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 […]
Your team has decided to add ML to the product. Now someone in the room says “we need to predict this” and someone else says “no, we need to classify it” and a third person is sketching a forecasting model on the whiteboard. The meeting ends without a decision. This confusion is not a technical problem. It […]
Ask most engineering teams when they chose between RAG and fine-tuning and the honest answer is – before they fully understood the problem they were solving. A proof of concept gets built with whichever approach the team was most familiar with. That approach either works or does not. If it does not, the other approach […]
There is a distinction that most SaaS teams building GenAI features do not make early enough, and it costs them significantly when they discover it in production. The distinction is between users trusting your feature and your feature being trustworthy. A GenAI feature can earn user trust quickly. The outputs sound confident. The interface feels […]
Most organisations that have experimented with generative AI in their product and engineering teams share a version of the same experience. The pilot looked promising. Code was being generated faster. The demos impressed. Then adoption stalled, the productivity numbers came in lower than projected, and the ROI question went unanswered at the next quarterly review. […]
The standard advice for build vs buy decisions in SaaS is well-worn – buy commoditised infrastructure, build what differentiates you. Use Stripe for payments, Twilio for messaging, Auth0 for authentication. Build your core product workflow. Everyone broadly agrees on this, and it works for most decisions. AI agents break it. Not because the principle is […]
Most conversations about AI agents in SaaS circle around the same question – what can it automate? That is a reasonable starting point, but it is the wrong frame for the more significant shift that agents introduce. The deeper change is not about speed or task reduction. It is about the definition of a completed […]
Most SaaS founders who deploy a chatbot are solving a volume problem. The support queue is full of the same questions. The tier-one team is spending most of its time on things that should not require a human. A chatbot that deflects those queries frees the team to work on what actually needs them. That is […]
The typical chatbot conversation at a SaaS company goes like this. Someone on the founding team demos an AI support assistant at a conference or in a competitor product. The idea goes into the roadmap. A vendor is brought in or a build is scoped internally. The estimate comes back at six weeks and a budget that […]
Most businesses hear “AI chatbot” and “AI agent” as if they mean the same thing. They do not. A chatbot is usually built to answer questions and guide users through a defined conversation, while an AI agent is designed to take action, make decisions within boundaries, and complete more complex tasks. For product and platform […]