james_ross

for a long time I've believed that the way to bridge the visual and the textual worlds is to generate the visuals from a plain text source of truth. I've never gone so far as to make a visually editable programming language, but I have done multiple projects where, for example, process diagrams in an IDEF0 style were generated from human readable text propositions of the form:

Prepare Meal is a Process Oven enables Prepare Meal Utensils enable Prepare Meal Prepare Meal transforms Raw Ingredients Prepare Meal produces Finished Meal Menu governs Prepare Meal Customer Order governs Prepare Meal

You can map out a business process using a very simple (and XML-free, and diffable) plain text DSL and generate interactive diagrams from it. My most recent example is for concept maps along similar lines.

this seems to be a load bearing claim in the article: "success is determined by how well a person understands the problem they are trying to solve, not whether they’re trained in coding."

I would normally assume that my understanding of the problem I'm trying to solve is a blend of domain knowledge and system knowledge; that is, some of the what and some of the how. And just as important as bringing domain knowledge to the table is bringing the ability to articulate it with conceptual clarity in a way that bridges to the software. I have met many very deep domain experts who don't have that skill.

My personal interest of late is in capturing domain knowledge and managing it like source code, and using it to share with both the humans (in visual form) and the agents (in plain text form) some of that foundational understanding to make them both better at both the what and the how. This seems aligned with the article when it says "the more understanding a worker brings to an agent, the more quality work the agent is able to do" but I would also say that the more understanding we can bring to future humans new to the domain has pretty good ROI as well.

I'm a massive fan of capturing domain knowledge in a plain text format that both humans and AI can use, one of my favourites being concept maps stored in human readable form. I did a talk on this exact topic long before we all got AI pilled, this version from 2015 for example: https://www.infoq.com/presentations/concept-map/

The web app mentioned in that talk that I built to help with that no longer exists, but I recently built a new desktop app (Apple Silicon Mac only so far, sorry) for this exact purpose: https://thinkingtools.software/concepticon