Sourdough, Starters, and the Art of Patience: What Baking Teaches Founders About AI
Let’s talk about sourdough starters. No, this isn’t a culinary detour (though, if you haven’t yet gotten your hands doughy, check out this sourdough starter recipe). Instead, let’s make a case for why every entrepreneur or marketer working with AI should care about the humble, bubbling jar of flour and water living on a kitchen counter.
Fermentation is Iteration
A sourdough starter isn’t bread. It’s potential—the living, slightly unpredictable foundation for bread. You feed it, you wait, you adjust. Sometimes it bubbles over with enthusiasm; sometimes it sulks and refuses to rise. Sound familiar? If you’ve ever tried wrangling an LLM, coaxed a recommendation engine to be less weird, or watched a chatbot invent new facts, you’ve already played this game.
Just like a starter, AI systems (especially those built on machine learning) thrive on incremental care. You don’t get a perfect loaf on day one. You don’t get a perfect model after the first round of training. Growth is uneven; progress is not linear. The starter needs to be refreshed, discarded, fed—so does your data pipeline and your prompt engineering. Ignore it and you’ll have a crusty mess. Hover over it obsessively and you’ll probably end up with the same.
Uncertainty is the Point, Not the Problem
There’s a reason why sourdough bakers talk about “reading” their starter. There’s no universal, scientific timer that tells you when it’s ready—just a combination of bubbles, smell, and instinct. Algorithms share this trait. Despite all our dashboards and metrics, we’re still peering at outputs, sniffing for signs of readiness, and making judgment calls about when to launch, retrain, or pivot.
This is uncomfortable for those of us raised on the myth that technology is always rational, always measurable. But, like sourdough, AI sits at the intersection of science and art. You can optimize, but you can’t automate away every variable. Sometimes you have to trust your gut (or, less poetically, your small batch test results).
Discard Isn’t Waste—It’s Learning
Ask any baker: you have to discard some of your starter every day. It feels wrong, at first. Wasteful. But it’s essential for a healthy culture. In AI and business, we’re not great at discarding. We hoard data, features, even entire product lines, just in case they someday become useful. But progress often comes from letting go—pruning models, sunsetting experiments, killing off underperforming automations.
What bakers call “discard,” technologists might call “iteration.” It’s not a loss, but a reset. The next version is better because you had the humility to admit the last one wasn’t quite right.
The Human Is in the Loop
The most experienced bakers will tell you they never really “master” sourdough. There are too many variables—season, humidity, the mood of the microbes. The same is true for AI. You can’t just set-and-forget. You’re in a relationship with the system. It changes, you change, and the process is alive as long as you’re paying attention.
This is the philosophical underpinning of human-centered AI. Not AI as oracle, but AI as starter: powerful, unpredictable, needing your input to become something valuable. It asks for your patience, your willingness to experiment, and your acceptance that perfection is a mirage. The best results come from partnership, not abdication.
Actionable Business Recommendations
- Embrace small-scale experimentation: Like a baker with a single jar, start AI projects in contained environments. Iterate before scaling.
- Don’t be afraid to discard: Regularly review and prune underperforming automations, models, or data. Stale inputs lead to stale results.
- Invest in “starter maintenance”: Prioritize ongoing care—monitor performance, retrain models, and solicit feedback. Treat your AI like a living process, not a finished product.
- Trust, but verify: Use intuition to guide experimentation, but always validate outcomes with real-world data and user experience checks.
- Stay human-centered: Remember, AI is here to augment, not replace. Keep humans in the loop, both for quality and for a little unpredictability—the same secret ingredient found in every good loaf of bread.
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