Daniel Miessler has posted a provocative essay with the attention-grabbing headline: "How AI is Eating the Software World". (*) He subtitles his essay this way:
The future of software is asking smart questions to a mesh of APIs running layered models
Meissler posits three architectures:
- "Outcomes" which is pretty much conventional software design: Inputs, controls, task or process, and outcomes.
- "Understanding" which he thinks is the not-too-distant world of generative AI. A progressing stack of data (unorganized and unevaluated), information (organized data), knowledge (integrated information), and understanding (all before applied in context with situational awareness)
- "SPA" which he has coined for "state" (present situation, but multi-dimensional), "policy" (... "which is your desired state and the set of things you want and don’t want to happen"), and "action" (..."which is the recommendations or actions that can be performed to bring the STATE in line with the POLICY.")
Eventually, the software that runs a project or a business will be defined by a number of APIs that address various layers of multi-dimensional sources of "understanding" but work in a SPA kind of architecture.
Need something new in the SPA? Define an API, or buy it from someone else.
Need to offer something to a customer? Give them access to an API that pulls from your company's value-add stack of "understanding".
Now Miessler readily admits that the current generation of generative AI tools are not ready for business or project prime time because what you get is not predictable or necessarily repeatable (if you run a generative AI query 10 times you are likely to get 10 different answers. That's a no-no for most business or project processes)
Like I said, a provocative essay.
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(*) An essay from 2011 by Marc Andreessen, with a similar title, is this one: "Why Software is Eating the World"
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