The adoption curve for agentic AI in SaaS is moving faster than most teams expected and producing less value than most demos implied. According to McKinsey’s State of AI 2025 survey of nearly 2,000 organisations, 88% of companies now use AI in at least one business function, and 62% are at least experimenting with AI […]
The internal RAG demo always looks impressive. The team asks questions. The system retrieves the right documents. The answers are clear, well-structured, and grounded in actual product content. Someone says “we’re ready to ship.” Then the first real users arrive. Real users do not ask the questions you rehearsed. They do not know what the […]
Most teams start a RAG project by evaluating vector databases. They compare embedding models, read benchmarks, set up a LangChain prototype, and have something running against a handful of test documents within a week. That week goes well. The problems arrive three months later, after the index has grown to thousands of documents, after real […]
There is a version of RAG failure that nobody in the team notices in time. The system doesn’t crash. The latency looks fine. The monitoring dashboards stay green. A user asks a question. The retriever pulls something that looks relevant. The model produces a clean, well-structured answer in the product’s tone. The answer is wrong. […]
Most teams evaluating AI right now are looking at the same shortlist – which model to use, which vendor to talk to, which feature to build first. It’s a reasonable starting point, and it’s also the wrong one. The conversation about AI capability tends to dominate the room because it’s visible and easy to compare. […]
A board update goes out. Two sentences near the bottom mention you’re adding AI agents to the product. Six months ago that line would have gotten a thumbs up and nothing else. Today it gets a follow-up question, sometimes several. What does the agent actually do. What happens when it’s wrong. Is this something you […]
Every roadmap review has the same moment. Three good ideas, one quarter of engineering time, and a conversation about which two get cut. For most of software history, that tradeoff was the entire point of roadmapping. Prioritization frameworks like RICE and WSJF all ask some version of the same question: how much value do we […]
Every product team building an AI agent that takes real action eventually asks the same question – is this agent trustworthy enough to act on a user’s behalf without a human checking every step? The instinct is to answer that question with reassurance. Add a confirmation dialog. Add a disclaimer. Add more hedging language to […]
Most SaaS founders who have experimented with AI features hit the same wall. The model is impressive in demos and unreliable in production. It gives generic answers where specific ones are needed. It confidently describes things that are not true about the product. It fails to distinguish between what your product does and what a […]
You shipped the chatbot to take pressure off your support team and give users instant answers. The dashboards looked healthy at first. Sessions were happening. Then you looked closer at what those sessions actually contained, and the picture changed. Most people open the chat, type one or two messages, and leave. Seven out of ten […]