Post-market surveillance means watching a product after it is on sale, in real use, not only before launch. The video shows a shop that tests a coffee machine for one afternoon, buys it, and finds months later that the coffee tastes bitter.
A short explainer video, under a minute. The shopkeeper and the helper are an illustration of the idea.
At a glance
What Post-Market Surveillance Is
Watching a product after it is on sale has a name: post-market surveillance.
Before and After Launch
The video sets two views side by side. Before launch there is one test, in a controlled place.
Why It Matters
The video turns this into one question: who is watching it after the test?
The Business Engineer framework maps where each part of the AI stack sits and who holds the leverage. These pills are short lessons from the same library.
Our report on the UK government’s response on regulating AI in healthcare says the response describes a “conscious shift towards ongoing assurance rather than overreliance on pre-market assessments and passive adverse event reporting”. The report also says the MHRA’s AI Airlock page names post-market surveillance as its current priority regulatory challenge area.
This is the lesson’s idea in a new setting: a check before launch, and watching afterwards. The report presents all of it as the government’s own statements of intent, and this publication verified none of it independently.
AI Evaluation as Acceptance Test contrasts with Post-Market Surveillance. An acceptance test decides before shipping; post-market surveillance keeps checking in real use because a test shows one day.
Red Teaming(lesson unlocks soon) contrasts with Post-Market Surveillance. Red teaming attacks before launch and never proves there are no holes; surveillance keeps watching in real use.
Kill Switch(lesson unlocks soon) contrasts with Post-Market Surveillance. Surveillance is the alarm that tells you; a kill switch is the owned stop that acts.
The Notification Clock(lesson unlocks soon) builds on Post-Market Surveillance. Watching in real use is how a maker spots a flaw after sale, and the notification clock starts the moment it does.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
