Edward Yavno

Husband, father, hands-on technology leader & software engineer in #FinTech. Occasional fitness and Jiu Jitsu.

[Edward Yavno @edyavno]

@aaronburnett Using in my Verizon bill now looks like I have some savings and some missing trade-in credit.
I want to try it in my utility bills too!

[Sayer Ji @sayerjigmi]

🚨1/The bill Bernie Sanders introduced was drafted in London.🇬🇧

Its drafter, ControlAI, admitted it to TIME. Its funder — sole publicly named — is Jaan Tallinn, who led Anthropic’s Series A and sits on Anthropic’s board as an observer.

Neither Sanders nor the UK sponsor disclosed it.
🧵👇

[Senator Cynthia Lummis @SenLummis]

This afternoon, Senate Democrats proved they were never truly serious about protecting consumers and preserving American leadership. I sat at the table with Senate Democrats working in good faith to get this done while they played games.

For over a year, they presented demands and the second we met them, they made new demands and moved the goal posts. Today they voted against real limitations on politicians’ personal crypto investments. They voted against protecting American consumers from the scammers and fraudsters this bill would have shut down. They voted against American leadership, and handed China and every one of our foreign competitors exactly what they wanted. Democrats chose politics over the American people—again. That’s not leadership on their part, that’s surrender to their radical, socialist base.

The once-proud Democratic party is anti-consumer and pro-illicit finance, anti-ethics, anti-free enterprise, anti-worker, anti-livable wage jobs, and pro-socialism. The Democrats are now anti-American. Sad!

[Hunter Ash @ArtemisConsort]

METR is the EA doomer AI safety NGO that Dario wants to install as political commissars with employee-level access in every frontier lab. So let’s meet them: 🧵

[Marc Andreessen 🇺🇸 @pmarca]

What Is To Be Done?

I propose a simple plan:

Big AI companies should be allowed to build AI as fast and aggressively as they can – but not allowed to achieve regulatory capture, not allowed to establish a government-protect cartel that is insulated from market competition due to incorrect claims of AI risk. This will maximize the technological and societal payoff from the amazing capabilities of these companies, which are jewels of modern capitalism.

Startup AI companies should be allowed to build AI as fast and aggressively as they can. They should neither confront government-granted protection of big companies, nor should they receive government assistance. They should simply be allowed to compete. If and as startups don’t succeed, their presence in the market will also continuously motivate big companies to be their best – our economies and societies win either way.

Open source AI should be allowed to freely proliferate and compete with both big AI companies and startups. There should be no regulatory barriers to open source whatsoever. Even when open source does not beat companies, its widespread availability is a boon to students all over the world who want to learn how to build and use AI to become part of the technological future, and will ensure that AI is available to everyone who can benefit from it no matter who they are or how much money they have.

To offset the risk of bad people doing bad things with AI, governments working in partnership with the private sector should vigorously engage in each area of potential risk to use AI to maximize society’s defensive capabilities. This shouldn’t be limited to AI-enabled risks but also more general problems such as malnutrition, disease, and climate. AI can be an incredibly powerful tool for solving problems, and we should embrace it as such.

To prevent the risk of China achieving global AI dominance, we should use the full power of our private sector, our scientific establishment, and our governments in concert to drive American and Western AI to absolute global dominance, including ultimately inside China itself. We win, they lose.

And that is how we use AI to save the world.

It’s time to build.

[David Sacks @DavidSacks]

Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead.

You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence. You’ve also claimed the lead is widening because of recursive self-improvement.

I don’t see what you see in the lab. If the unreleased models are scary enough that you think you should slow down, I support your decision to be responsible.

But stop pretending you need anyone else’s permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic’s investors and staff. Stop pretending you need those same evaluators to police competitors who aren’t even at the frontier.

Most of all, stop pretending the motivation to slow down is purely altruistic. You face massive product-liability exposure if your products enable a truly damaging cyberattack. The market already punishes models that behave in unpredictable or unauthorized ways. After the Hugging Face episode, it is simply good business for OpenAI and Anthropic to trade some raw power for reliability and predictability. Call it alignment if you want. It is also just giving customers what they want.

Pacing the frontier would also create breathing room for a more intelligent conversation about regulation than Bernie Sanders’ “shut it all down.” China is very unlikely to join a global agreement, as you know, and that has to be taken into account as well.

So go ahead and pace the frontier. You are the ones setting it. The easiest way not to build superintelligence is for you to agree not to build it. Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system. So just do it.

If you do, you’ll buy goodwill for the next conversation. If you don’t, we’ll know this was just another bid for regulatory capture — or an election-season psyop.

[Parker Thayer @ParkerThayer]

This post looks like the start of a VERY sophisticated and well-funded PR operation to get support for Democrats to regulate AI into oblivion. Let me show you how it works:
1.) This guy, with minimal followers and no previous account activity, goes to the Wall Street Journal which publishes an exclusive with quotes from him on his resignation 18 minutes BEFORE this post goes up. Planning was clearly done in advance.

2.) Within hours, it has tens of thousands of reposts and the account has 100k+ followers. The post is punchy, quotable, it almost seems professionally written. The first three accounts to quote tweet it all do so within 15 minutes of the initial posting. Remember, this account had basically zero engagement beforehand, so an organic reach explanation seems unlikely.

According to Grok those accounts are @_NathanCalvin (General Counsel at Encode AI), @peterwildeford (Head of Policy at the AI Policy Network), and @DKokotajlo (Head of the AI Futures Project), all of which are up-and-coming AI-Doomer policy advocacy nonprofits.

The AI Futures Project website says it is funded “primarily” by the Survival and Flourishing Fund, which says on its own website that it has advised Jaan Tallinn, Skype creator and one of the leading investors in Anthropic, to grant over $2.5 million to the AI Futures Project since 2024.

Encode AI says on its website that it is ALSO funded by the Survival and Flourishing Fund, which in turn says that it told Anthropic investor Jaan Tallinn to grant $516,000 to Encode AI in 2025.

And wouldn’t you know it, the Survival and Flourishing Fund ALSO says it told Jaan Tallinn to grant $2 million to the AI Policy Institute, the 501(c)(3) affiliate of the AI Policy Network, as well.

What are the odds that the first three quote tweets of Coxon’s post would all be major AI-restriction policy advocates funded generously by the same donor, who also happens to be one of the leading investors in, and a board member of, Anthropic, the company Coxon was resigning from? And all within 15 minutes of posting (two within ten)?

3.) Jacob Coxon doesn’t have much of a resume, but we do know that, in 2022, he got a $20,159 scholarship for the “long term future scholarship program” from the Good Ventures Foundation, one of the philanthropic vehicles of Dustin Moskovitz, a notorious AI-doomer who has spent tens if not hundreds of millions on policy advocacy to strictly regulate AI, while also being an Anthropic Investor himself.

It also just so happens that the 14th person to quote Coxon’s post was @MaxNadeau_ (27 minutes after posting) who is the program officer for the Technical AI Safety team at Coefficient Giving, another of Moskovitz’s philanthropic spending vehicles. Max is not a frequent poster, his last posts before quoting Coxon were before Labor Day, but he was remarkably quick off the mark for this one.

4.) Basically every major Democrat politician and candidate has suddenly glommed on to this post, and conveniently, as the people cry out foe answers, Bernie Sanders already has a bill written to “ban super intelligence” and regulate AI into oblivion, and will be releasing later this week. The bill, among many other things, will create “a new cabinet-level federal agency to safeguard the public from the dangers of artificial intelligence” that will be “advised by an Artificial Intelligence Advisory Board comprised of experts on artificial intelligence.” Do you think, perhaps, Anthropic and its many investors who fund AI policy advocacy might have interest in getting to place a pet “expert” on the board of an entity that dictates what AI is and isn’t allowed to do? And isn’t it fortuitous that this whistleblower came forward with his oh-so scary stories so close in proximity to the release of the most radical piece of AI legislation ever introduced?

[David Sacks @DavidSacks]

Some thoughts on Dario’s post:

1. Dario does not actually address Gavin Baker’s account of what he said – something he could easily deny if it were inaccurate.

2. Dario claims his critics live in a “bubble” where all regulation equals regulatory capture. He calls this an overly simplified view and notes that “Many people outside this bubble think of regulation as something that constrains corporate power and benefits ordinary people.” This argument is a straw man. Of course treating all regulation as capture would be overly simplified – but almost no one holds that view. I have repeatedly argued for strong antitrust enforcement to keep industries competitive, especially Big Tech. If Anthropic continues toward monopoly or duopoly status, I would be among the first to demand those rules apply.

3. Regulatory capture is not vague or in the eye of the beholder. Nobel laureate George Stigler defined it as regulation acquired by an industry and designed and operated primarily for its benefit. Stigler challenged the traditional view that government regulation arises from a benevolent state protecting the public from market failures. Rather, industry groups have concentrated stakes and pour resources into influencing regulators, whereas the public’s stake is diffuse and unorganized. The revolving door between companies and the agencies that regulate them compounds the problem. Anthropic understands these dynamics: it has hired multiple senior Biden AI-policy officials and built a substantial government-affairs operation plus a network of aligned organizations to push its preferred frameworks at state and federal levels.

4. Dario has consistently pushed for a new federal agency to review and approve frontier models prior to release – a proposal framed variously as an “FDA for AI,” an “FAA for AI,” and most recently a “FINRA for AI.” I call it a “DMV for AI” because a review process modeled on the FAA or FDA (which takes years) or FINRA (which issues rules for a staid industry widely seen as protecting incumbents) will create long queues as AI models wait for testing and approval. This process will only become more labyrinthine as rules accumulate to prevent theoretical harms. This would handicap the U.S. relative to China, which will not adopt the same constraints. It would also undermine Anthropic’s own business model, whose pricing power depends on remaining ahead of open models. Whatever Dario states today, it is difficult to believe the company would simply accept outcomes that erase that advantage.

5. Anthropic is on track to become one of the most valuable companies in history, with the resources to navigate any approval process and shape the rules while competitors wait. Dario wants open models under heavier scrutiny – he has called them dangerous in Senate testimony, criticized them for not being centrally monitored or withdrawn, and linked them to IP theft. He says he has never sought a ban, but he could achieve a similar result by insisting that identical rules apply to both open and closed models. The U.S. risks becoming an island of costly closed models while the rest of the world races ahead with broader choice.

6. Dario acknowledges that AI is structurally centralizing but attributes this mainly to chips and scaling laws. Access to compute matters, but the deeper risk is who decides which capabilities are available to whom. His preferred pre-deployment testing and FAA/FINRA-style oversight would place that gatekeeping power in a federal bureaucracy working hand-in-glove with a small number of frontier labs – reinforcing centralization rather than countering it.

7. The second part of Dario’s post assumes we have amnesia about Anthropic’s well-orchestrated campaigns hyping AI fears. His May 2025 claim that AI would wipe out 50 percent of entry-level knowledge jobs within five years still lacks supporting evidence fifteen months later. Similarly Anthropic breathlessly promoted its heavily contrived “blackmail” study on 60 Minutes. Yet Dario blames public negativity on a long-standing loss of trust in institutions rather than his own messaging.

8. These narratives have done more than anything to shape public fear. People are left asking the same question Mark Zuckerberg posed: why race to build a future you describe in such negative terms? Thomas Sowell’s "The Vision of the Anointed" captures the mindset – elite intellectuals convinced that only they are enlightened enough to control the outcome. As Zuckerberg notes, concentrating power in the hands of an enlightened few has rarely produced the promised results; the practitioners turn out to be less enlightened in practice than in self-conception.

9. Gavin Baker summarized the disagreement cleanly on our pod: Dario believes frontier AI is too powerful to distribute; we believe it is too powerful to centralize. Dario appears to believe, sincerely, that safety and progress are best served by centralizing authority in a marriage of corporate and state power. The weight of human history gives us reason to fear that outcome.

[Edward Yavno @edyavno]

@shellenberger One very important aspect is not covered in the article - the likely case that Anthropic is pursuing a regulatory capture strategy and hence has an incentive of creating a lot of fear. Related - how many executives came from the Biden admin & tried to restrict AI dev before?

[Marc Andreessen 🇺🇸 @pmarca]

🇺🇸

[Edward Yavno @edyavno]

@gregisenberg It's also great as a "second brain" for teams building multiple services to help connect them all in a form of self maintained knowledge base that you can also use to build new connected services. Been using it for months for building trading systems with a great result.

[Edward Yavno @edyavno]

@HilzFuld You answered your own question. It's not for power users. Power users use a phone when they need mobility or use a higher-end laptop or desktop when they need power. Everybody else, iPad fits nicely in between and replaces a laptop for many average consumers.

[Edward Yavno @edyavno]

@davereaboi Completely different experience here. And I use AI professionally. For research, especially something that references recent events, Grok is really good. And Grokipedia is very good too, much better than Wikipedia.

[Edward Yavno @edyavno]

@unclebobmartin Was/is very practical with PIT when in Java. Why would you say it was impractical before but is now? I don't think agentic coding adds something new in this particular case. Not following your reasoning here @unclebobmartin

[Insurrection Barbie @DefiyantlyFree]

https://t.co/pyqLItyhvJ

[Edward Yavno @edyavno]

@dhh Everybody who tried FSD in the last month or so is probably realizing that the rest of the cars are now obsolete. Once the unsupervised version clears regulatory impediments, the owners will basically get a car AND a full time personal driver for the price of a car.

[Dr Milan Milanović @milan_milanovic]

𝗠𝗼𝗱𝗲𝗿𝗻 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 𝗡𝘂𝗺𝗯𝗲𝗿𝘀

Most engineers still quote Jeff Dean’s 2012 latency pyramid

But hardware has sprinted ahead: an NVMe drive can fetch a 4-KB block faster than a datacenter round-trip used to take

Here are the numbers you should keep in your head in 2025:

𝙻𝟷 𝚌𝚊𝚌𝚑𝚎 𝚛𝚎𝚏𝚎𝚛𝚎𝚗𝚌𝚎 ≈ 0.𝟽 𝚗𝚜
𝙻𝟸 𝚌𝚊𝚌𝚑𝚎 𝚛𝚎𝚏𝚎𝚛𝚎𝚗𝚌𝚎 ≈ 𝟸.𝟻 𝚗𝚜  𝟹× 𝙻𝟷
𝙻𝟹 𝚌𝚊𝚌𝚑𝚎 𝚛𝚎𝚏𝚎𝚛𝚎𝚗𝚌𝚎 ≈ 𝟾  𝚗𝚜  𝟷𝟷× 𝙻𝟷
𝙱𝚛𝚊𝚗𝚌𝚑 𝚖𝚒𝚜𝚙𝚛𝚎𝚍𝚒𝚌𝚝 ≈ 𝟾  𝚗𝚜
𝙼𝚞𝚝𝚎𝚡 𝚕𝚘𝚌𝚔 / 𝚞𝚗𝚕𝚘𝚌𝚔 ≈ 𝟸𝟻  𝚗𝚜
𝙼𝚊𝚒𝚗-𝚖𝚎𝚖𝚘𝚛𝚢 (𝙳𝙳𝚁𝟻-𝟻𝟼00) 𝚛𝚎𝚏𝚎𝚛𝚎𝚗𝚌𝚎 ≈ 𝟽0  𝚗𝚜  𝟸𝟾× 𝙻𝟸
──────────────────────────────────────────────────────────────
𝚂𝚎𝚗𝚍 𝟸 𝙺𝙱 𝚘𝚟𝚎𝚛 𝟷0 𝙶𝚋 𝙴𝚝𝚑𝚎𝚛𝚗𝚎𝚝 ≈ 𝟷.𝟼 µ𝚜
𝙲𝚘𝚖𝚙𝚛𝚎𝚜𝚜 𝟷 𝙺𝙱 𝚠𝚒𝚝𝚑 𝚂𝚗𝚊𝚙𝚙𝚢 ≈ 𝟸  µ𝚜
𝚁𝚎𝚊𝚍 𝟺 𝙺𝙱 𝚛𝚊𝚗𝚍𝚘𝚖𝚕𝚢 𝚏𝚛𝚘𝚖 𝙽𝚅𝙼𝚎 𝚂𝚂𝙳 ≈ 𝟸0 µ𝚜
𝚁𝚎𝚊𝚍 𝟷 𝙼𝙱 𝚜𝚎𝚚𝚞𝚎𝚗𝚝𝚒𝚊𝚕𝚕𝚢 𝚏𝚛𝚘𝚖 𝚖𝚎𝚖𝚘𝚛𝚢 ≈ 𝟸0 µ𝚜  (≈𝟻0 𝙶𝙱/𝚜)
𝚁𝚘𝚞𝚗𝚍-𝚝𝚛𝚒𝚙 𝚠𝚒𝚝𝚑𝚒𝚗 𝚜𝚊𝚖𝚎 𝚍𝚊𝚝𝚊𝚌𝚎𝚗𝚝𝚎𝚛 ≈ 𝟾0 µ𝚜
𝚁𝚎𝚊𝚍 𝟷 𝙼𝙱 𝚜𝚎𝚚𝚞𝚎𝚗𝚝𝚒𝚊𝚕𝚕𝚢 𝚏𝚛𝚘𝚖 𝙽𝚅𝙼𝚎 𝚂𝚂𝙳 ≈ 𝟷00 µ𝚜
──────────────────────────────────────────────────────────────
𝙳𝚒𝚜𝚔 𝚜𝚎𝚎𝚔 (𝟷𝟻 𝚔 𝚁𝙿𝙼 𝙷𝙳𝙳) ≈ 𝟺  𝚖𝚜
𝚁𝚎𝚊𝚍 𝟷 𝙼𝙱 𝚜𝚎𝚚𝚞𝚎𝚗𝚝𝚒𝚊𝚕𝚕𝚢 𝚏𝚛𝚘𝚖 𝙷𝙳𝙳 ≈ 𝟷0  𝚖𝚜
𝙲𝚛𝚘𝚜𝚜-𝚘𝚌𝚎𝚊𝚗 𝚁𝚃𝚃 (𝙲𝚊𝚕𝚒𝚏𝚘𝚛𝚗𝚒𝚊 ↔ 𝙽L) ≈ 𝟷𝟺𝟻 𝚖𝚜

𝗪𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝗲𝗱 𝗶𝗻 𝘁𝗵𝗲 𝗺𝗲𝗮𝗻𝘁𝗶𝗺𝗲?

🔹 NVMe killed “slow” SSDs. Random 4 KB reads are ~20 µs, 7× faster than the 150 µs SATA numbers you learned a decade ago.
🔹 DDR5 is wider, not much quicker. Raw DRAM latency only dropped from ~100 ns to ~70 ns, but bandwidth doubled; a 1 MB sweep now finishes in ~20 µs.
🔹 In-rack networking is microsecond-class. Modern fabrics (RoCE/100 GbE, Mellanox BlueField, etc.) hit sub-100 µs RTT inside one datacenter, below the regional 1-2 ms “cloud” numbers.
🔹 Cross-region RTT hasn’t moved. Physics still rules; fiber across the Atlantic is ~145 ms round-trip.

𝗪𝗵𝗮𝘁 𝗱𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗺𝗲𝗮𝗻 𝗳𝗼𝗿 𝘀𝘆𝘀𝘁𝗲𝗺 𝗱𝗲𝘀𝗶𝗴𝗻?

1. One fast box beats many mediocre ones. A single beefy VM with NVMe and 1 TB of RAM can serve hundreds of thousands of requests per second with single-digit-millisecond p99, often easier than sharding.

2. Cache everything you can. Terabyte-class Redis/Memcached nodes are routine; at 70 ns DRAM latency, a cache miss is now far costlier than a hit.

3. Think µs, not ms, inside your DC. Any microservice hop, queue, or serialization step competes with ~80 µs network RTT. Count how many you can afford in a 100 ms SLA.

Keep these new baselines handy during architectural discussions.

#softwareengineering #programming #systemdesign

[Edward Yavno @edyavno]

@unclebobmartin don't know if this is exactly what you're looking for, but this is a simple example I've used in several talks training people internally to illustrate how clean readable code is important for maintainability.

https://t.co/ggLZltkcAC

[Edward Yavno @edyavno]

A definite must read and know for Software Engineers and Architects - "Designing Data-Intensive Applications (DDIA)" https://t.co/VDSaUthPQJ

[Edward Yavno @edyavno]

https://t.co/wJCkyrT47J