What Early-Stage Founders Often Get Wrong About Tech

Launching a startup today feels like a race against the clock. Founders see competitors sprinting to market, investors demanding traction, and headlines celebrating record-breaking speed.

In the scramble, it’s easy to treat software like a magic lever. But after working with dozens of early-stage teams, we see how it can derail promising ventures long before they run out of runway.

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1. Building Tech Too Soon

“Once we have tech, we’ll get customers”

That ‘build it and they will come’ mindset is seductive, but it rarely pays off. A chunky product build locks in assumptions about who your customer is and what they need… assumptions that are almost always wrong on the first try. The startup that wins is usually the one that understands its users best, not the one that ships the heaviest codebase first.

Try this instead

• Customer-discovery sprints: 20–30 conversations before you build any product
• Low-fidelity prototypes: Figma screens, a Typeform, or even a slide deck to test willingness to pay
• Pilot customers: Can you gain commitment from a few customers to work with you, even if it’s initially quite a manual version of the product

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2. Building Too Much Tech

“Our customers need the full enchilada from day one”

We often see founders over-engineer their first wedge to market and weigh it down with features. The risk is that the features you add to your v1 cost you time and money without meaningfully proving or disproving your hypotheses about early users, and can just become tech debt in your v2.

The leaner your stack, the lower your maintenance overhead and the easier it is to pivot when (not if!) customer feedback surprises you.

Try this instead

• No code or vibe code first: We’re always using the likes of Airtable and Bubble to get to a paying user without the requirement of a full dev team.
• Handcranking: Early Airbnb bookings were confirmed by the founders in Gmail… that was fine until it wasn’t - at which point they knew exactly what needed automating.
• Feature ruthlessness: Launch with a simple wedge to market that delivers the promised outcome. Everything else can wait.

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3. Trying to Automate Your Way to Product-Market Fit

‘We can be so efficient with AI!’

Whilst it’s true we’re seeing some of our software engineers code 10× faster with AI copilots, fully delegating product development to AI introduces some risk:

1. Misaligned outputs: AI can happily churn out solutions but it quickly goes off the rails without an experienced hand guiding it to the right solution.
2. Lost customer intimacy: Manually performing some select customer facing tasks is invaluable when it comes to understanding the end to end journey and what is and isn’t working. If you have no touch points, you lose a lot of context.

Try this instead

• Human-in-the-loop: Use AI where it makes sense, but quality control the outputs with a human, and try to interact with your customers personally where you can
• Incremental automation: Automate tasks only after they’re done manually at least ten times and the edge cases are known.

Ultimately, the most capital-efficient founders treat technology like a scalpel, not a sledgehammer. They start with deep discovery, deliver the smallest useful slice of value, and introduce automation only when the manual version is bursting at the seams.

If you can resist the urge to over-build or over-automate, you give your startup its greatest asset… the agility to learn faster than everyone else. And in early-stage ventures, learning velocity beats launch velocity every time.

If you want to chat about venture building, drop into our DM’s at hello@palomagroup.com

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