How Gorilla Logic Turned Experiments into a Repeatable AI Delivery System
Most engineering teams treat AI adoption as a speed problem. Gorilla Logic decided to treat it as a sequencing problem, and built an AI delivery system that proves it. That single shift is what makes AI Factory different. Every engineering organization reaches the same inflection point: interest in AI is high, experiments are everywhere, and […]
The Three Layers of AI-Driven Engineering Productivity
Most organizations are one layer deep into AI adoption and wondering why AI engineering productivity gains don’t match the promise. The framework for understanding why is actually simple, and one you’ve heard before: you have to slow down to go faster. The trick is to build on success. Gorilla Logic has spent more than 20 […]
Enterprise QA Automation: From Strategy to Scalable Impact
For enterprise engineering teams, every release cycle is a calculated risk. Your systems need to hold, your pipelines need to deliver, and your teams need to move fast without breaking what matters most. Across complex architectures, regulated environments, and distributed teams, that risk compounds fast, and without a mature enterprise QA automation strategy built into […]
Operationalizing AI in Energy Infrastructure
The Energy and Utilities industry is undergoing an enormous shift in the age of AI and digital transformation. What was once a distinct operating model is rapidly evolving into a complex software engineering challenge, demanding the same advanced cloud, AI, and data architectures, along with the operational rigor that modern engineering organizations use to build […]
AI-Enabled Engineering Starts With Your Delivery System, Not Your Toolstack
Across engineering organizations, a familiar paradox is playing out: developers feel more productive than ever, yet delivery timelines and quality remain largely unchanged. AI tools are in use, velocity appears to be up, and somehow outcomes aren’t improving. The reason is straightforward, even if uncomfortable. If requirements are unclear, architectural decisions are rushed, testing remains […]
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 […]
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. […]
5 Signs Your Manufacturing Platform Is Holding Back Your Product Roadmap
Technical debt doesn’t announce itself. It accumulates quietly — until the day your competitors ship faster, your engineers spend half their time firefighting, and your roadmap slips again. Nobody builds a platform intending to create a bottleneck. The legacy systems that now sit at the center of most manufacturing and automotive engineering organizations were built […]