Code Generation AI is all the rage these days. But is generating code for programming languages like JavaScript and Python the right path to take? I think not. I think we should be generating code for declarative languages like Excel or SQL.
What's the difference, you ask?
In declarative languages, you express what your intention is. For example, in Excel, you can use SUM() to add all the line items and calculate the order amount. If the quantity of a line item changes, it will automatically recalculate the line item amount and then invoke SUM() to recalculate the order amount. But in imperative languages like JavaScript or Python, you instruct the computer on how to calculate the order amount. You would implement a function to add the line items as the order amount. Anytime the quantity of a line item changes, it is your job to call the function and recalculate the order amount.
Why is this important?
If you are asking AI to generate code for your requirements, you are essentially expressing your intent. So, expressing it in a declarative language seems natural. This will help the person who gave the requirement to understand the code generated by the AI. On the other hand, generating code for a programming language seems like the worst form of leaky abstraction. "Leaky abstraction" describes a scenario where attempts to simplify a system end up requiring users to understand its underlying complexities to troubleshoot it. Code generation can automate the creation process. But, the resulting code can be a puzzle even to a skilled developer who is debugging it. The person who gave the requirement will most likely not understand any of it.
So, why do AI companies generate code like this?
I guess it comes down to the availability of training data for AI. There are a lot of open-source projects in JavaScript or Python, so it is easy to train AI with it. But open-source projects in Excel are almost non-existent. So, the unavailability of training data might be the primary reason behind the direction these code generation AI companies are taking. At Neartail, we are taking a middle road. We have created a declarative language using JavaScript syntax so that we could train the AI as well as make it understandable to business owners. Will other AI companies realize the perils of leaky abstraction and change its course? Only time will tell.
Comments (3)
Apr 23
I think you are heading in the right direction. I had a similar idea about a year ago and spent three months contemplating it because creating a programming language seemed a bit daunting. In September, I began the development, and about a month ago, I released a new programming language named Plang (short for pseudo language). It embodies what you describe as intent programming. You can find the repository here: https://github.com/plangHQ It’s remarkable how much less code is required, and there are significant security benefits as well.
Apr 24
Plang looks great, Ingi! I liked Lojban because of its intersection between human language and software. However, being AI-native and in English gives Plang a very good shot at this problem. All the best!
Aug 8
how can train the ai
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