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🌐WHY A BITCOIN BAN IN THE EU IS LIKELY… AND STUPID🌐
Despite holding off to date, a Bitcoin ban by the EU could be on the horizon. But Bitcoin doesn’t ask for permission.
January 02, 2023
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Bitcoin is under attack. It is increasingly seen as a “dirty currency.” Elon Musk’s Tesla, Wikipedia, Greenpeace and other organizations have stopped accepting BTC for their products or as a means to donate money.

Musk, who is not only one of the richest but also one of the most controversial people on this planet, has said: “Cryptocurrency is a good idea on many levels, and we believe it has a promising future, but this cannot come at great cost to the environment.” Ouch.

And it’s not just Musk. Politicians have also taken aim at Bitcoin.

Before the European Commission’s Markets in Crypto-Asset Regulation (MiCA) regulation was passed, it caused quite a stir within the Bitcoin community, especially due to the left-wing factions of the EU Parliament that were opposed to proof of work (PoW) and the power consumption of the Bitcoin network. In the trilogue, a version of MiCA was finally passed that did not ban PoW or mining.

As became known in April 2022, some members of the European Parliament (MEPs) tried to push through a ban on bitcoin mining and one on BTC trading in the course of the draft law. Luckily, they failed.

However, the foundations for further steps have been laid. For example, the issuers of cryptocurrencies, which we know are mostly simply tech startups, will be obliged to deliver some kind of report on the energy consumption and the associated carbon footprint of the respective asset. Brokers and exchanges, in turn, must inform their customers about these exact figures when they purchase crypto assets.

The increasing aversion to Bitcoin also gained traction through an anti-Bitcoin Greenpeace USA campaign launched in March, which was financed by Ripple co-founder Chris Larsen, among others. Interestingly, Greenpeace accepted bitcoin donations between 2014 and 2021 until they were put on hold due to environmental concerns.

NEARLY HALF OF THE EU PARLIAMENT DOESN’T LIKE BITCOIN

As mentioned, a mining or trading ban for Bitcoin didn’t make it into the MiCA legislation. However, it is very unlikely that members of the EU parliament who tried to implement this in MiCA will give up — we can assume the contrary.

In March 2022, the economic and monetary affairs (ECON) committee in the EU parliament voted against a ban on PoW. Thirty-two members voted against it, 24 in favor. The topic seems to become more and more ideologically driven, as the Social Democrats, the Greens, and the left mostly wanted a PoW ban, whereas the Conservatives, the Liberals and right-wing factions tended to vote against it.

The final MiCA draft created by conservative MEP Stefan Berger included a compromise: Instead of a ban on PoW, they agreed on including a rating system for cryptocurrency to assess their environmental impacts (more on that later).

In an email conversation with Politico, the Spanish Green EU parliament member Ernest Urtasun explained:

“Creating an EU labeling system for crypto will not solve the problem as long as crypto-mining can continue outside the Union, also driven by EU demand
 The Commission should rather focus on developing minimum sustainability standards with a clear timeline to comply.”

And he added:

“Ethereum’s recent upgrade just showed that phasing out from environmentally harmful protocols is actually feasible, without causing any disruption to the network.”

THE ECB DOESN’T LIKE BITCOIN — AT ALL

While we see different opinions on Bitcoin in the European Parliament, the signals we’re getting from the European Central Bank (ECB) are very clear. The ECB is issuing warnings about cryptocurrencies on a regular basis, naming their “exorbitant carbon footprint” as “grounds for concern”.

Just recently, on November 30, 2022, the ECB published a blog post titled “Bitcoin’s Last Stand.” In it, ECB’s Market Infrastructure And Payments Director General Ulrich Bindseil and advisor JĂŒrgen Schaff argue that, “Bitcoin's conceptual design and technological shortcomings make it questionable as a means of payment.”

According to Bindseil and Schaff, Bitcoin transactions are “cumbersome, slow and expensive,” which they say explains why the world’s largest cryptocurrency — created to overcome the existing monetary and financial system — "has never been used to any significant extent for legal real-world transactions.” Bindseil and Schaff added that since Bitcoin is neither an effective payment system nor a form of investment, “it should be treated as neither in regulatory terms and thus should not be legitimized.”

While it may seem paradoxical to very vocally attack something that is on the “road to irrelevance,” it is not the first time that the ECB has attacked Bitcoin.

In July 2022, the ECB singled out Bitcoin in a research article and compared proof of work to fossil fuel cars while considering proof of stake as more akin to electric vehicles. Let’s ignore for a minute that this doesn’t make sense and look at what it wrote in detail:

“Public authorities should not stifle innovation, as it is a driver of economic growth. Although the benefit for society of bitcoin itself is doubtful, blockchain technology in principle may provide yet unknown benefits and technological applications. Hence, authorities could choose not to intervene with a view to supporting digital innovation. At the same time, it is difficult to see how authorities could opt to ban petrol cars over a transition period but turn a blind eye to bitcoin-type assets built on PoW technology, with country-sized energy consumption footprints and yearly carbon emissions that currently negate most euro area countries’ past and target GHG saving. This holds especially given that an alternative, less energy-intensive blockchain technology exists.”

In general, the ECB believes it’s highly unlikely that the European Union will not take action in terms of carbon emissions on PoW-based assets like bitcoin. The authors of the paper argue that in their view it’s likely that the EU will take similar steps on phasing out PoW as they are doing with fossil fuel cars. Especially since, according to them, an “alternative, less energy-intensive” technology like PoS exists.

“To continue with the car analogy, public authorities have the choice of incentivising the crypto version of the electric vehicle (PoS and its various blockchain consensus mechanisms) or to restrict or ban the crypto version of the fossil fuel car (PoW blockchain consensus mechanisms). So, while a hands-off approach by public authorities is possible, it is highly unlikely, and policy action by authorities (e.g. disclosure requirements, carbon tax on crypto transactions or holdings, or outright bans on mining) is probable. The price impact on the crypto-assets targeted by policy action is likely to be commensurate with the severity of the policy action and whether it is a global or regional measure.”

The vast majority of citizens are used to thinking of money as something other than what it really is, and the ECB is also to blame for this. Money is perceived as something that has value by itself, instead of something whose value comes from the interaction between the people who use it.

The euro is subject to both constant changes (regular inflation) and traumatic events (devaluations, forced exchange rates, etc.), but these are ignored or otherwise underestimated. People believe they own it, although they can only exchange it for other things.

For how many and for what things will 100 euros be exchanged in one year, five years or ten years? This is, in no way, up to us.

Its exchange function is constantly changing due to factors we cannot control. The interaction between those who use it is the main factor and, in turn, this interaction depends on economic and monetary policy rules that few people know about.

Bitcoin escapes these rules (and this is the reason why the ECB wants to ban it), it is just code that the ECB and the regulators are trying to make useless. Bitcoin also and above all expresses its value through features that are totally independent of a government’s power and, therefore, the ECBs.

WHAT WILL HAPPEN NEXT?

In 2025, we will see a rating system for cryptocurrencies according to their environmental impact within the European Union — think energy labels for fridges or TVs. You can already expect that bitcoin will get the worst classification. This step will essentially be positive for Ethereum and bad for Bitcoin.

It’s quite unlikely that such a label will scare off investors from buying bitcoin, especially since the Bitcoin community is saying that the Bitcoin network is not an obstacle but a solution for more green energy.

Therefore, the Bitcoin mining industry has the incentive to become greener: The fossil fuel analogy in the ECB paper makes no sense. The energy mix of a PoW network like Bitcoin can come entirely from renewable, green sources. Bitcoin can serve as a way to immediately monetize energy, as is already happening with flared gas that would be flared anyway. However, it’s questionable how fast and effective this effort will be to policymakers, especially since fossil energy companies like Exxon are now mining Bitcoin using flared gas.

The authors of the ECB paper are already implying that a higher bitcoin price equals more energy consumption, as more miners will participate. Destroying demand for bitcoin would hence be an effective solution to bring down the hash rate. At least in theory.

CONCLUSION

The academic and political consensus seems to point toward something like trying to retire the “old” PoW, and moving towards the “new” PoS standard. Particularly since Ethereum’s recent merge, many bystanders believe this could be a viable path for the Bitcoin network. We doubt that and plan to elaborate on that in a future post. As we’ve seen in different scenarios, banning Bitcoin is hard, if not impossible. The Nigerian government tried, failed and eventually gave up, for instance.

It will be quite a while until 2025, and with an energy crisis, increased focus on carbon emission as well as global uncertainty overall, the only thing we can do at this point is to expect the unexpected.

Even if the worst-case scenario happens, and we see a Bitcoin ban of some sort happen in the EU, we doubt that this will hold forever. Bitcoin does not ask for permission. Bitcoin is something that ontologically struggles to stay inside a fence. It is not an idea derived from anarchist positions, it is an argument derived from the inherent characteristics of the technology introduced by Satoshi Nakamoto. The regulators work in an authorizing logic and so it is clear that they struggle to intercept the Bitcoin phenomenon, which functions regardless of someone else’s permission.

This is a guest post by Guglielmo Cecero and Raphael Schoen. Opinions expressed are entirely their own and do not necessarily reflect those of BTC Inc or Bitcoin Magazine.

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You likely already scrolled past it once thinking it was just another weight drop, but Teutonic-II 110B Genesis isn't a finished model. It is a clean, randomly initialized sparse Mixture of Experts (MoE) checkpoint that the network is pretraining live from scratch, completely in public, on Bittensor Subnet 3. đŸŒđŸ”„

The Raw Architecture 📊

  • Total Scale: ~110B total parameters.

  • Active Routing: ~7.3B active parameters per token.

  • Incentive Engine: Permissionless updates, open datasets, and over 6,000 per day inTAO rewards paying the builders who drive loss down.

The Pay-Publish-Price Test đŸ§Ș

Most people look at "110B on Bittensor" and instantly compare it to Llama. That’s the wrong frame. You aren’t looking at an open model—you are looking at an open training market.

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Here is why this is massive:

‱ Nvidia builds the raw compute ⚙

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‱ Bittensor ($TAO) builds the open, permissionless marketplace for global machine intelligence 🌐

While crypto Twitter is busy chasing daily meme coin rotations and short-term leverage plays, the key architect of the AI boom just gave a nod to decentralized AI infrastructure.

💡$TAO isn't just another altcoin—it’s an incentive layer for open-source AI models. Most traders won't connect the dots until the rest of the market catches up. Don't sleep on what's being built here. 💎🚀

#Bittensor #TAO #Nvidia #Crypto #ArtificialIntelligence #JensenHuang

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While most headlines focus on AI-driven displacement, Groq Founder and CEO Jonathan Ross offers a fascinating, contrarian perspective. He argues that instead of mass unemployment, we are heading toward a massive labor shortage driven by three tectonic shifts:

1. Massive Deflationary Pressure: Efficiency gains from automated farming, robotics, and streamlined supply chains will drive down the cost of everyday essentials—from coffee to housing—meaning people will ultimately need less money to thrive. â˜•ïžđŸ 

2. The Great Economic Opt-Out: As living costs drop and productivity skyrockets, humans will choose to work fewer hours, fewer days a week, and retire much earlier because their lifestyles will be easier to support. ⏳🌮

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Chutes is gaining attention as a decentralized AI inference platform that claims to combine real usage, cryptographic verification, confidential computing, and open-source infrastructure into a working production system. The thesis is simple: instead of trusting Big Tech clouds with AI workloads, users get a distributed compute layer built around verification and privacy.

🔑 Key points

đŸ”č Chutes is live in production and reportedly scaled to more than 1,170 active GPU nodes, including large numbers of Nvidia H200s and Blackwell-class hardware.

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đŸ”č Chutes is using post-quantum cryptography, trusted execution environments, and Nvidia confidential ...

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A new clash is emerging between legacy finance and crypto legislation after JPMorgan CEO Jamie Dimon reportedly warned that the CLARITY Act could let crypto firms offer bank-like products without bank-level oversight. The dispute is quickly turning into a larger fight over regulation, competitiveness, and who controls the future architecture of digital finance in the United States.

🔑 Key points

đŸ”č Jamie Dimon reportedly called the CLARITY Act a threat to the financial system, arguing it could allow crypto firms to offer yield-like products while avoiding the capital, reserve, and oversight burdens traditional banks face.

đŸ”č Senator Cynthia Lummis pushed back publicly, framing the issue as a global strategic race and warning that if the U.S. does not set digital asset standards, other powers will.

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👉 Coinbase just launched an AI agent for Crypto Trading

Custom AI assistants that print money in your sleep? 🔜

The future of Crypto x AI is about to go crazy.

👉 Here’s what you need to know:

💠 'Based Agent' enables creation of custom AI agents
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💠 Integrates with Coinbase’s SDK, OpenAI, & Replit

👉 What this means for the future of Crypto:

1. Open Access: Democratized access to advanced trading
2. Automated Txns: Complex trades + streamlined on-chain activity
3. AI Dominance: Est ~80% of crypto 👉txns done by AI agents by 2025

🚹 I personally wouldn't bet against Brian Armstrong and Jesse Pollak.

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The seasoned sailor doesn’t try to dominate the ocean. He listens to it. He senses the change in pressure before the wave even breaks. He adjusts his trim by fractions of an inch. He knows when to catch the gust, when to alter his angle, and when to drop anchor and simply wait out the fog. A minimal touch on the tiller, executed with precision, accomplishes far more than desperate struggling against a gale.

Perhaps navigating existence demands the exact same touch.

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đŸ«€âšĄïž Think your brain is the most electrically active organ in your body? Think again. The human heart produces an electromagnetic signal magnitudes stronger than anything generated in your head. đŸ§ đŸ’„

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🚹 U.S. Treasury targets Iran-linked crypto network tied to more than $100 million in oil payments 🚹

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đŸ€–Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?đŸ€–
The race to build the future of robotics is no longer just about robots. It's about who controls the intelligence behind them.
 
Over the last three years, a small group of companies has emerged as the backbone of the AI revolution. Microsoft provides cloud infrastructure. NVIDIA supplies the chips. Google, OpenAI, Anthropic, Meta, and others develop the models. Together, they control much of the compute, data, and software stack powering modern AI.
 
Now that AI is moving into the physical world, many are asking a bigger question:
 
Will these same companies end up controlling robotics too?
 
It's a valid concern.
 
The latest generation of robots relies on enormous amounts of compute, simulation, training data, and foundation models. Many robotics startups today are built on infrastructure provided by large technology companies. NVIDIA's Omniverse is becoming a key simulation environment for robot training. Microsoft Azure is powering the training of robotics foundation models. Physical AI startups increasingly depend on hyperscale cloud infrastructure to train and deploy intelligent systems. Recent partnerships across the industry show just how central Big Tech has become to robotics development.
But while Big Tech is building the highways, another movement is trying to ensure it doesn't own every destination.
 
That movement is decentralized AI.
 
Why Decentralized AI Exists
 
The idea behind decentralized AI is simple. Instead of a handful of companies owning the models, compute infrastructure, data pipelines, and intelligence networks, these resources are distributed across thousands of participants.
 
This means anyone can contribute compute, contribute models, validate outputs and can participate.
The most visible example today is the decentralized AI network known as Bittensor (@bittensor). The network has evolved into a large ecosystem of specialized AI markets called subnets, where participants compete to provide useful machine intelligence and are rewarded based on performance. Rather than relying on a single company, intelligence is generated and validated by a distributed network of miners and validators.
 
Think of it as an attempt to build an open marketplace for AI instead of a world where intelligence is rented from a few centralized providers.
 
Why This Matters for Robotics
 
Robotics has a unique problem. Unlike chatbots, robots operate in the physical world. They need to perceive environments, make decisions, move safely and they need to learn continuously.
 
The challenge is that collecting and training on real-world robotic data is incredibly expensive. That's one reason large companies have such an advantage. They can afford the compute, simulation environments, and data infrastructure needed to train robotics models at scale.
 
This is where decentralized systems become interesting.
 
Instead of one company collecting all the data and training all the models, decentralized networks could allow thousands of contributors to participate in building robotic intelligence.
 
Imagine a future where:
  • Warehouse robots contribute operational data.
  • Delivery robots contribute navigation data.
  • Factory robots contribute manipulation data.
  • Developers contribute models.
  • Validators evaluate performance.
The resulting intelligence becomes a shared network rather than a proprietary asset.
 
That vision is beginning to emerge.
 
Bittensor's Move Toward Physical AI
 
While many people associate Bittensor (@bittensor) with language models and AI services, parts of the ecosystem are increasingly exploring embodied intelligence and robotics.
 
One example is Kinitro, a subnet focused on incentivizing the training and evaluation of embodied AI systems. The goal is to create competitive environments where developers build robotic intelligence and are rewarded based on performance.
 
The broader Bittensor ecosystem has also expanded into compute marketplaces, distributed inference systems, bandwidth infrastructure, and AI coordination layers that could eventually support robotics workloads. Several subnets now focus on decentralized compute, confidential inference, data transfer, and model training, critical components for future robotic systems.
 
In other words, the pieces are starting to appear.
 
Not a decentralized robot network yet.
 
But the infrastructure that could support one.
 
Beyond Bittensor: The Rise of Physical AI Networks
 
Bittensor isn't alone.
 
Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
 
New research published in 2026 introduced the concept of DAO-enabled decentralized physical AI, or DePAI. The idea combines robotics, decentralized infrastructure, AI models, governance systems, and human oversight into a single framework. Instead of centralized control, robots and physical infrastructure could be coordinated through transparent rules and distributed ownership models.
 
At the same time, developers are exploring decentralized operating systems for robots that allow machines to communicate directly with each other and with distributed compute resources. These architectures are designed to make robotic systems more resilient and less dependent on a single cloud provider.
 
The goal is not simply decentralization for its own sake.
 
The goal is resilience.
 
If one server fails, the system continues.
 
If one company disappears, the network survives.
 
If one participant leaves, innovation continues.
 
But Here's the Reality
 
Decentralized AI faces the same challenge every decentralized technology faces.
 
Big Tech has resources. A lot of resources.
 
Training advanced robotics models requires enormous compute budgets, sophisticated simulation environments, access to specialized hardware, and vast amounts of real-world data.
 
That's why many robotics startups still partner with major cloud providers and AI companies. It's often the fastest path to deployment.
 
And there are legitimate concerns about whether decentralized networks can maintain quality, reliability, and security at the scale required for industrial robotics. Even researchers studying decentralized AI systems have highlighted risks around concentration, incentives, governance, and network security.
 
The challenge isn't just decentralizing intelligence.
 
It's decentralizing intelligence while maintaining performance.
 
That's much harder.
 
The Most Likely Outcome
 
The future probably won't be fully centralized. And it probably won't be fully decentralized either. Instead, we're likely heading toward a hybrid model.
 
Large technology companies will continue providing chips, cloud infrastructure, simulation platforms, and foundational research.
 
At the same time, decentralized AI networks will emerge as alternative coordination layers where intelligence, data, and economic value can be shared more openly.
 
The companies building robots may use NVIDIA hardware.
 
Train on Azure.
 
Run foundation models from OpenAI.
 
But they may also participate in decentralized data networks, decentralized compute markets, and decentralized intelligence protocols.
 
The future of robotics could end up looking less like a monopoly and more like an ecosystem.
 
The Bigger Question
 
The real question isn't whether decentralized AI can eliminate Big Tech.
 
It can't.
 
At least not anytime soon.
 
The real question is whether decentralized AI can prevent a future where a handful of companies control every robot, every model, every dataset, and every decision made by the machines operating around us.
 
As robots become workers, assistants, delivery drivers, factory operators, and even economic agents, that question becomes increasingly important.
 
Because the battle for the future of robotics is no longer about hardware.
 
It's about who owns the intelligence.
 
And that battle is just getting started.
 
 

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Navigating the world of blockchain 🧭
Navigating the world of blockchain can feel like learning a completely foreign language. Between technical jargon and fast-moving Web3 terminology, getting started can be overwhelming.

Whether you are exploring digital assets, building on-chain, or simply trying to understand decentralized technology, here is your foundational glossary of essential blockchain terms every beginner should know.

đŸ›ïž 1. Core Architecture: The Base Layer

  • Blockchain: A distributed, immutable digital ledger that records transactions across a peer-to-peer network of computers. Once data is written to a block and added to the chain, it cannot be altered without altering all subsequent blocks.
  • Block: A collection of verified transactions grouped together. Once filled, the block is cryptographically linked to the previous one, forming a chronological "chain."
  • Node: An individual computer connected to a blockchain network that helps validate transactions, store ledger data, and maintain network consensus.
  • Consensus Mechanism: The set of rules and algorithms that network nodes use to agree on the validity of transactions.

    • Proof of Work (PoW): Requires miners to solve complex mathematical puzzles using computational power (e.g., Bitcoin).
    • Proof of Stake (PoS): Requires validators to lock up ("stake") native tokens as collateral to participate in block validation (e.g., Ethereum).

🔑 2. Ownership & Security: Wallets and Keys

  • Public Key (Address): An alphanumeric string that acts like your bank account number or email address. It is safe to share publicly so others can send you digital assets.
  • Private Key: A secret cryptographic passphrase or key that grants full access and control over your wallet assets. Never share your private key or seed phrase with anyone.
  • Seed Phrase (Recovery Phrase): A sequence of 12 to 24 random words generated when you set up a wallet. It acts as the master backup key to restore your wallet and access your funds on any device.
  • Hot Wallet vs. Cold Wallet:

    • Hot Wallet: A software-based crypto wallet connected to the internet (e.g., browser extensions, mobile apps), making it convenient for frequent transactions but higher risk.
    • Cold Wallet: An offline hardware device (e.g., Ledger, Coldcard) designed to isolate private keys from internet-connected threats.

⚙ 3. Execution & Functionality: Smart Contracts and Apps

  • Smart Contract: Self-executing code stored on a blockchain that automatically enforces agreement terms once predetermined conditions are met—eliminating the need for intermediaries.
  • dApp (Decentralized Application): Applications built on top of a blockchain network that run via smart contracts rather than centralized cloud servers.
  • Gas Fees: Network transaction fees paid to validators or miners to cover the computational energy required to process actions on a blockchain.
  • Layer 1 vs. Layer 2:

    • Layer 1 (L1): The underlying primary blockchain network (e.g., Bitcoin, Ethereum, Solana) that handles base security and finality.
    • Layer 2 (L2): Secondary frameworks or companion networks built on top of an L1 to increase transaction speeds and lower gas fees (e.g., Arbitrum, Optimism, Base).

💰 4. Financial & Market Concepts

  • Tokenomics: The economic design, supply dynamics, utility, and distribution model of a cryptocurrency or token project.
  • DeFi (Decentralized Finance): Financial services—such as lending, borrowing, trading, and earning interest—built on smart contracts without traditional banks or financial intermediaries.
  • Liquidity: The ease with which an asset can be bought or sold in a market without significantly impacting its price.
  • DYOR (Do Your Own Research): A foundational golden rule in the Web3 space reminding users to independently verify technical code, whitepapers, and team backgrounds before making any capital commitments.

💡 Quick Cheat Sheet

"Not your keys, not your coins."

If you do not hold the private keys or seed phrase to your digital wallet, you do not truly own the assets inside it—a centralized entity or exchange does. Always prioritize security first as you explore the space.

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AI Is Coming for Your Job Title

Artificial intelligence may or may not take your job, but it has already broken into the human resources department and vandalized the org chart.

The evidence is all over LinkedIn, where perfectly serviceable occupations now arrive wearing titles such as “forward-deployed and agentic AI architect.” That person may be building sophisticated software. They may also be helping a chatbot remember what happened three prompts ago. Either way, somebody approved the business cards.

The expanding AI lexicon offers a useful counterpoint to the darker debate about technology and employment. Most discussion centers on how many jobs AI will eliminate. Hiring data presents a more complicated picture that includes a weak overall labor market containing a small but rapidly growing neighborhood of AI-related work.

Indeed Hiring Lab found that the number of postings on Indeed mentioning AI surged 134% from its February 2020 level by the end of 2025, even as total postings stood only 6% above that benchmark. AI appeared in a record 4.2% of Indeed postings in December.

AI, in other words, is not merely changing work. It is adding syllables to it.

The Titles Employers Actually Want

The undisputed champion is AI engineer, which ranked No. 1 on LinkedIn’s 2026 Jobs on the Rise list. The ranking, based on growth during the previous three years, also highlighted AI consultants and strategists, AI and machine-learning researchers and data annotators.

The title is popular partly because it is wonderfully accommodating. An AI engineer might build applications around large language models, connect corporate data to an AI system, improve model performance or spend Thursday afternoon persuading a customer service bot not to offer refunds for products the company doesn’t sell.

Indeed’s data showed the terminology spreading beyond Silicon Valley. Nearly 45% of data and analytics postings contained an AI-related term at the end of 2025, along with roughly 15% of marketing postings and 9% of human resources listings. A more recent Indeed analysis reported by Business Insider found that the number of frequently advertised job titles explicitly referencing AI rose from 264 in 2022 to 822 in the first quarter of 2026. Nearly two-thirds were outside traditional technology fields.

That produces titles such as AI marketing manager, AI learning specialist, responsible AI counsel and AI transformation lead. These are not always new occupations. Frequently, they are familiar jobs that have discovered a highly effective résumé keyword.

LinkedIn data cited by the World Economic Forum estimated that AI investment has supported 1.3 million positions, including AI engineers, data annotators and forward-deployed engineers, plus more than 600,000 AI-enabled data center jobs. The server racks, unlike the chatbots, still need electricians.

The Jobs With the Science-Fiction Salaries

At the upper end, AI has created a compensation market that resembles professional sports, except the competitors wear hoodies and discuss inference latency.

A Syracuse University review put chief AI officer compensation between $200,000 and more than $500,000, while specialized roles can exceed $400,000 after bonuses and equity. Frontier research engineers, AI infrastructure specialists and engineers who can train or deploy advanced models command some of the largest packages.

Then there is the forward-deployed engineer, an old Palantir title that the AI boom has placed on a rocket sled. These engineers embed with customers, translating an executive’s desire to “do something with AI” into software that works. The Next Web reported that Indeed postings for the role were about 19 times higher in January than a year earlier.

A CTO guide from the blog Signal Through the Noise placed forward-deployed engineer compensation between $238,000 and $700,000, research-engineering packages as high as $1.4 million and chief AI officer compensation above $1 million in some cases. It also made a less flattering observation: Many lavishly differentiated titles describe the same three basic functions. People build AI products, train models or keep the infrastructure from catching fire.

The Department of Unnecessary Titles

AI has created some genuinely new work. Evals engineers design tests to determine whether models perform reliably. AI red teamers try to make systems fail before customers do. Model behavior engineers study why an AI system responds as it does. AI governance leaders manage risks involving data, bias, security and regulation.

Other titles seem to have escaped from a brainstorming retreat.

There is the Claude Evangelist, whose mission apparently combines product education with the traditional duties of an apostle. There are vibe coders, who build software by describing what they want and accepting AI-generated code with varying degrees of supervision. “Vibe engineer” is the more respectable version, roughly equivalent to putting on a blazer before asking the machine to fix the login page.

“Context engineer” is a real discipline involving the data, instructions, memory and tools supplied to AI models. “Prompt engineer,” once advertised as a possible six-figure profession for gifted chatbot whisperers, is increasingly treated as one skill inside a broader AI role.

The CTO guide also identified “builder,” “AI-native developer,” “RAG engineer,” “agentic AI engineer” and “principal agentic GenAI forward-deployed context architect,” the last of which appears to require both technical proficiency and exceptional lung capacity.

Has AI created entirely new jobs? Absolutely. Some occupations, including AI safety, evaluation and model governance, exist because modern generative systems introduced new technical and business problems. However, many job titles are old jobs with fresh vocabulary, higher salary bands and a sudden aversion to the words “software developer.”

That may be the safest prediction about AI and employment. The machines will automate some tasks, generate others and force companies to rethink the division of labor. Before any of that is settled, however, corporate America will form a steering committee, appoint a chief agentic transformation evangelist and schedule a meeting to determine what that person does.

Source

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