Sparks

AI is everywhere so I thought I’d see what I could do with it productively.

Working with LLMs has been an interesting experience. My team:

 Me: Architect and Product Owner

 Claude: Lead Engineer (Claude Pro account)

 Codex: Senior Engineer (Codex Pro trial)

 Copilot: Intern (GitHub free account)

Along with setting the project guidelines and directives, managing token spend and task allocation has had its challenges. Keep in mind, I am working with a limited budget.

More than that, being the human in the loop has been quite taxing. LLMs produce code prolifically. Unless I keep the tasks chunked small enough, the AI still strays from the directives:

 APIs/contracts/abstractions first, implementations behind them

 Tests at the API level, spec first

 Run tests locally, then staging; nothing reaches the prod registry until it’s scanned and signed, including public libraries and containers

 Jira tickets are the source of truth for what is designed and implemented, and Confluence pages are composed from Jira tickets for the publishable design. This isn’t standard process, but it’s one I’m championing. It would normally be preceded by a concept doc, but that one lived in my head.

 Use variables and string replacement: be ready for i18n

 …and more

Despite these guidelines, LLMs don’t always stick to them: working context, compaction… Some LLMs go down the rabbit hole more often and burn through their tokens; some are very efficient. Sometimes they do something in one session and fail to do the same in the next. Sometimes they forget. Sometimes they assume. Lots of challenges like that.

In the end, though, LLMs are scary good at writing code. They write a lot of it, and they can do a lot with little guidance.

I handed the AI the autonomy and kept the accountability with me.

Without an effective human in the loop, the code can spiderweb and bloat (I’m sure this will improve; the rate of change is astounding). And AI does make mistakes. I can’t count the number of times it has said “that was my mistake” or something along those lines. But it does recognize and acknowledge them, and the ratio of errors to productive code is small. Sometimes your lead engineer launches into a complicated task and you just have to wait and hope you can assess what was done at the end…

This has been a roughly 6-month project, with a lot of ramp-up to establish processes and guidelines. Most of them had to be discovered along the way and then embedded into the project directive. Only recently did I add more AI engineers and expand the development process (staging, prod environments, etc.).

https://ownerent.com:8085/

As I was filling out the ballot (mail in), I found myself trying to look up the propositions to understand them (with the help of AI), and looking up the candidates in the various categories to check up on their history. I thought to myself, is there a better way? Maybe…

WIP so it is not complete: https://ownerent.com:8085/s/hHATxpCEQV

Analysis and assessments provided by -Groq, Cohere, Qwen3.

This is spark in formation…

Whether we live in a simulation or not is a hotly debated topic, but the thought I had was does the universe split every time a consciousness loses its home?

My thought is definitely more philosophical. It plays on the many worlds idea- simulation just happens to give it a grounding that clings to many worlds but one mind. I am claiming that the self has a singular existence which ends at death. Not unlike data deduplication to some extent, the consciousness exists across all the words but ceases to exist at death. When it ceases to exist across the multiverse, it reverts back to the collective – Brahma? 

Memory by definition is only accessible to self. Memories and their compacted form, which is a light semblance of the real occurrence, thereof is the evidence to ourselves of our existence. 

AI today is a wrapper around some form of an LLM. The LLM matches patterns and the wrapper imitates a type of intelligence that is getting very close to human. Pattern recognition, pattern matching and pattern morphing (all based on probability) can definitely take this technology far but what it doesn’t yet do is generate new knowledge. AI of today is exceptionally better than most humans at seeing more discreet forms of things already known and generating new forms of already known information. 

For the most part AI coding assistants, trained on a tranche of existing code to do everything that software can do, are paraphrasing code already written to do the tasks being requested. Developers have been doing the same for the past decade (and longer). AI agents do it quicker. It’s not magic. It is how generative AI works – pattern, probability, transform, present. 

But keep in mind, what is generated is very narrow and targeted – it’s not yet a holistic solution producer. AI models still struggle with larger contexts and scopes. Whole, cohesive solutions are still your job as the human in the loop.

Claude countered that “paraphrasing” was not the best representation of what was happening. I insisted that it alleviated complication. Yes, “paraphrasing” is over simplification of the way AI training originally ingested and transformed the various code sources to then be able to generate the most probable output but it matches at the high level.

Is the defining property of life simply its access to quantum mechanics as a configuration layer — and everything else just what happens next?

I had a thought – Claude helped me trim the rough edges to form a clearer question.

The most valuable thing we have now is time. But its intangible, unstorable and as yet uncreatable. It can be mined though – from other people when their time is used to achieve something. Kings, feudal lords etc achieved this. It transformed for a bit but is now back in vogue again. Mining people’s time to achieve goals. Its more sinister now and may be headed in an irreversible direction. Much of life is based on repeatability, pattern recognition and replication. This doesnt work for innovation and new ideas, yet. In the past this was part of the downfall of the ruling class. Today, ideas come from the bottom and have a chance to rise. But a common human affliction ensnares them all: to quote NYU professor Scott Galloway – “ Every journey is the same, from Anakin Skywalker to Darth Vader. We think they’re the ones that are going to save us, that they should be president, and then we find out like the rest of them, their job is to do and say whatever will get their share price up… It’s a villain’s journey.” The vast majority of humans keep falling for this repeatable pattern – and are ready to be mined, freely. But, stakes are higher now as the “blast radius” is the size of this planet. 

Humans are creatures of emotions with nostalgia on their brains and euphoria or regret as their drivers. The overlay of our frontal lobe applies reasoning, planning and decision making – making the social human appear out of the living creature.

When wealth becomes so immense and income becomes useless, how should society deal with the extravagant opulence?

A billion dollars would require the holder to spend over 27k every day over 100 years. Growing modestly in even a simple savings account, this is unspendable wealth – over 30 million annually. 

27k — what many Americans scrape through an entire year on — is what a billionaire could burn through before dinner, daily, for a century, and still die rich

Once a person achieves this level of wealth, what else are they gaining besides more bloat to their ego? 

Supporting perspective via Claude:

“Concentrated wealth occasionally backfills what functional public systems would have handled anyway — and gets credited as generosity for doing so.

• The NIH, DARPA, and NASA produced transformative innovations through distributed public funding, not concentrated private wealth

• The polio vaccine came from Jonas Salk, who refused to patent it

• Most Gates Foundation health work operates in areas governments abandoned, which is an indictment of policy failure, not proof that billionaires are necessary”

Does it provide any upsides that don’t leverage ulterior motives? Walk a mile in their shoes and will you see a new perspective or will it confirm the detachment from societal good and self aggrandizement?