What eight years of building an AI company taught me about timing

Founders are often told that timing is everything. The advice sounds obvious, but it is not particularly useful when you are inside the company, making decisions with limited information. You rarely know whether you are early, wrong, or simply not patient enough.

When we started AI Palette in 2018, artificial intelligence was already widely discussed. Yet enterprise adoption—especially within consumer-goods companies—was still cautious. The technology could reveal valuable signals, but customers were not necessarily organised to act on them. We were building both a product and the confidence required to use it.

Being early creates two jobs

If you enter a market early, you do not only have to build the solution. You also have to help the customer understand the problem in a new way. That education can become an advantage, but it consumes time, capital and founder attention.

The mistake is assuming that technical readiness and commercial readiness arrive together. They rarely do. A product can be impressive and still be difficult to buy, integrate or trust. In enterprise AI, the distance between a successful demonstration and an operational decision can be enormous.

Three clocks have to align

I now think about timing as three separate clocks: the technology must be capable enough, the customer must feel sufficient urgency, and the company must have enough resilience to survive until the first two align. Founders tend to obsess over the first clock and underestimate the other two.

Good timing is therefore not merely predicting the future correctly. It is designing a company that can keep learning while the future arrives. The best early-stage strategy is often the one that buys you another cycle of evidence without losing sight of the larger thesis.