Artist's co-founder warns that the biggest mistake founders make is building technology too early. Her team validated their text-based learning concept by manually texting early users, confirming the core hypothesis and user engagement before committing significant engineering resources.

The job of an early founder isn't to be right, but to discover the truth about the market. This requires shipping imperfect products quickly to test assumptions, gathering harsh feedback, and being humble enough to accept when you are wrong.

Founders often get stuck endlessly perfecting a product, believing it must be flawless before launch. This is a fallacy, as "perfection" is subjective. The correct approach is to launch early and iterate based on real market feedback, as there is no perfect time to start.

Companies with radical, long-term visions often fail by focusing exclusively on their ultimate goal without a practical, near-term product. Successful deep tech companies balance their moonshot ambition with short-term deliverables that provide immediate user value and sustain the business on its journey.

Todd Graves reflects that his early desire for perfection was a mistake. Delaying a new training program's rollout until it was "perfect" lost valuable progress. He now advocates for releasing "Version 1" of any internal process and improving it over time, prioritizing progress over perfection.

The software-centric Minimum Viable Product (MVP) model is ill-suited for hardware. Instead of aiming for a 'viable' product, focus on a 'testable' one. This allows for controlled pilot deployments to gather real-world data and iterate before committing to expensive, hard-to-change physical designs.

To overcome high AI pilot failure rates, companies like Pace use "forward deployed engineers" (FDEs). These founder-type individuals work onsite, deeply understand customer problems, and do whatever it takes—from prompt tuning to data cleaning—to ensure successful production deployment.

Moving from a science-focused research phase to building physical technology demonstrators is critical. The sooner a deep tech company does this, the faster it uncovers new real-world challenges, creates tangible proof for investors and customers, and fosters a culture of building, not just researching.

Gecko Robotics' founder bootstrapped for years by developing robots directly inside power plants. This "build in the real world" ethos contrasts sharply with the typical VC-backed lab development model, leading to a more robust and customer-aligned product.