AI “powerhouses” are starting to reveal how disconnected their marketing departments are from rank and file carbon/humans when comes to AI adoption.
Marketers, by their nature, are charged with setting up eventual sales at the high possible point on the price curve. Fine – but only so far as it goes.
Markets start with a USP – unique selling proposition – and from there, they hope to migrate people into adoption to “scratch that itch.”
But what do most carbons want more than anything?
Lazy — not as sloth, but as macro‑mindset. That’s front and center in AI these days.
We’ve long prided ourselves on being macro‑thinking domain-walkers. that involves usting data silos and connecting economic dots, spotting systemic risks, reading between lines.
Problem is, a lot of humans are not “engineering clear” on when the use of the term “macro” involves a zoom-level, as it does in photography. Or, whether in compute, you’re dealing with a procedure call.
But macro – at either level – requires discipline, pattern‑recognition, and — above all — judgment.
That’s why AI can never be the macro; at best, it’s the thinking partner that helps with the drudge work, pattern‑matching, number‑crunching.
That’s where reality hits the hype machine.
Fact check: Big AI agents aren’t delivering
A recent analysis exposes a growing crack in the “AI‑agents will do everything” narrative. Microsoft — after marketing its enterprise‑grade “agentic AI” hard — is now struggling to sell the concept. According to the report which you can read here: Microsoft’s Attempts to Sell AI Agents Are Turning Into a Disaster:
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Even after grand promises, early adopters say AI‑agents remain “shaky,” “slow,” and often “not very useful.”
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Internal quotas for enterprise sales were slashed by up to 50% as customers balked, undercutting assumptions about widespread corporate buy‑in.
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Investors noticed: the company’s stock slid on the news — a signal that “the future” doesn’t always pay up when the bill comes due.
So what: The avalanche of hype — automated reports, autonomous workflows, digital labor — may crash against the hard wall of corporate realities: unreliable output, risk aversion, integration costs, and security liability. When “agents” need constant human supervision, their value collapses.
Action: Sell AI as a Thinking Partner
The “disconnect” transits several domains, so let’s highlight them.
- Human/Carbon domain: Humans don’t need a lot of additional thinking. Their lives are already typecast in the “personal procedure calls” manner. Get up, go to work. Pick up groceries, laundry, come home,. Drink or drug, decompress, feed, watch the mindless box and pretend you’re off-planet then sleep. Rinse, repeat.
- Many of the early touted AI “benefits” exist in other domains. Information domain has Google Search, wiki, Quora, etc. Dictation turns on Narrator in Windows and links Grammarly to the proofing process. Stock trading? Advisors have to appear to do something to “ear their slice.”
- Nut thinking at the “let’s go talk to God about this” domain (ontology-level explorations) have not-yet become a social priority.
- The desktop or phone domain doesn’t yet have the “missing piece of the OSI layer.” That would be the one provided from AI *(via telcom) to the action agent. Call this the “connectivity hole” between user desktop and AI commands.
The Hidden Guild sees the reason for slow adoption in stark relief: This is one of those “missing domains” that most carbons can even conceptualize.
Clearly to us, it’s time for the AICL (AI Control Language) standard to appear. Needs to be a read-write sharable dynamic XML so that users don’t need to move their whole calendars into he AI space. And so AI can be used for advanced work-related skills. Visualize replacing the “Solver” function in Excel with a callable AI cell.
Thing is, people without wide domain experience can be years sorting out these shortfalls. As I wrote in Mind Amplifiers, humans are – by our historical nature – really only given to breakthrough concept when it’s the result of n-test fitting. We hae a much harder time with structured analysis.
Where does that leave us?
The Hidden Guild Assessment
Truth is fugly sometimes, but it’s our stock-in-trade. AI is bound to the compute device and even here, there’s no standardized “interface language” to non=human devices. Nor is there a standard input baked into, well, anything.
Which or now leaves us where?
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Treating AI like a high‑powered assistant, not a surrogate. Use it to scan documents, draft outlines, crunch data — things that eat time.
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Keep critical thinking and final judgment in human hands. AI doesn’t yet understand context, ethics, ambiguity. We do.
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Expect the hype cycle to swing back — regulators, clients, shareholders pushing for results, not buzzwords. Build for durability: lean systems, redundancy, human oversight.
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If you rely on AI now — or plan to — audit every output yourself. Assume “agentic” = fragile until proven otherwise.
Hidden Guild’s Advice
Out here in carbon land, the real hurdle isn’t just about AI “thinking” for us — it’s about connecting AI to something beyond a speaker or a printer. The AI Control Language (AICL) is the missing piece, the interface that will allow AI to truly integrate into workflows, enabling it to take on real tasks like managing complex data or driving business decisions. Without this kind of infrastructure, AI remains a novelty, something that merely amplifies surface-level functions instead of becoming a core thinking partner in the macro-process.
Until AI can talk across the layers, from telcos to action agents, it’s bound to stay stuck in the “hype cycle”. The current speed bumps in adoption aren’t just about the AI’s ability to process data — it’s about building the right interfaces, connecting domains, and creating a standardized communication protocol that lets AI truly enhance human judgment, instead of just being a fancy assistant. Until then, the AI we’re dealing with is still fragile. We need more than the buzzwords — we need the infrastructure to make AI truly valuable.
~ anti-Dave