Equational

Is failure ok? I was recently asked: " What companies have a culture where failing is ok "? I cheekily answered " None "!  The art of high-performance engineering This is the recipe I have been applying for the last fifteen years: Never f ail to achieve previously promised goals Never f ail deadline because of waiting on others Never f ail to use all your team members Never f ail to stay productive because of exhaustion Never f ail because of misalignments Never f ail because of past work no longer relevant, or past work never finished. To which mostly people say: are you kidding? There is a twist! These are extreme technology projects. Agile deconstructed An agile process typically maintains delivery drive and failure avoidance with process cycling over: Features (what we discuss with our stakeholders) Stories (what we work with) Code (what we deliver) These are primary driving efforts.  I skip the 10+ supporting efforts, such as validating, analyzing, etc. I skip ...

Sixt y years ago, Melvin E. Conway wrote: Organizations which design systems (in the broad sense used here) are constrained to produce designs which are copies of the communication structures of these organizations. — Melvin E. Conway, How Do Committees Invent? (quoting from Wikipedia) How does Conway's finding affect software language design? How does one specify a language that meets the many different communication structures of one or more organizations and yet still preserve formal properties such as security and provability? How do I make a language that does not end up communicated as list of hundreds of recommended design patterns? How does one zigzag between OO, FP, and other programming approaches? How is this related to machine learning and LLMs? Recently I was asked to help on a project. My immediate response was: Tricky, knowing what I know now, I would write a DSL to produce the necessary content for the project, but we cannot afford that for this project, so no DSL. ...

Writing software that actually behaves like pure math is harder than it looks. Usually, state changes, loops, and memory quirks get in the way, turning elegant logic into a tangled mess of side effects. A modern tracing library fixes this by acting as a silent observer. It watches your program execute, sweeps away all the temporary memory junk the computer needed to do the work, and leaves behind a perfect, permanent map of how your data actually flows. By completely separating how the code runs from what the math is, you get a flawless, auditable blueprint of your system. It gives you the exact precision needed to stop fighting your language's quirks and start engineering truly smooth, reliable software. And so last year I wrote a first draft of a Python tracing library (see original https://github.com/equational/hltpy ). This code works, but fails to be elegantly re-entrent: it is tricky to trace interpretations of traces. So today, pressured by a needy use case, I am rewriting t...

If you look at A Prayer for Owen Meany  through the lens of category theory and functional execution, John Irving didn't just write a novel about destiny—he built a strictly commuting diagram evaluated lazily from a terminal object. Stop here if you do not want to know the end or details of the book! FYI: Info is "fuzzed" below to lessen damage. Most novels, and most human lives, execute like an imperative program. They are Markovian. You start at state A, apply a decision, move to state B, and the future is an open, uncomputed tree. Owen Meany’s life operates under completely different mathematical physics. Here is the categorical breakdown of how Owen’s universe functions: 1. The "eventful location" is a Terminal Object In category theory, a terminal object is an object to which there is exactly one morphism from every other object in the category. The "action" in the "eventful location" is the terminal object of Owen’s existence. Every sin...

How to introduce ML in your company? That is the question that I was asked last Friday. I found myself saying "it is tricky, ML typically comes in a right-angle to the people process, and that does not work!" Right-angle? You might say? And you would be right! Therefore I picked up a deck I wrote last November, kept only the key statements, added the context, and recorded a 17m presentation here: https://www.youtube.com/watch?v=08uEBKft_Bg   which will not tell you "why" but "how", as in "how to introduce machine learning in your company". The finer story here, and not highlighted in the presentation is success with or without machine learning is first about your team maintaining maximum performance throughout the project. See it as a rocket that is maintaining maximum thrust. And for that to happen you must carefully ensure that everyone can invest their maximum with a full understanding of what they and the team wants to achieve. Teams may some...

I was recently approached by an ML company setting up shop in Zurich. To be honest, I’m still not sure if it was a real person, an agent, or just a sophisticated scouting bot. But it sparked the question: What exactly do they see when they look at me? I know I can provide crazy value, but within a certain scope. I also know my digital footprint is sparse. To find out what the world thinks of 'James Litsios,' I went into an anonymous Gemini session and asked a simple question: 'Why would someone hire this man for an ML project?' The answer I got shocked me: a highly accurate "slice" of a man who existed ten years ago.  Let's start with Gemini's response (with some annotations in Blue ).  Then I will update you on how I have evolved my core beliefs from the Gemini expressed basis. Gemini Pro's reply to: Who is James Litsios and why would someone hire him to develop a ML application? Dr. James Litsios is a veteran technologist, architect, and leader b...