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In my journey as a startup founder and early employee, I’ve accumulated many stories related to customer research. The funny thing is, when I founded my own startup, I thought I was doing customer research, only to realise later in future roles that I did almost everything wrong when it came to validating our product idea. I’ve already shared this in a previous blog post—we were very fast in launching the product to market, and we learned a lot from real customers, which was good. However, we also had to change many of our initial assumptions—something that could have been avoided with the right approach to customer research. Later in my career, I had the opportunity to conduct customer research with product teams at established startups, and I learned there is a method to do this properly. Although I haven’t created another product since then, I now know what I would do differently – and this is the advice I give to the founders I mentor at Techstars and Startup Lisboa, among others. Understanding your potential customers—what drives them, what problems they face, and how they might react to your solution—is critical, if not mandatory, for success in your entrepreneurial […]

Innovation brings about increasing capacity to automate tasks.  At the edge of innovation in AI, we are starting to see teams of specialised autonomous agents perform complex tasks, which would take a team of humans weeks of work to accomplish. skip render: ucaddon_blog_simple_quote In a previous article, I explored the concepts behind LLMs, Chains, AI Agents and Multi-Agent Systems (MAS).  When I talked about chains, I pointed to frameworks like LangChain and LlammaIndex, and later when talking about agents, I referred to frameworks like Microsoft Autogen, CrewAI and LangGraph to build multi-agent workflows. That article felt complete until last month when I got the privilege to sit in at the Mindvalley AI Summit. There, I watched a talk from AI Entrepreneur and Investor, Juan Martitegui. In it, he showcased how to trigger a team of AI agents to: Automatically generate ideas for YouTube videos based on a given topic Rank the previously generated ideas Do market research of the top performing YouTube videos in the topic, collecting metrics such as views, subscribers, likes Write the script for a video recording of the top-ranked idea Generate copy for social media posts  Write a report  Send the report to the speaker’s email  […]