Mindset and Strategy for Early Stage Founders

There's a few topics that come up repeatedly in our conversations with early stage founders when they're figuring out how to build product. In November we (Seb Cox and Simon Plant) hosted a session at Blackbird Sunrise Aotearoa to tackle a few of these themes head on.

1. MVP Is Dead, Long Live MVP

Building a successful product is one of the hardest challenges for any founder. Too often, outdated "lean startup" thinking leads founders astray—go too heavy and you risk locking in assumptions that prove wrong; go too lean and your MVP may fail to solve any real problem.

When deciding what to build, shift your focus from features to risks:

• Business Model Risk – Is there a solid business model under your product? Are the unit economics good?
• Market Risk – Will customers want and pay for it?
• Technology/Product Risk – Can you build what you need with the resources you have?

2. Listen to Customer Feedback or Trust Your Gut?

It's common advice to build what customers tell you. We think this is wrong. Everyone wants to make data driven decisions but in most cases startups do not have enough data to do this approach properly. Great products are born from outlier insights, not crowd consensus.

3. Beware the Commoditisation of AI

AI tools, especially LLMs, are exciting enablers, but they come with risks. If your product relies heavily on third-party AI remember that everyone has the same tools that you do, which means thousands of teams are building similar AI-powered products. Low barriers to entry mean fierce competition.

Remember: AI isn't a business model; it's a tool. To succeed, build a strong foundation that doesn't depend solely on AI's novelty.

4. Humans Are Often Cheaper Than Code

Technology is expensive, but building the wrong technology is even costlier. Founders often over-invest in automation and scalability too early, solving problems they don't yet have. Instead, embrace "Flintstoning"—using scrappy, manual solutions behind a veneer enabled by technology.

5. Low-Code: A Powerful Start, but Not Always a Long-Term Solution

Low-code and no-code tools like Bubble, Airtable, Webflow, or Framer have revolutionised early-stage building. They're great for idea validation and prototyping, however challenges arise with scaling—collaboration becomes a bottleneck quicker than you think and security and performance often suffer. Know when it's time to re-platform for growth.

6. Tech Stack: Simple Is Smart

Your tech stack matters, but not as much as you think. Early-stage startups should prioritise simplicity, mainstream tools and frameworks with strong community support, and wise use of cloud credits. Ultimately, productivity and flexibility trump chasing the latest tools.

7. LLMs: An Enabler, Not a Silver Bullet

LLMs are transforming productivity and enabling new products, but they're not magic. Founders should understand the cost implications of training and tuning on their underlying COGS, combine AI with experienced engineering, understand the limitations of LLMs, and avoid over-reliance on a single AI vendor.

8. Optimizing for Mindset and Experience

In early-stage teams, mindset is just as important as technical experience. Look for people who prioritise ruthlessly and make tough calls about what not to build, balance early-career energy with seasoned expertise, and are flexible and focused on outputs. Great startups solve real problems with elegant solutions—and that starts with a strong team mindset on output.