Insights
Thinking on AI product development, enterprise modernization, and what it takes to build in the age of intelligence.
When a Product Leader Goes Back to Building: Reviving 5-Year-Old SaaS With AI
Parental leave has a funny way of slowing life down in the best possible way. Between diaper changes, late-night feeds, and short naps, I found myself with something I hadn’t...
How to Build AI Products That Actually Solve Problems (Not Just Use Technology)
The Technology Trap That’s Costing Enterprises Millions Every month, I see the same pattern repeat itself: leadership teams greenlight AI initiatives based on technological capability rather than business necessity. The...
Integrating Generative AI into Your SaaS Product: A Guide with Real Examples
The buzz around Generative AI in SaaS is deafening, and for good reason—it’s opening doors we only dreamed of a few years ago. Yet, amidst the excitement, there’s a crucial...
Traditional AI Engineers vs. GenAI Engineers: What Sets Them Apart
As AI transforms how we build products, it’s also reshaping who builds them. The roles of Traditional AI Engineers (data scientists, ML engineers) and Generative AI Engineers (LLM engineers, AI...
Rule-Based vs. Probabilistic: How Traditional & GenAI Workflows Differ
Once you understand the training differences between Traditional AI and Generative AI, the next major shift to grasp is in how they operate day-to-day. This is where things get real...
How Traditional AI and Generative AI Are Trained: Why That Changes Everything
In the first post of this series, we explored the core differences between traditional AI and generative AI — what they do, how they behave, and when to use them....