How To Get Your First Users

Predictions and Expectations:

• The speaker expects that many consumer companies will still be created despite the challenges.
• The speaker believes that most products evolve from basic functions (amoebas) into mature products with millions of users (humans or dogs).
• The speaker predicts that consumer apps will struggle because ads often do not cover AI costs and subscriptions must squeeze into a small personal budget.
• The speaker anticipates that the Tesla Model Y's characteristics (e.g., fast acceleration) are the result of early adopters valuing tech and acceleration over comfort, and implies that a mass market vehicle designed in a vacuum would likely not have a zero-to-60 time of under three seconds.
• The speaker is not sure if a mass market vehicle designed in a vacuum would have a zero-to-60 time of under three seconds but implies the answer is probably not.

Timelines and Milestones:

• No specific timelines or dates were provided in the text.

Technology and Product Direction:

• Startups should build a "Minimum Evolvable Product" rather than just a minimum viable product to allow for evolution based on market pressures.
• Early startups should engineer a "wide surface area" for early users to find them since founders do not yet know who these users are.
• Founders should expect to run constant experiments on pricing, landing pages, onboarding, and features.
• The speaker expects that the final shape of a product will depend on the starting point and the specific early users chosen.
• The speaker believes that if Tesla's early adopters were willing to pay for a slow, plush vehicle, the cars would look very different today.

Market and Industry Outlook:

• The speaker expects that many AI founders will choose to start by selling to prosumers, businesses, or high-value users like doctors.
• The speaker observes that the average personal software spend is small (about $150 a month) compared to corporate software budgets.
• The speaker expects that early adopters and people with burning problems are rarely price sensitive.
• The speaker expects that finding first users is more of a search problem than a persuasion problem.

Company Plans:

• The speaker expects that startups fighting irrelevance will not write public reports about bad experiments, unlike big companies.
• The speaker expects that founders can usually fix relationships with users who are annoyed, as the relationship is personal.
• The speaker expects that if a user churns, there are plenty of others who haven't heard of the product yet.

Financial Guidance:

• No specific financial guidance or numbers regarding revenue targets were provided.

Risks and Caveats:

• The speaker notes that early adopters are willing to take risks on products that may be impractical or lack basic infrastructure (e.g., Tesla Roadster lacking public charging).
• The speaker cautions that charging real money early is necessary to get sharper feedback than free users provide.
• The speaker warns that using broad outreach like billboards is less likely to reach early adopters compared to targeted personal outreach.

Confidence and Disagreement:

• The speaker states the lesson about finding users is "simple" and implies high confidence in the "Minimum Evolvable Product" framework.
• The speaker uses the hedge "probably true" regarding the financial interpretation of the Tesla Roadster funding CapEx.
• The speaker uses the hedge "probably not" regarding whether a mass market vehicle designed in a vacuum would have under-three-second acceleration.