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Bring the Ethos to Corporate Etherians
Original Article Title: "Ethereum Developers Bringing Their Talents to the Private Sector"
Original Article Author: Eric, Foresight News
On the evening of the 19th (Beijing time), Bankless co-founder David Hoffman posted on X to "commemorate" Ethereum Foundation's longest-serving researcher, Dankrad Feist, who chose to leave Ethereum and join the stablecoin L1 Tempo.
David Hoffman believes that the issue of for-profit companies absorbing talent nurtured by the Ethereum open-source community is significant and states that these companies will not necessarily bring greater benefits to Ethereum as they claim. David Hoffman bluntly expressed, "In my view, the significance of Tempo is to intercept the tens of trillions of dollars expected to flow into it over the next decade and put it on their private blockchain. Of course, this will grow the pie, but Tempo still intends to take as big a slice of that pie as possible." He believes that Tempo will be restricted by compliance issues regardless and that even issuing tokens cannot solve this. Although Tempo and Ethereum will both bring changes to the world, only Ethereum is best suited to be a trusted, neutral global settlement layer, with no shareholders and not bound by laws.
The "grass is greener on the other side" sentiment towards Ethereum has been evident since this cycle, as Ethereum's price performance lagged behind Bitcoin. Over time, it has become apparent that the departure of talented individuals from the Ethereum community seems to be an irreversible trend. When dreams clash with interests, many people ultimately choose the latter, which has long been a concern in the industry...
Dankrad Feist is Not the First, Nor Will He Be the Last
On the 17th of this month, Dankrad Feist announced on X that he would join Tempo and continue to serve as a research advisor for Ethereum Foundation's protocol cluster's three strategic initiatives (L1 scaling, Blob extension, and user experience improvement). Dankrad Feist stated, "Ethereum has a unique set of strong values and technical choices that underpin it. Tempo will be a great complement, built on similar technology and values while able to break boundaries in scale and speed. I believe this will greatly benefit Ethereum. Tempo's open-source tech can easily reintegrate back into Ethereum, benefiting the entire ecosystem."
According to LinkedIn, Dankrad Feist officially became an Ethereum researcher in 2019, focusing on researching Ethereum mainnet's sharding technology for scalability. The current core part of Ethereum's scalability roadmap, Danksharding, is named after him. Danksharding is seen as a key technological path for Ethereum to achieve high throughput and low-cost transactions, widely regarded by the community as a crucial upgrade direction post "Ethereum 2.0."
Dankrad Feist drove the precursor version of Danksharding, Proto-Danksharding (EIP-4844), which introduced the blob transaction type. This EIP provided Rollup with a cheaper and more efficient data availability layer, significantly reducing the data publishing costs of Rollup.
Furthermore, he engaged in a public dispute with Geth lead developer Péter Szilágyi on the MEV issue, eventually prompting Vitalik to intervene and push the community to prioritize MEV mitigation mechanisms like PBS (Proposer-Builder Separation).
Tempo researcher Mallesh Pai introduced new members joining Tempo in September, including Liam Horne, former CEO of OP Labs and co-founder of ETHGlobal.
Prior to Dankrad Feist, another figure that surprised the industry was Danny Ryan, co-founder of Etherealize, which secured a $40 million funding. As a former core member of the Ethereum Foundation known as the "Ethereum 2.0 Lead," he announced an indefinite departure in September 2024 and joined Etherealize just six months later. However, given Etherealize's similarity to ConsenSys founded by Ethereum co-founder Joseph Lubin, who left 11 years ago due to commercialization disputes, Danny Ryan received wide understanding.
What really concerns David Hoffman are companies like Tempo and Paradigm. Renowned Ethereum developer Federico Carrone expressed a similar view, retweeting David Hoffman's tweet about Dankrad Feist joining Tempo and stating that he has been warning for the past two years that Paradigm's influence within Ethereum could pose a tail risk to the entire ecosystem.
Federico Carrone wrote that the sole objective of a venture capital fund is to maximize returns for LPs, and Ethereum should not form a deep technical dependency on a venture capitalist playing with very high strategic skill. After the FTX scandal, Paradigm almost entirely removed all cryptocurrency-related brand exposure, making a high-profile shift to AI. Carrone believes this is enough to prove his point.
Following Trump's return to the White House, Paradigm re-entered the Web3 space, heavily recruiting top community researchers and funding key Ethereum open-source libraries, as well as supporting Stripe's launch of Tempo. Carrone believes that while Paradigm claims everything they do is beneficial for Ethereum - more funding, more tools, more testnets, new ideas that can all feed back into Ethereum - these are indeed potential benefits. However, when a company has too much visibility and influence over an open-source project, priorities shift from the community's long-term vision to corporate interests.
The Accumulation of Ethereum's Technical Debt
The mere loss of talent in the Ethereum open-source community may not be a cause for widespread concern, but if talent loss is accompanied by the accumulation of technical debt, then there is cause for high alert.
A week ago, a community user posted a screenshot on X and stated that the top contributors to the Solidity language have almost ceased their development efforts. Only Cameel continues to raise new issues and drive technical progress, but it appears to be in a maintenance mode. They believe the community needs to allocate more resources to support this programming language.
Some users in the comments questioned why effort should be spent on continuing to improve upgrade Solidity rather than just maintaining it to ensure stability and security. The user who posted explained that even changing the Solidity compiler would not affect any already deployed contracts but could enhance security, improve development experience, or support the use of new contracts. As shown in the image above, the level of development activity has sharply declined since the beginning of the last hype-driven bull market.
Federico Carrone also expressed his concerns, stating that what worries him the most is that many core tools and libraries built around Solidity may not receive long-term maintenance at all. Even the latest Solidity compiler is currently supported by very few developers. Additionally, companies related to L2 and ZK technologies are downsizing, making it possible that the iteration of cutting-edge technology may rely on just a few companies. As the Gas Limit increases, many execution clients have not made substantial performance improvements, and judging from the libraries, the development teams of these clients seem to have fallen behind.
Federico Carrone stated, "Ethereum's technical debt continues to accumulate, not only because the protocol itself must keep evolving, but also because many dependent libraries and peripheral repositories are now stagnant. The entire ecosystem continues to expand, guarding assets worth billions of dollars, while part of its foundation is quietly eroding."
The Open Source Community Cannot Solely Rely on "Love-Powered" Contributions
For an open-source community like Ethereum that carries a significant amount of tangible value in the form of programmable money, balancing "love-powered" contributions with economic incentives is a problem with no prior cases to reference. This should have been a highly concerning issue for the Ethereum Foundation, but it seems to have been overlooked.
Péter Szilágyi, who joined the Ethereum Foundation in 2015 and was responsible for Geth development and maintenance, explicitly outlined three of the most disappointing issues in a letter to the Ethereum Foundation leadership a year and a half ago: being portrayed externally as a leader but marginalized internally, severe income misalignment with Ethereum's market cap growth, and an excessive influence of Vitalik and a small group around him on the Ethereum ecosystem.
By the end of 2024, Péter Szilágyi discovered the Ethereum Foundation secretly incubating an independent Geth fork team, was subsequently fired due to disputes with the Ethereum Foundation, and was repeatedly denied rehiring. Subsequently, the Ethereum Foundation even proposed to pay Péter Szilágyi $5 million for Geth to become independent of the foundation, a proposal that was rejected. Currently, Péter Szilágyi still maintains the Geth codebase as an independent contributor.
Rumors of internal corruption within the Ethereum Foundation have been widespread, but this is actually a problem that should have been anticipated from the moment the Ethereum Foundation was established. The saying goes, "Where there are people, there is a rivers-and-lakes community," indicating that we cannot eliminate human greed. However, we cannot allow Ethereum to gradually lose its most core value due to commercialization.
Ethereum has a market cap of tens of billions of dollars, has facilitated the transfer of trillions of dollars' worth of value on-chain over the years, and is built on the foundation of a professional technical team, with a core ethos of permissionless open source, and through the commercialization brought by a large number of enterprises. However, such a vast system requires a significant amount of personnel to maintain, and as we have seen, these individuals are leaving due to disappointment or choosing to join other projects for economic gain.
The Ethereum Foundation underwent substantial reforms this year, but it does not seem to have produced remarkable results yet. Ethereum still can be described as the world's computer, with the potential in commercial applications still being continuously explored by brilliant teams. However, as the foundation of all this, Ethereum cannot continue to disappoint those who still persist for their ideals.
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link
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