Startup Minded is a startup I co-founded. It started as an AI consultancy helping small-to-medium businesses integrate AI into their workflows, then evolved into our own product: SM Advisor.

  • Services: https://startupminded.com/services
  • Advisor: https://advisor.startupminded.com/

This is the condensed story—what we tried, what hurt, and what we learned.

Phase 1: AI consultancy

What we did

We helped companies adopt AI in two ways:

  • Internally: automate processes (ops workflows, report generation, doc handling).
  • Externally: chat-bots assistants (FAQ/lead qualification/chatbot experiences).

What was hard (the real work wasn’t “the model” nor the software)

  • Finding customers: AI interest was high, budgets were not. Many calls were “curiosity calls.”
  • Requirements gathering: converting the “make it smarter” into measurable outcomes.

What we learned

  • Services scale with people. If you want leverage, you need a product or a process.
  • Good projects started with one narrow workflow and a clear before/after metric.
  • The deal is usually won on trust + clarity, not on “AI magic.”

Phase 2: building our own product — SM Advisor

Why we built it

We wanted something more scalable. SM Advisor became a project-management style tool with an AI chat experience that could:

  • turn messy goals into tasks
  • propose next steps
  • keep work structured and trackable
  • helped managing resources

What was hard

  • Marketing: Getting consistent traffic and signups was not as expected.
  • Competition and Customer finding: the space is crowded—task tools, PM tools, AI copilots, templates. Differentiation has to be sharp, founders and teams want different things.
  • Customization: everyone wants it to match their workflow, knowledge and method.

What we learned

  • Product-market fit is mostly distribution + focus. The tool can be great and still lose if the channel isn’t.
  • “AI generates tasks” is not enough—users need trust, control, and consistency.
  • The best feedback came from watching real users: where they hesitate, what they ignore, what they copy/paste elsewhere.

The through-line

Consulting taught us the messy reality: data, process, buy-in, and outcomes. Building SM Advisor taught us the other half: messaging, channels, retention, and competing in a noisy market.

If you’re building in AI: the model is rarely the bottleneck. The bottleneck is usually distribution, workflow fit, and making value obvious.