One thing I've been learning while building my startup is that finishing a product and earning the trust of the people you want to serve are two very different things.
Over the past year, I've spent a lot of time building the technology, but I've also realized that getting a foot in the door requires more than having something that works.
I've started focusing on building credibility in other ways:
Publishing research in an international project management journal.
Writing a LinkedIn newsletter to share what I'm learning about business and technology.
Preparing to speak at an international technology conference.
Working through security, integrations, and the requirements of building software for organizations.
Participating in industry communities and building relationships with people who understand the problems I'm trying to solve.
I've used ChatGPT and other AI tools while building my startup, and they've made it possible to take on work that would normally require a much larger team. Research, technical problem-solving, planning, and exploring new ideas can happen much faster. But one thing I've learned is that completing more work doesn't necessarily mean the business is moving forward at the same speed. You can build faster, solve technical problems faster, and make improvements faster, while the harder questions about customers, adoption, and business growth still take time to answer. It's changed how I think about productivity as a founder. I'm learning to distinguish between how much work gets completed and whether that work is actually moving the business forward.
For founders building with AI, what's one lesson you've learned about the difference between moving faster and making real business progress?
In our first six months, whenever a paid user churned, our immediate reaction was: Ah, they needed Feature X. Let s build it."
Our backlog became a graveyard of quick fixes requested by churned users. Yet, retention stayed flat.
It took us a painful realization to see that the issue wasn t a feature gap; it was a friction gap. The product required too many context switches from our users' daily routines.
For founders who survived this phase: How did you shift your team's mindset from "ship more features" to "reduce workflow friction"? What metrics actually helped you spot this early?
Our product is an automated machine learning product. If I had to redo one thing, I would have focussed on web application part from day 1. Instead we focussed on getting data science part right first.
