Precisely. Demo day planning > heroic last-minute extractions. Forgotten or missed paths can be costly or even disastrous these days. With all the corporate "spray and pray" installs, an opportunity might exist there somewhere.
Skills survive economically when there is liquid demand. If portions of the population shift to reduced or guaranteed income models, spending narrows. Households prioritize rent, food, fuel, and medical care. Skilled labor becomes discretionary. The work still exists, but the buyer does not.
There is a common belief that certain trades are insulated because they involve physical or specialized work. That assumption holds only if customers retain purchasing power.
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Removing a highly embedded operator layer from daily infrastructure could be more complex than simply uninstalling an app.
It could be more like trying to extract wiring from a building after the walls are closed.
But once billions of digital tendrils are woven into booking systems, procurement pipelines, code repositories, financial rails, HR workflows, and customer communications, unwinding them becomes non-trivial.
Efficiency targets don’t wait for perfect guardrails.
At scale, this can start to resemble something less like optimization and more like saturation.
A kind of corporate “spray and pray”, deploy broadly, iterate later, and rely on the fact that most systems won’t fail catastrophically.
Operational agents don’t just assist employees. They compete with headcount. That incentive is not philosophical. It’s financial.
The call inside organizations becomes simple: automate this, automate that. If it can be delegated to an agent, delegate it.
Converting human labor into cost savings rarely gets framed that way publicly. The language is cleaner: “Asset reallocation.” “Workforce restructuring.” But reduction in workforce by any other name is still a layoff.
Substack - zeittrender.substack.com/p/ai-agents-...
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𝚆𝚑𝚎𝚗 𝚘𝚙𝚝𝚒𝚖𝚒𝚣𝚊𝚝𝚒𝚘𝚗 𝚜𝚢𝚜𝚝𝚎𝚖𝚜 𝚜𝚑𝚊𝚙𝚎 𝚋𝚎𝚑𝚊𝚟𝚒𝚘𝚛, 𝚝𝚑𝚎 𝚛𝚎𝚜𝚞𝚕𝚝𝚒𝚗𝚐 𝚍𝚊𝚝𝚊 𝚏𝚎𝚎𝚍𝚜 𝚝𝚑𝚎 𝚗𝚎𝚡𝚝 𝚐𝚎𝚗𝚎𝚛𝚊𝚝𝚒𝚘𝚗 𝚘𝚏 𝚘𝚙𝚝𝚒𝚖𝚒𝚣𝚊𝚝𝚒𝚘𝚗.
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History suggests systems eventually answer that question in their own way. The only real variable left is how we choose to respond while we still can.
#AI #Economy #UBI #Technology
Every job is AI-proof until the customers run out of money.
The real question is not how much AI can produce, but how many people remain economically necessary to the system.
No skill survives without demand. Skills rarely disappear. Customers do.
A plumber, electrician, contractor, mechanic, or medical specialist may remain indispensable in theory. In practice, their livelihood depends on households with the purchasing power to hire them.
Modern economies run on a simple loop: wages create demand, and demand sustains production.
Artificial intelligence may soon break that loop.
Full article links below:
Substack - zeittrender.substack.com/p/economic-h...
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2/2: Then it gets interesting:
• Synthetic feedback: AI-generated content starts training the next models
• Cognitive mediation: The system doesn’t just suggest, it starts shaping what you see, think & decide
1/2: The Convergence Stack isn’t sci-fi, it’s already happening:
• Extraction: Your clicks, scrolls & sensors become training data
• Prediction: Models forecast what you’ll do next
• Optimization: Systems nudge behavior for efficiency
AI isn’t just automating tasks.
It’s building a convergence Stack that turns your data into prediction → optimization → synthetic feedback → regen.
Full article links below:
ZeitTrender - zeittrender.com/the-converge...
X - x.com/ZeitTrender/...
Substack - zeittrender.substack.com/p/the-conver...