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 […]
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 […]
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 have the budget approved. The board is excited. Someone on the team has already built a demo over a weekend that looked convincing enough to get everyone nodding. Now the pressure is on to turn that demo into a real feature inside your product, and the quiet worry sitting underneath the excitement is the one […]
Artificial intelligence has reached a point where most mid-market companies are no longer asking whether they should adopt AI. The real question has become – how do we implement AI without wasting money, disrupting operations, or ending up with another failed technology initiative? That shift explains why AI consulting has become one of the fastest-growing advisory […]
You hired an AI consulting firm. They ran workshops. They interviewed your team. They produced a comprehensive AI strategy presentation with a technology roadmap, a list of recommended vendors, and a prioritised list of use cases. The engagement closed. You have a deck. Six months later, nothing has been built. This is the most common outcome of AI consulting engagements. […]
You ran the assessment. You sat down with your team, worked through the questions honestly, and found something you did not expect to find. Maybe it was the data, years of records with no labelling, no outcome signal, nothing a model can learn from. Maybe it was the use case, three people in the room […]
Somewhere in the last eighteen months, a decision got made in a lot of product teams that sounded reasonable at the time. The question was “should we add AI to this feature?” and the answer was “yes, we should use one of the big language models.” Nobody in the room pushed back. GenAI was what everyone was […]