Software 4.0

We’ve reached an uncanny milestone in tech. We are building intimate conversational bonds with AI chatbots, yet the software infrastructure surrounding our daily lives remains as rigid, silent, and fragile as ever. LLMs tease us with their facilities to write code, but forcing this new form of intelligence to work with programming paradigms that pre-date the World Wide Web is driving a silent crisis of structural decay in large-scale software systems. This post introduces the Software 4.0 era. Informed by biological processes, it turns software into a living, self-verifying organism that provides the perfect complement to LLMs. It transforms how we build and co-evolve the digital fabric of our world. ...

A 2022 article in Noema magazine describes apophenia as “faulty pattern recognition. People see faces in clouds and alien ruins on Mars. … Humans are pattern-recognizing creatures, and so apophenia is built in.” A Google engineer had claimed an LLM to be conscious, sentient, and indeed a person, and the article explores reasons for why he had reached such a conclusion. It’s well worth a read, particularly its observation that we apply concepts that have wholly anthropomorphic heritage and meaning to LLM technology. Pehaps we need new vocabulary. The technology’s stochastic prowess is much advanced 42 months later, and perhaps that’s all the more reason we continue to see things that aren’t there. Matt Shumer’s “Something Big Is Happening ” is the latest example. ...

Trillions of dollars are flowing into LLM technology and services — that’s not an exaggeration — and yet LLMs can’t grapple with enterprise software. When we invite them to code, to update schemas, to modify configurations, they break things. Constantly. But this isn’t an LLM problem. It’s a software problem. ...

It is important to understand the ways in which software may be conjured into the world for the simple reason that software and information technologies more generally have immense social and economic impact. The genesis of such process has been called software architecture, and there have been various attempts over the years to define the term and corresponding activities precisely, specifically in relation to the elements, forms, rationale, and constraints involved (“What Is Your Definition of Software Architecture?,” 2017). A well-defined understanding of software architecture is critical to its practice and perhaps the word choice alone has helped sustain a certain nature of software architectural practice akin to that undertaken for buildings. The definitional approach taken by Perry and Wolf (1992) is typical of the traditional genre, drawing parallels with the precursors of hardware and network architecture, and their forerunner, the architecture of the built environment. Samuel Butler (1912) observed: Analogy points in this direction, and though analogy is often misleading, it is the least misleading thing we have. To what degree are we misled by the architectural analogy? And might we find a better analogy, that is one that’s less misleading? ...