György Balázsi

Digital Strategist | Content marketer | Daml smart contract dev | Blockchain architect | Functional Programming specialist

[Khairallah AL-Awady @eng_khairallah1]

https://t.co/naBnj0ITi1

[Aakash Gupta @aakashgupta]

Anthropic has 454 open roles. The company is hiring software engineers at $320K-$405K. Their CEO, Dario, said three months ago that coding is "going away first, then all of software engineering."

The paradox resolves instantly.

Dario's engineers told him they don't write code anymore. They let Claude write it. They edit. They review. They architect. They didn't lose their jobs. They got faster. Anthropic grew from a small research lab to 1,500 employees in four years, adding engineers the entire time.

This has played out five times in computing history. Compilers replaced assembly. Frameworks replaced boilerplate. Cloud replaced server management. Every prediction was the same: most programmers won't be needed. Every result was the same: the number of engineers grew.

The global software engineer pool went from roughly 5 million in 2010 to 28.7 million today. BLS projects 17% growth in US software developer roles through 2033, adding 304,000 positions. The pool is projected to hit 45 million by 2030.

When building software gets cheaper, more problems become worth solving with software. A startup that needed 10 engineers now needs 3. But 50 companies that couldn't afford to build at all now can. The denominator shrinks. The numerator explodes.

Meta's engineering headcount is up 19% from January 2022. Google's is up 16%. Apple, 13%. These companies adopted AI coding tools years ago. They're using Copilot and Claude Code daily. They're hiring more engineers than before those tools existed.

Every generation of "coding is dead" content creates two cohorts: engineers who freeze up, and engineers who build 10x more with the new tools. The second group has won every single time.

[Canton Network @CantonNetwork]

The first Canton Coin ↔️ CBTC trade is happening today.

The live trade on CantonSwap marks another step in building real liquidity on-chain. Watch live 👇

[Teagan @0xteagan]

Little sketch today 🪶

Exercise to show the difference between complete mirroring with no off-chain reconciliation needed for institutions between Canton, and the custody + off-chain reconciliation model mostly seen on Ethereum 🧵

[Canton Network @CantonNetwork]

Blockchain has proven that it can deliver instant trading and settlement.

But the moment crypto meets TradFi, that efficiency breaks down: cut-off times replace real-time processing, batch cycles interrupt continuous flow, T+1 settlement delays trap capital overnight.

Canton Network changes that.

Institutions can now move collateral, automate margin, and finance trades 24/7 - with:

→ Instantly convertible stablecoins
→ High-utility tokenized collateral
→ Privacy fit for institutions

... all on infrastructure built for regulated finance.

Find out more in this blog by Georg Schneider ⤵️
https://t.co/bTaUBV1X5a

[Shaul Kfir @ShaulKfir]

L1 transparency is a bug, not a feature

[Canton Network @CantonNetwork]

CBTC is now live for early adopters on Canton Network!

@BitSafe_Finance

https://t.co/5q9IfPT7h8

[Canton Network @CantonNetwork]

Great analysis from ecosystem participant @Kiln_finance on Canton Network's growth 🚀

Their key finds:
• 2M+ daily transfers (20x growth since March)
• Transfer volume now outpaces most other permissioned chains
• Projected 5M daily transfers by Q4 2025 & $10T settled in tokenized assets by 2026

"Canton is positioned to become the default backend for regulated finance" - @Kiln_finance

[György Balázsi @winnfield]

https://t.co/tdaPon479u via @NYTimes

[Chris Matturri @cnmtennis16]

Excited to ship this for the Canton community! Feel free to give us any feedback & looking forward to rolling out more features very soon

@wesarn_real @YuvalRooz @njess

[Tim Denning @Tim_Denning]

I'm 38.

When I was 28 I worshipped politicians, followed the rules, went woke & believed in universal basic income.

Then I later discovered Isaac Asimov, and he transformed my life forever.

12 lessons from America's most outspoken & unknown writer:

[Canton Network @CantonNetwork]

This is how real RWA infrastructure succeeds.

See what's happening on Canton in real-time⤵️
https://t.co/1XwTviTAUl

[Shaul Kfir @ShaulKfir]

"But often to have true privacy you need it baked into every architecture decision of the L1, which often breaks existing L1s."

Amen.

[Leonardo Rizzo @LnrdRizzo]

How we "guessed" the Pope using network science: inside the cardinal network. A study by me, Beppe Soda and Alessandro Iorio. Article: https://t.co/xQ0fTmpVxb @Unibocconi

[Yuval Rooz @YuvalRooz]

Imagine a stablecoin issuer that uses ZKPs to issue coins with “privacy”. Now imagine a hacker find vulnerability like below. That’s literally the definition of a “money tree”. The integrity of said stablecoin ledger is forever damaged. This is a ticking time bomb behind the hype. Don’t fall to the trap.

[György Balázsi @winnfield]

@karpathy Leptos full stack framework in Rust

[DFNS @dfnsHQ]

Privacy is the hottest trend in blockchain finance today ♨️

Banks, FMIs, and fintechs are very interested, but when asked why they haven’t adopted blockchains yet, the answer is always the same: “We can’t have our money movements made public.”

Finance is a hyper-regulated industry, built on systems that ensure confidentiality, governance, approvals, and audit trails. Institutions need predictable execution, full control, and privacy-preserving smart contracts that support compliance and confidentiality at scale.

Unfortunately, public blockchains fall short for many real-world use cases.

That’s where the @CantonNetwork comes in.

It’s gaining strong momentum with institutions like Goldman Sachs, Société Générale, Circle, Gemini, Broadridge, DRW, and more.

✅ Deterministic finality with DAML smart contracts
✅ Private, dedicated networks for internal fund transfers (think: Onyx-as-a-service)
✅ A shared public layer for cross-institution settlement (think: public blockchain compatibility)

Yesterday marked the final day of the @blockworksDAS in New York. @dfnsHQ CEO @clarisse_hagege joined @digitalasset COO @ShaulKfir on stage to talk about how fintechs and banks are using crypto rails, and why technologies like Dfns and Canton help them adopt blockchain without disrupting their existing systems or compliance processes.

Catch the replay of our panel discussion 👇
https://t.co/u4Xcjy48BO

[Digital Asset @digitalasset]

Most blockchain tokens are speculative, but Canton Coin is different. It’s designed to reward real network utility, not hype.

So, what is @CantonNetwork?
It’s a decentralized infrastructure connecting real-world assets to on-chain finance with privacy and control built in which is a game-changer for institutions and innovators.

Key Features of Canton Coin:

✅ Fair launch with no pre-mine or pre-sale
✅ Rewards participants for contributing value
✅ Self-regulating burn-and-mint mechanism for price stability
✅ Opportunities for Super Validators, Validators, and Application Providers

If you're looking for blockchain with real-world use cases, Canton Network is where you should be.

Learn more and get involved now:
https://t.co/nrcXPPm4B6

[Yuval Rooz @YuvalRooz]

I’ve said many times, collateral on chain is probably one of the most important use cases. Not only it will bring billions of dollars in efficiency to tradfi, it can bring a lot of risk reduction and scale to crypto markets. This is super exciting.

[Andrew Ng @AndrewYNg]

At the Artificial Intelligence Action Summit in Paris this week, U.S. Vice President J.D. Vance said, “I’m not here to talk about AI safety.... I’m here to talk about AI opportunity.” I’m thrilled to see the U.S. government focus on opportunities in AI. Further, while it is important to use AI responsibly and try to stamp out harmful applications, I feel “AI safety” is not the right terminology for addressing this important problem. Language shapes thought, so using the right words is important. I’d rather talk about “responsible AI” than “AI safety.” Let me explain.

First, there are clearly harmful applications of AI, such as non-consensual deepfake porn (which creates sexually explicit images of real people without their consent), the use of AI in misinformation, potentially unsafe medical diagnoses, addictive applications, and so on. We definitely want to stamp these out! There are many ways to apply AI in harmful or irresponsible ways, and we should discourage and prevent such uses.

However, the concept of “AI safety” tries to make AI — as a technology — safe, rather than making safe applications of it. Consider the similar, obviously flawed notion of “laptop safety.” There are great ways to use a laptop and many irresponsible ways, but I don’t consider laptops to be intrinsically either safe or unsafe. It is the application, or usage, that determines if a laptop is safe. Similarly, AI, a general-purpose technology with numerous applications, is neither safe nor unsafe. How someone chooses to use it determines whether it is harmful or beneficial.

Now, safety isn’t always a function only of how something is used. An unsafe airplane is one that, even in the hands of an attentive and skilled pilot, has a large chance of mishap. So we definitely should strive to build safe airplanes (and make sure they are operated responsibly)! The risk factors are associated with the construction of the aircraft rather than merely its application. Similarly, we want safe automobiles, blenders, dialysis machines, food, buildings, power plants, and much more.

“AI safety” presupposes that AI, the underlying technology, can be unsafe. I find it more useful to think about how applications of AI can be unsafe.

Further, the term “responsible AI” emphasizes that it is our responsibility to avoid building applications that are unsafe or harmful and to discourage people from using even beneficial products in harmful ways.

If we shift the terminology for AI risks from “AI safety” to “responsible AI,” we can have more thoughtful conversations about what to do and what not to do.

I believe the 2023 Bletchley AI Safety Summit slowed down European AI development — without making anyone safer — by wasting time considering science-fiction AI fears rather than focusing on opportunities. Last month, at Davos, business and policy leaders also had strong concerns about whether Europe can dig itself out of the current regulatory morass and focus on building with AI. I am hopeful that the Paris meeting, unlike the one at Bletchley, will result in acceleration rather than deceleration.

In a world where AI is becoming pervasive, if we can shift the conversation away from “AI safety” toward responsible [use of] AI, we will speed up AI’s benefits and do a better job of addressing actual problems. That will actually make people safer.

[Original text: https://t.co/uvjfNwXq4c ]