"! (PS, please come work with me in a technical or nontechnical capacity if this is the kind of thing you want to do or build enabling tools for)

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We’re in the era of the “hard pivot”: leaner policies, AI-driven headcount reviews, and blunt “you’re replaceable” rhetoric. It may boost short-term metrics, but at what cost to credibility and culture? 1. Credibility Is Fragile Flip from “our people are our greatest asset” to “you’re lucky to have a job,” and trust evaporates. Teams remember how they were treated long after the numbers rebound. 2. AI as Tool, Not Tyrant Automate routine work, yes—but don’t let algorithms dictate who stays or goes. Machines optimize processes; only humans sustain purpose and empathy. 3. Guardrails for Human-Centered AI - Be Transparent: Explain how AI factors into decisions. - Upskill Intentionally: Create new roles, don’t just cut headcount. - Balance Efficiency & Empathy: Protect your most valuable, hard-to-replace talent. Hard pivots might win a quarter, but people-centered leadership wins careers—and longevity. Embrace AI, but keep humans at the center to preserve the soul—and the future—of your organization. #Leadership #Culture #AI #FutureOfWork #HumanCenteredInnovation https://lnkd.in/e67ys3_s

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