To determine pricing, explore how your target customers pay for similar software products, whether it's a flat fee, per usage, or other structures, and align your pricing strategy accordingly.

Simplify and scale with tiered pricing; avoid having too many tiers to prevent confusion and ensure that your pricing aligns with your ideal customer profile.

It's important to keep pricing simple; complicating pricing structures can kill the sales process, and committed recurring revenue is preferable to usage-based pricing, especially during economic downturns.

AI companies should align their pricing with what matters to their customers after demonstrating value, rather than relying solely on fixed or consumption-based pricing models.

Usage-based pricing, where customers pay based on consumption, is gaining popularity, especially among cloud providers and AI products, as it scales with user demand.

If you're offering something for free but your business model relies on other revenue streams, it's crucial to explain that to users to alleviate their concerns and build trust.

Keep your pricing simple and transparent; complexity can deter customers from making a purchase decision.

Don't set pricing based on compliance as a sales strategy, as it can lead to complications and customer dissatisfaction. Don't discourage adoption through your pricing model; think of pricing as an invitation, not a barrier, to make it easy for new users to adopt your product.

Project-based pricing is common in consultancy and professional services, but founders should transition to more scalable pricing models as soon as possible.