AI Isn’t Delivering 50–80% Productivity Gains, and Here’s Why
There’s a conversation happening behind closed doors at a lot of companies right now, and it goes something like this: AI coding assistants are deployed, adoption is high, developers seem genuinely faster — and yet the product is shipping at roughly the same cadence it always has. Boards are asking about AI productivity gains. Private […]
The AI Coding Trap: Why Your Velocity Spike Might Be a Debt Bomb
A recent study out of Carnegie Mellon confirms what disciplined engineering teams already know: AI tools without structure don’t accelerate development — they accelerate chaos. Every engineering leader has heard the pitch. Developers self-reporting 10x productivity gains. Demos showing features shipped in minutes. The promise that agentic AI coding tools will transform your team’s output […]
Scale AI-First SDLC: N Solo Modes Is Not Scale Mode
This is Part 2 of a two-part series. Part 1 covered Solo Mode: one human operator, a team of AI agents, and a disciplined loop. This post starts where that one ended: what breaks when you scale past a single operator and move into a Scale AI-first SDLC. Recently I was talking to an engineer […]
AI Value Creation in Private Equity: What We’re Seeing from the Portfolio Trenches
This whitepaper draws from our work with PE-backed portfolio companies to separate what creates value in 18–36 months from what amounts to a science project that pays off beyond the fund’s hold period. We cover where AI delivers fast ROI, what doesn’t fit PE timelines, and why success is 80% adoption and 20% technology.
Solo AI-First SDLC: How One Person Becomes a Full Team
This is Part 1 of a two-part series. This post covers the solo operator case: one human, six AI agents, a disciplined loop, and real software shipping. Part 2 covers the AI-first SDLC and what breaks when you scale past one operator. I’ve been through two industry paradigm shifts in my career: Cloud and Agile. […]
Executing AI in Private Equity: A Framework for Implementation
In Part 1 of this series about AI in Private Equity, I made the case for why operational alpha through AI has become a non-negotiable lever for PE firms facing multiple compression. In Part 2, I mapped the use cases that realistically deliver within your hold period. Now, in Part 3, I want to tackle […]
AI and Patient-Centered Digital Health: Why Delivery Discipline Matters Most
Patient-centered digital health is often framed as a technology problem. Add AI-driven personalization, smarter triage, better engagement tools — and patients will have better experiences. The logic is appealing, but it skips a more fundamental question: can your delivery system actually support the pace of change those experiences require? In most healthcare organizations, the answer […]
AI Value Creation in Private Equity: Use Cases That Fit Your Hold Period
For private equity firms focused on AI value creation, the question is no longer whether to act — it’s where to deploy capital for maximum impact within the hold period. You’ve made the case internally that AI matters. The investment committee is on board. Now comes the harder question: where exactly do you deploy it? […]
AI Personalization for Retail: Why Engineering Systems Outperform Algorithms
Retail and CPG leaders investing in AI personalization are not short on ambition. Most organizations already invest heavily in customer data platforms, AI-driven recommendations, loyalty engines, and omnichannel tooling. Yet despite this investment, many brands still struggle to deliver experiences that feel timely, consistent, and genuinely customer-centric. The issue isn’t that AI doesn’t work.It’s that […]
Why Healthcare Software Delivery Breaks Down, and How Engineering Leaders Fix It
When critical healthcare software initiatives fall behind schedule, the immediate reaction is often to blame the tools. Leaders look for better platforms, more automation, or simply ask their teams to push harder. But in reality, delivery breakdowns rarely stem from a lack of effort. They start deep inside the engineering system itself. For engineering leaders […]