I’ve been thinking about something along these lines for some time. I really like the direction of this.
The challenge I see more broadly is we (as engineers now empowered by LLMs) are trying to find the right level of abstraction to operate in. Writing long form sentences and (sometime) reviewing the output feels too far away. But having an LLM work directly with you in an IDE feels too close to “the old way”.
Personally for me the approach here still feels a little too close to the lower level old way, but it’s better than the two approaches above.
Right level of abstraction is a good way of putting it. It's basically like creating a custom DSL, but flexibility of LLMs allow the DSL to be ad-hoc.
At what point will you need formal rigid syntax? Or is not having rigid syntax the point? If the latter, how much "informational noise" or ambiguity can you inject before the "DSL compiler" gets confused?
Scaling is another bit. Convertible Psuedocode a great pattern for writing functions, but is it useful for writing modules? If you're writing a paragraph to change behavior of a function, you're underutilizing LLMs. Paragraphs are best for spec'ing modules, and the LLMs already fill in the blanks. Not sure if it would be faster to psuedocode the entire module (although maybe just the interface would be a sweet spot...)
Why not just put an instruction into your favorite harness’ system prompt: “If I give you pseudo code, spell out my intent, and then write and test it in real code.”
Definitely an approach worth exploring! I actually started to look into semi formal spec language like Quint because I wanted something more structured then prose, so I feel like this goes into the right direction.
Writing fizzbuzz requires that you understand algo + you credit card, while agent requires only your credit card. I believe most of people will pick the 2nd one.
Yes for many non-technical people who are building stuff for the very first time, this is absolutely true. Natural language will always be easier for them. But experienced engineers are wanting to use AI for very complex codebases, and AI struggles significantly beyond a certain point.
You seem to be conflating two things: how to prompt, and how to share sessions. You can already use pseudo-code today if you want to. As for sharing, you can commit (a link to) it, use `git notes` (as I do), or a service like entire.io.
I think you should work on your differentiation. The session management stuff is the greater concern, in my opinion; pseudo code is not a novelty.
Help me understand - what do you mean be "share sessions"? And yes you can definitely use pseudo code today - that in and of itself is not a novelty at all. The specific novelty is the fact that the editor assumes two equivalent sources - your pseudocode which acts as a prompt, and the source code generated from that prompt. The editor also provides a source map for the two, so that as a codebase grows in size and complexity, it's trivial to link a specific section of code back to a human's written intent.
I’ve been thinking about something along these lines for some time. I really like the direction of this.
The challenge I see more broadly is we (as engineers now empowered by LLMs) are trying to find the right level of abstraction to operate in. Writing long form sentences and (sometime) reviewing the output feels too far away. But having an LLM work directly with you in an IDE feels too close to “the old way”.
Personally for me the approach here still feels a little too close to the lower level old way, but it’s better than the two approaches above.
Excited to see where you take it!
Right level of abstraction is a good way of putting it. It's basically like creating a custom DSL, but flexibility of LLMs allow the DSL to be ad-hoc.
At what point will you need formal rigid syntax? Or is not having rigid syntax the point? If the latter, how much "informational noise" or ambiguity can you inject before the "DSL compiler" gets confused?
Scaling is another bit. Convertible Psuedocode a great pattern for writing functions, but is it useful for writing modules? If you're writing a paragraph to change behavior of a function, you're underutilizing LLMs. Paragraphs are best for spec'ing modules, and the LLMs already fill in the blanks. Not sure if it would be faster to psuedocode the entire module (although maybe just the interface would be a sweet spot...)
Dumb question:
Why not just put an instruction into your favorite harness’ system prompt: “If I give you pseudo code, spell out my intent, and then write and test it in real code.”
Are we supposed to be able to read the examples with our eyes? It looks like black text on a very dark grey background on my iPhone.
EDIT: same on Firefox on my Mac (macOS Ventura).
Pushing a fix now - thanks for letting me know.
edit: fixed
Definitely an approach worth exploring! I actually started to look into semi formal spec language like Quint because I wanted something more structured then prose, so I feel like this goes into the right direction.
Writing fizzbuzz requires that you understand algo + you credit card, while agent requires only your credit card. I believe most of people will pick the 2nd one.
Yes for many non-technical people who are building stuff for the very first time, this is absolutely true. Natural language will always be easier for them. But experienced engineers are wanting to use AI for very complex codebases, and AI struggles significantly beyond a certain point.
You seem to be conflating two things: how to prompt, and how to share sessions. You can already use pseudo-code today if you want to. As for sharing, you can commit (a link to) it, use `git notes` (as I do), or a service like entire.io.
I think you should work on your differentiation. The session management stuff is the greater concern, in my opinion; pseudo code is not a novelty.
Help me understand - what do you mean be "share sessions"? And yes you can definitely use pseudo code today - that in and of itself is not a novelty at all. The specific novelty is the fact that the editor assumes two equivalent sources - your pseudocode which acts as a prompt, and the source code generated from that prompt. The editor also provides a source map for the two, so that as a codebase grows in size and complexity, it's trivial to link a specific section of code back to a human's written intent.