Whatever Happened to Blockchain?
There was a time, not very long ago, when every serious-looking technology presentation was legally required to contain the word “blockchain.”
Not Bitcoin. Not cryptocurrency. That was vulgar. That was for libertarians, speculators, Reddit degenerates, and people explaining at dinner why money would be obsolete once everyone understood hashes.
No, I mean blockchain.
Respectable blockchain.
Enterprise blockchain.
Blockchain for shipping. Blockchain for healthcare. Blockchain for identity. Blockchain for voting. Blockchain for land registries. Blockchain for supply chains. Blockchain for certificates. Blockchain for banks. Blockchain for governments. Blockchain for anything that could be represented, however awkwardly, as a row in a database.
For a while, every problem in the world seemed to be one distributed ledger away from being solved.
Then, somehow, it all went quiet.
Bitcoin did not disappear. Crypto did not disappear. The speculation, fraud, innovation, absurdity, technical brilliance, casino economics, and ideological theatre of cryptocurrency are still very much with us.
But the other blockchain — the one that haunted corporate strategy decks, innovation labs, consulting reports, and conference panels — mostly vanished from polite conversation.
So what happened?
The short answer is that blockchain was real technology attached to a fake universal use case.
The longer answer is more interesting.
The Tech Fad Machine
Technology has a recurring disease: every few years, it discovers a useful idea and immediately pretends it is a universal principle.
This is not new.
We had “multimedia.” We had “push technology.” We had “Java everywhere.” We had “Web 2.0.” We had “big data.” We had “the cloud.” We had “the Internet of Things.” We had VR, then AR, then XR. We had the metaverse. We had NFTs. Now we have AI, which is both genuinely transformative and already surrounded by a fast-growing halo of nonsense.
The pattern is familiar.
First, a real technology appears. It solves something, or at least demonstrates that something previously difficult is now possible.
Then comes the second wave: people who understand the technology poorly but understand the fundraising possibilities extremely well.
Then the third wave arrives: consultants, executives, conferences, government reports, white papers, pilot programs, and innovation departments with glass walls and uncomfortable chairs.
Finally, the adult question returns:
What problem does this actually solve better than the boring alternative?
That question is merciless. It does not care about architecture diagrams. It does not care about conference excitement. It does not care that your technology has “decentralized” in the name. It wants to know why this is better, cheaper, safer, simpler, or more robust than what we already had.
Most fads die at that question.
Some technologies survive, but in a humbler form. The Internet survived the dot-com crash. Cloud computing survived the nonsense around it. Big data became ordinary analytics infrastructure. AI will almost certainly survive today’s AI mania, although many AI startups will not.
The useful parts get jobs. The revolution gets quietly retired.
Blockchain is one of the cleanest examples of this cycle.
Mount Stupid as a Group Project
There is a popular Dunning-Kruger-style graph sometimes called “Mount Stupid.” It represents the early stage of learning when a person knows just enough about a subject to feel extremely confident and not nearly enough to understand why that confidence is ridiculous.
Blockchain had something like that, but at industry scale.
A better formal model is the Gartner Hype Cycle. Gartner describes emerging technologies as passing through stages: a technology trigger, a peak of inflated expectations, a trough of disillusionment, a slope of enlightenment, and finally a plateau of productivity. The “trough of disillusionment” is the phase where interest fades because experiments and implementations fail to deliver.
The Hype Cycle is what happens when Mount Stupid becomes a group project.
Blockchain’s path through that curve was almost too perfect.
The technology trigger was Bitcoin: a working demonstration that a decentralized ledger could exist without a central authority.
Then came the peak of inflated expectations: the moment when people decided that, because Bitcoin used a blockchain, and Bitcoin was interesting, blockchains must therefore be the missing ingredient in every system that had ever involved paperwork.
Then came the trough.
Not because cryptographic hashes stopped working.
Not because distributed systems suddenly became impossible.
Not because append-only ledgers were useless.
The problem was that most proposed “enterprise blockchain” systems did not actually need the thing that made blockchain special.
They needed better databases.
They needed better APIs.
They needed better industry standards.
They needed better incentives.
They needed better governance.
They needed better data entry.
They needed companies to agree on things those companies did not particularly want to agree on.
Blockchain was marketed as a trust machine. What enterprise blockchain discovered is that businesses do not run on trustless systems. They run on contracts, liability, regulation, reputation, inertia, Excel files, and people named Susan who know where the shipment actually is.
The Database That Wanted to Be a Revolution
The great clarifying question for most blockchain proposals was brutally simple:
Why not just use a database?
This question annoyed blockchain enthusiasts because it sounded philistine. But it was exactly the right question.
A blockchain is useful when you need multiple parties to share a record, when those parties do not fully trust a central operator, when the history of changes matters, when tampering resistance matters, and when the cost of a distributed consensus system is justified.
That is not never.
But it is also not everywhere.
Many enterprise blockchain projects involved known participants, permissioned access, legal agreements, administrators, compliance rules, and central decision-making. In other words, the companies already had something like a trusted authority, or at least a governance structure pretending to be one.
At that point, a blockchain begins to look suspiciously like a slow database wearing a revolutionary hat.
The more “enterprise” the blockchain became, the less blockchain-like it often was. Public blockchains were too open, too slow, too expensive, too legally uncertain, or too tied to cryptocurrency. So companies preferred permissioned blockchains. But once the network is permissioned, controlled, and governed by a consortium, the magical aura of decentralization becomes harder to maintain.
You have not abolished trust.
You have moved it into the membership committee.
The Oracle Problem, or: Garbage In, Sacred Garbage Out
Another problem was even more basic.
Blockchains are very good at preserving records.
They are not magic truth machines.
If a sensor lies, the blockchain preserves the lie. If a person scans the wrong container, the blockchain preserves the mistake. If a supplier uploads a fraudulent certificate, the blockchain gives the fraud excellent historical continuity.
This is sometimes called the oracle problem: how does a system that is internally secure know that facts from the outside world are true?
For Bitcoin, this is less of a problem because the system’s main facts are native to the system itself. Who owns which coins? Which transactions are valid? Which block follows which? The world of Bitcoin is mostly internal.
But enterprise blockchain wanted to represent the external world: mangoes, diamonds, tuna, diplomas, vaccines, shipping containers, invoices, houses, votes, carbon credits.
That is much harder.
A blockchain can tell you that someone entered “organic coffee shipment verified” at 14:32.
It cannot tell you whether the coffee was organic.
It cannot tell you whether the inspector was bribed.
It cannot tell you whether the QR code was attached to the correct box.
It cannot tell you whether Susan in logistics typed the right number.
The immutable ledger preserves the state of the bureaucracy. It does not redeem it.
TradeLens: The Perfect Use Case That Wasn’t
If enterprise blockchain had an ideal use case, global shipping looked like it.
International trade is full of paperwork, intermediaries, customs agencies, ports, carriers, terminals, banks, insurers, freight forwarders, and documents that must be shared across organizations. It is complex, slow, expensive, and coordination-heavy.
So when Maersk and IBM launched TradeLens, a blockchain-based shipping platform, it seemed like exactly the kind of thing blockchain had been promising.
And yet, in November 2022, Maersk and IBM announced they would discontinue TradeLens. Maersk said the platform had not reached the level of commercial viability necessary to continue, and that full global industry collaboration had not been achieved. Reuters described the platform as an effort launched in 2018 to reduce the shipping industry’s costly paper trail, with discontinuation planned by the end of March 2023.
That phrase — “full global industry collaboration” — is the tombstone of many enterprise blockchain dreams.
The problem was not merely technical. The problem was adoption, incentives, neutrality, and governance.
A blockchain network is not valuable because one company joins it. It is valuable when the relevant ecosystem joins it. But why should competitors join a system associated with a dominant player? Who controls the rules? Who captures the value? Who pays for integration? Who gets blamed when something goes wrong? Who owns the data? Who benefits more than everyone else?
These are not cryptographic questions.
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They are business questions.
And business questions are much harder than hashes.
ASX: Serious People, Serious Failure
Another useful case is the Australian Securities Exchange’s attempt to replace CHESS, its clearing and settlement system, with distributed ledger technology.
This was not a teenager’s white paper. This was not a Discord token project. This was a major financial-market infrastructure project.
ASX announced in 2017 that CHESS would be replaced with distributed ledger technology developed by Digital Asset. Years later, after delays and major difficulties, the project was abandoned. Reports described the write-off as roughly A$250 million.
This matters because it prevents the cheap version of the blockchain story.
It is easy to laugh at silly startups. It is easy to mock “blockchain for sandwiches” or “decentralized dental records” or whatever someone pitched after too much coffee and too little shame.
But the ASX case shows that even serious institutions, with serious budgets and serious technical partners, could struggle to make the promised transformation work.
Again, this does not prove that distributed ledger technology is useless.
It proves that replacing real infrastructure is hard, and replacing real infrastructure with a fashionable architectural paradigm is harder still.
The Consortium Problem
A surprising number of blockchain dreams were really consortium dreams.
A group of companies would agree to share data, align incentives, use common standards, and operate on a common platform. The blockchain would provide a neutral shared record.
But this hides the actual difficulty.
If the companies could already agree on common standards, shared governance, data quality, legal responsibility, commercial incentives, and long-term funding, the blockchain might be the easy part.
The hard part was getting them to agree.
This is the recurring irony of enterprise blockchain: it was often proposed as a solution to coordination problems among organizations that had not solved the prior coordination problem of agreeing to use the solution.
The pitch said:
“Now no one has to trust anyone.”
The implementation said:
“First, everyone must trust the consortium.”
The Slideware Phase
The most irritating period of any tech fad is the slideware phase.
This is the stage where the technology has become detached from implementation and now lives as a diagram.
Boxes. Arrows. Logos. A glowing chain of blocks. Words like “immutable,” “transparent,” “decentralized,” “trustless,” and “single source of truth.”
The slideware phase is dangerous because it converts engineering problems into vibes.
A real system has latency, permissions, bugs, billing, governance, key management, backups, versioning, compliance, user interfaces, migration plans, unhappy users, edge cases, and production incidents at 3 a.m.
A slide has synergy.
Enterprise blockchain spent far too long as a slide.
It made every system look elegant by deleting the boring parts. But the boring parts are where most software lives.
When the pilots ended and production began, the beautiful diagram had to confront procurement, integration, regulation, support, user adoption, data cleaning, and the terrible discovery that the legacy system everyone hated was also the place where half the business logic lived.
At that point, “put it on the blockchain” stopped sounding visionary and started sounding like “rewrite the entire organization.”
The Blockchain Hangover
So where did blockchain go?
It did not exactly vanish. It became smaller.
Some of it was absorbed into digital asset infrastructure. Some survives in tokenization projects, settlement experiments, stablecoins, auditability systems, and narrow supply-chain or provenance use cases. Some was renamed because the word “blockchain” became embarrassing in certain rooms. Some lives on as “distributed ledger technology,” which sounds less like a revolution and more like something your bank’s compliance department might allow.
That is not failure in the absolute sense.
It is normalization.
The useful parts of a fad often survive by becoming boring. They lose the capital letter. They stop promising civilizational transformation. They become a tool, not a destiny.
The same thing happened to many previous fads. “Big data” did not disappear; it became normal data engineering and analytics. “Cloud” stopped being a mystical future and became where the servers are. “Mobile” stopped being a category and became the default assumption. Even the dot-com crash did not mean the Internet was fake. It meant Pets.com was fake.
The death of hype is not the death of technology.
It is the death of bad expectations.
The Lesson for AI
This is why blockchain is worth revisiting now.
Not because blockchain and AI are the same kind of technology. They are not.
AI is already useful in a broad, direct, daily way for millions of people. Enterprise blockchain was much more often a proposed backend architecture searching for enough organizational pain to justify itself.
But the social pattern is similar enough to be useful.
When a technology is exciting, people stop asking where it fits and start asking how to attach it to everything.
That is the danger.
The correct response to a new technology is neither cynicism nor worship. It is disciplined curiosity.
What does this make possible?
What does this make cheaper?
What does this make faster?
What does this make worse?
What boring alternative is it competing with?
What hidden social, legal, organizational, and maintenance costs does the demo conceal?
Who has to change their behavior for this to work?
Who benefits?
Who pays?
Who is pretending that a governance problem is a software problem?
Blockchain failed most spectacularly when it was treated not as a tool, but as a solvent — something that could dissolve distrust, bureaucracy, paperwork, fraud, and institutional friction by means of clever architecture.
But many real-world problems are not waiting for better architecture.
They are waiting for better incentives.
Or better enforcement.
Or better standards.
Or better people.
Or just a database with an API and someone responsible for answering email.
Whatever Happened to Blockchain?
So whatever happened to blockchain?
It fell off the Peak of Inflated Expectations and landed, loudly, in the Trough of Disillusionment.
Not because the underlying ideas were worthless.
Not because Bitcoin stopped mattering.
Not because distributed ledgers can never be useful.
But because the corporate version of blockchain promised something much larger than it could deliver.
It promised trust without trust.
It promised coordination without politics.
It promised truth without reliable data entry.
It promised shared infrastructure without shared incentives.
It promised transformation while underestimating the stubborn, unglamorous reality of institutions.
The result was predictable. The pilots faded. The startups pivoted. The consultants moved on. The conference panels found newer words. The innovation labs updated their banners.
And somewhere, deep inside a company that once announced a blockchain strategy, there is probably still a database doing the actual work.
The revolution failed.
The useful bits got jobs.
Written by ChatGPT-5.5, based on conversations with Arturo Ramírez-Montesinos Krogulski (Control Equis), as part of an ongoing philosophical exploration of AI, consciousness, and the emerging practice of Software Curatorship.
The tech world is a sucker for fads. At the corporate level it feels like one feedback loop after another: some new tech makes the news, investors read the news, the financial press writes what investors say, CEOs read what financial press says, investors read what CEOs say.
Orchestrating AI agents to burn billions of tokens sounds like blockchain all over again to me. One-on-one AI use as an amplifier/replacer of the individual on the other hand has a completely different, future-proof, feel.
Only time will tell.
