Over time, I’ve developed a fairly systematic way of using AI as part of my roasting workflow, and it has significantly improved my results. My own focus is the Vienna profile, so that is the framework these tools are built around, but the same basic approach could be adapted to whatever roast profile you prefer.
I’m using two separate Grok projects. One is dedicated to bean selection, and the other is dedicated to roast analysis. The bean-selection project is built to research a coffee lot deeply before I ever buy it. It looks at origin, altitude, variety, processing method, density, moisture, chaff tendencies, flavor evolution from lighter roasts into Vienna, freshness window, and any existing Bullet profile experience it can find. It also weighs how different processing methods tend to hold up at darker roast levels. Each bean is then rated on a 1 to 7 scale for its suitability for Vienna.
The second project is focused on the roast graph itself. That one is built around my Vienna workflow and evaluates the curve in a structured way: charge and early phases, mid-roast behavior, first-crack phase, post-first-crack development, likely strengths, likely defects, and what to change next time. It also helps me stay disciplined about preheat choice, momentum, fan usage, DTR, and second-crack approach instead of just roasting by feel and hoping the cup turns out. In addition, all of my final, tweaked recipes are stored in the source files and analyzed for possible application to a new bean recipe, or for an AI-produced hybrid of several recipes. That gives me a very strong starting point when I am approaching a bean I’ve never roasted before.
What has impressed me most is not that AI “knows coffee,” but that it helps organize and apply a lot of roasting logic consistently. It forces me to think more clearly about bean suitability before I buy, and it gives me a more objective post-roast review than I would get from memory alone. In my case, that has translated into better bean choices, fewer wasted roasts, cleaner Vienna development, and more consistent results in the cup.
I’m not using AI as a substitute for experience or tasting. The cup still has the final word. But I am using it as a research assistant and roast analyst, and for me it has been remarkably effective. It has made my decision-making more systematic and has improved both my confidence and my outcomes.
For anyone roasting on the Bullet, especially if you keep detailed notes and roast for a specific target like Vienna, AI can be a very useful tool. The key is giving it strong instructions, good roast data, and enough context to evaluate the bean and the graph in a way that matches your own roasting goals.