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For a while, prompt engineering looked like the secret skill behind Generative AI. If you could phrase your instructions the right way, you could make an LLM behave exactly as you wanted. Many teams treated it like tuning a magic spell: add more instructions, change a few words, and hope the model suddenly becomes accurate. This worked in the early days, mostly because people were experimenting. But once GenAI started moving into real products, the limits became clear. A well

Most AI startups are losing money with every new customer due to negative unit economics. But a shift in API pricing from providers like OpenAI might change everything. Here's how. Growth Without Profit AI startups are growing fast but at what cost? While user numbers and engagement may impress on the surface, the underlying economics are broken. In many cases, every additional customer actually increases losses.  The root cause? The cost of accessing large language models (L

Small businesses are about to get their first “employee” who never sleeps, never forgets, and scales infinitely: the AI agent. If you’re...

When we first launched our AI claims screening tool, the model response time was lightning fast in staging — around 200ms. Everything...

When we first rolled out personalized dashboards for returning users, we didn’t expect much. It felt like a “nice to have” feature. But...

How I balanced relevance, timeliness, and trust in an AI-driven product When I joined a data-driven investment platform focused on...

When I first transitioned into AI product management, I did what most of us do — I reached for the comfort zone of metrics. Accuracy....