Artificially Intelligent: Building an AI Startup

episode artwork

Jacob Anderson

18 May 2023

48m 2s

Co-Founder Onboarding, Customer Research & Sprinting to Revenue

00:00

48:02

Note from future Jacob (2026):

This startup failed. In fact, it never got off the ground beyond an idea. The reasons were many, but if anything it was an inspiring exercise in what not to do. So much focus on brand, on what it should mean, and no focus at all on what difference the product should make to the person that uses it. I can forgive myself for that. It was incredibly easy to be swept away by the great wave of possibility that was early AI at this point.

Now, in 2026, as I write this, things are quite different. Back then, we had a taste. Now, with the arrival of models like Anthropic's Claude Fable and OpenAI's GPT-5.6, those of us who can operate the harnesses can build beyond our wildest dreams.

Some of the ideas from this startup have survived, and even the brand name has lived to fight another day. Sayora is an AI receptionist for UK small businesses. When your hands are full and your phone goes to voicemail, who answers? Sayora can.

Read more about the product, and the story behind the name, at sayora.ai

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It's week 4 of 16:

Jacob Anderson (@itwasjacob) and Colin Gray (@colinmcgray), his day job boss, sit down to discuss the exciting news that Jacob recently found a co-founder.

The podcast delves into why Colin wishes he had one at the start, the hows and why's of doing a partnership alignment workshop, and the market research findings that will shape their endeavors.

We also discuss our ideas for an easier-to-deliver MVP, which still solves similar problems, but lets us get to revenue faster.

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In this episode:

  • Finding a cofounder vs going solo
  • Onboarding a co-founder for your startup
  • Why partnership alignment is important
  • Early customer research findings
  • Building a customer research app for novices AND professionals
  • Why interviews work better than surveys for customer research
  • Deciding to build an MVP using the same tech, solving a related problem, but far quicker to revenue

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