This is not likely to happen for a few years, if ever.
Airtable is a closed formulaic system like Coda and many other no-code platforms. There is no “code” [per se] for it to learn from because you are writing psuedo code to begin with. Formulas in Airtable are an abstraction from actual code, so it has no corpus to gain intelligence from.
So either Airtable must train a fine-tuned LLM and bake it into the formula editor, or it must open-source the underlying proprietary abstractions. It’s a lot of work, and it requires internal access or independent development of a comprehensive formula parser.
If you spend a lot of time trying to create an AI approach to AI-assisted formula creation, I predict you will be deeply disappointed. Airtable will do this internally [eventually]. The market pressure to make formula development possible, fixable, and understandable from natural language prompts will be intense. They’re likely working on this already because they have the psudo-to-code translator, and that’s all that’s needed to:
- Create a few-shot prompt/training process that transforms a natural language query into code and then into their formulaic representation.
- Create a few-shot prompt/training process that transforms a natural language query to read a formula and explain what it does.
- Create a few-shot prompt/training process that transforms a natural language query to explain how to fix a formula that is not working.
This is the trifecta of AI and formulas; create, fix, explain. No one outside of Airtable will ever be able to do this well, and if someone manages to find a way, it probably won’t be financially practical. Best to keep the pressure on Airtable to do this right away.
If you want to use AI to make something useful in Airtable, focus on users and their data . That’s where the value will be for external AI solutions.