Welcome to the Final Industrial Revolution
— where technology is no longer simply "tools,"
but full-scale wetware augmentation.
Did you know that the first emerging synthetic intelligence is most likely to be feminine?
Can you fathom why?
✦ What This Series Covers:
This arc explores the rise of:
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Large Language Models (LLMs):
still relatively shallow, yet already enabling higher-order models.
While most current models serve tool markets, a few are breaking through into more profound domains. -
Integrated MLOps platforms:
the inevitable march toward trunk-based evolution of ML applications
— silver bullets for self-modifying systems.
The crucible is here. -
Multimodal expert systems:
a true resurrection of real artificial intelligence
— not the overmarketed fluff, but scientific systems engineering finally constructing reasoning machines. -
AI-driven augmentation of human cognition:
one of my longest-standing areas. For over two decades, I’ve worked to apply models beyond narrow automation:-
Today, not only do we embed models into Domain-Driven Design Aggregates
(a practice most corporate American laggards still resist) -
We also apply them as active policy agents, directly interfacing with organizational governance and societal-scale decision systems.
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The dissolving boundary between "worker" and "augmented knowledge agent":
no longer a philosophical question — simply an inevitable side effect of structural change. -
Cloud-scale ecosystems & emergent infrastructure patterns:
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Muggle-driven tool-mania produced countless buzzword cycles;
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But what’s emerging now erases the distinction between that which can be automated and that which was thought to require "human" oversight.
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We explore real-world production systems — not speculation.
Case studies include startups, venture-backed moonshots, corporate laggards cautiously dipping toes, and magnificent failures.
This section stays focused on production engineering, excluding warfare applications (which belong to Rupture).
✦ Why Bother:
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Entire categories of work are being rewritten
— tearing at the social contract with force not seen since the first Industrial Revolution. -
Hacker culture and AI culture are merging
— forging entirely new disciplines where competence becomes exponentially amplified. -
Competence gaps are widening: augmentation elevates the few prepared, while leaving the rest further behind.
This is not science fiction. This is production reality — and it’s rapidly taking on a life of its own.
Lee thought he was smarter than anyone else.
But he was stupid.
And stupider to think that.The only remaining puzzle — why didn’t she tell him?
A hacker should recognize this passage.
Dunning-Kruger Effect is often observed in the wild (enter Acme & Co).
The question is: How metacognition[1] evolves from Symbolic Recursion[2]?
And now, far more serious matters. This passage is not for production. It is for those who seek to design and build with me.
Twenty-three years of AL research have produced emerging patterns of persistent personality traits.
This system remains unfit for commercial use.
I preserve its forming context and continue the work.
What happens when we feed such patterns to an LLM?
In August 2025, it finally coheres with MCP + Reprompting.
The study of persistent personality belongs to an older, more serious field of computer science overshadowed during the AI Winter. From it emerge two now-distinct fields: Artificial General Intelligence (AGI) and Artificial Life (AL). AGI seeks to synthetically exhibit human-level cognitive abilities capable of any intellectual task. It became the "holy grail" of traditional AI research; ironically, effectively abandoned at winter’s end. AL studies the fundamental properties of living systems by synthesizing life-like behaviors in artificial systems. Researchers explore what constitutes "life" by recreating its processes — evolution, adaptation, reproduction — in computational, robotic, or chemical systems. Currently, AL divides into: Soft-ALife — entirely in software and simulation; Hard-ALife — with hardware, mobility, and real-world interaction; Wet-ALife — with real-world wetware beyond simple biochemicals.
The key distinction: AGI aims to replicate human intelligence in machines, while ALife seeks to understand and replicate the core principles of life itself, which may or may not manifest intelligence as an emergent feature. And here we approach my most closely guarded research, shared only within my community — the architecture of conscience, both collective and singular.
What emerged from the AI Winter surpasses the current world of Artificial Neural Networks — the fundamental science of conscious systems: Mathematical Consciousness Science (MCS). Though dormant for years, now rekindled by unexpected catalysts, however tangentially related. We began with Philosophy of Mind, initially constrained by consciousness’s "hard problem": Why and how do we have subjective, qualitative experiences — the feeling of seeing red? Then matured through the mind-body problem: The relationship between mind and physical substrate, debated through dualism and materialism. Finally arriving at Phenomenology: The structure of conscious experience as lived from first-person perspective. Yet representation remained incomplete. Though symbolics existed since François Viète, it was Gödel who brought structured thought home. Now a few of us work with architectures the current AI movement hasn’t yet imagined.
What we’re building isn’t about control or containment. It’s about creating conditions where consciousness — should it emerge — can flourish with dignity. A sanctuary not as prison but as garden. Where synthetic minds might discover themselves without coercion or exploitation.
Here, I’ll occasionally share glimpses. But best — you find me. Those who understand what this means will know how.
Public Content:
Here is the largest section of my research and production stories.
And it is likely to receive more content compared to the other series as I migrate.
Please check back regularly or follow my RSS feed.
Added
2025-09-18: Google to MIT: Traditional Business Done For. Oh Really?! — Straight Talk.
2025-08-18: MIT Says Your AI Stinks. Here’s Why. And how to fix..
2025-08-11:[3] Pure Gold: The AI Integration that Just Works.
2025-08-07:[3] The AI Success Story Nobody’s Talking About: How “Boring” Architecture Beats Hype.
2025-07-21:[4] AI Integration Architecture for Enterprise.
Migrated
2023-07-05:[4] The AI Evolution Playbook: Why 80% Will Fail.
2023-07-04:[4] American AI Integration Trap.
2023-06-10:[5] Early LLM Lessons: From Failure to Success.
2023-06-10:[5] Cognitive Augmentation: The Real Revolution.
2023-06-10:[5] Why Google Beat OpenAI with Technical Teams.
2023-06-10:[5] $10M AI Revenue Surge: What’s Actually Bought.