0xmelon

[0xmelon @0x_melonn]

Why is that the Consumer print is flat and every time I went to grocery, the price of daily goods is just higher and higher

[a16z crypto @a16zcrypto]

https://t.co/9gWWVgitKA

[0xmelon @0x_melonn]

@maggielove_ @jonwu_ Congrats! I wear the same dress when I got married! Love this Qipao!

[Perry Jia @perryzjia]

We're scaling @sundayrobotics's Data Ops team and looking for people who thrive in fast-moving AI environments. If you've helped build, scale, or run data operations for frontier labs or annotation companies, we'd love to have you on the team!

- Data Annotation Lead: https://t.co/T2Xt8wKo3c

- Technical Program Manager, Data Annotation: https://t.co/eHFbiyoCgG

- Evaluation Operations Associate: https://t.co/N9338UA4Dq

If you're confident you're the right fit or know someone who'll do great in one of these roles, please apply or share respectively!

[0xmelon @0x_melonn]

Inflation is really significant right now. Why the market is ignoring this? With 10Y treasury yield break 4.5%, will the market still ignore this?

[0xmelon @0x_melonn]

@coolish 魏神生快🎂！这是神级操作哇

btw bcoin上的API 过期了可以更新下不🧐

[0xmelon @0x_melonn]

It's really disappointing to see how these big players just lawyered up and pointed fingers instead of figuring out a way to work.

[Perry Jia @perryzjia]

Want to break into robotics but don't have prior experience?

Sunday is opening the door!

We're hiring Memory Developers to help train the next generation of general-purpose robots.

As a Memory Developer, you won’t just collect data—you will shape the “memory” of our robot and play a vital role in training the AI that powers it. Using provided hardware, you will record high-quality demonstrations of household tasks that directly influence how our robot learns to perceive and act in real environments. This is a flexible, remote, part-time role for individuals who are excited to contribute to the future of robotics.

Compensation follows our pay-per-task model:
- $30 per hour of approved data during a 1-week screening period
- Up to $60 per hour of approved data for more complex tasks after screening

If you're excited about robotics and want to be part of building something real, this is your chance to get started. 🚀

Apply here: https://t.co/qOhz2281lR

[0xmelon @0x_melonn]

@alexgroberman where is the Anthropic hiring post from Anthropic?

[0xmelon @0x_melonn]

Well said!

Critical time for organization leaders to adapt

[Jim Bianco @biancoresearch]

An Alternate View of the Post-AI Labor Market

AI collapses software costs and automates database drudgery. This newly affordable efficiency makes demand explode, creating new complex problems that future companies with human employees will solve. Yet if job destruction outpaces creation, we risk a historical societal revolt instead of a technological breakthrough.
----
The fear echoed in the Citrini Research report that AI will usher in a doomsday labor market fundamentally misunderstands the nature of business.

At its core, every business exists to solve a human problem. A hospital treats illness, automakers create affordable transportation, restaurants serve cheap fast food, and homebuilders create dependable housing. The fatal flaw in Citrini’s narrative is the assumption that humanity has a finite number of problems. Solve the current problems, and we will not create new ones.

Creates More Problems

When technological progress makes resource usage more efficient, Jevons Paradox suggests demand for that resource explodes higher.

If agentic AI brings the cost of drafting a lawsuit down to near zero, a lawyer is not going to pack up and go home. He or she is going to file exponentially more lawsuits, creating massive new demand for legal defense and judicial review.

MIT labor economist David Autor argues that while automation changes tasks, it does not destroy human work. We will use freed up time to expand what is possible and invent entirely new complex problems that require new companies with human employees to solve.

Winners and Losers

The first wave of this disruption is already driving the broadening market rally as software development costs are collapsing to zero.
Historically, companies like Salesforce and Bloomberg spent billions building desirable software products. They rely on expensive per-seat pricing to fund these massive builds.

Thanks to agentic AI, a few coders can recreate parts of a CRM or a data terminal in months for a fraction of the cost while offering it substantially below legacy companies’ current pricing. A CTO looking at thousands of per-seat licenses will easily justify tearing out embedded legacy systems to save tens of millions.

* Loser – Companies that spent a lot of money creating software.
* Winner – Companies that spent a lot of money purchasing that software.

Breaking Free From the Database

Modern knowledge work has devolved into a mind-numbing exercise in which workers are chained to a screen updating databases. Even the simplest task requires begging a database for permission, beginning with the universal frustration of trying to log in with a username and password.

Ethan Mollick, a professor at the Wharton School, champions AI for its ability to eliminate this exact workplace drudgery. Agentic AI will take over database management, freeing us to make judgment calls and actually problem-solve. The office will stop being a screen prison and return to being a hub of collaboration.

Scarcity Versus Overhead

When a job is disrupted, the outcome depends entirely on which part is automated.

For 150 years, the hard part of driving a London taxi was passing the knowledge test. This involved memorizing 25,000 streets and nearly 20,000 landmarks. This took three or four years, often riding around London on a moped. This knowledge created a scarcity of qualified drivers, allowing them to command a premium wage.

GPS automated this scarcity into a free app, flooding the market with new competitors (Uber/Bolt), which flattened wages. Technology took away the hard part of being a taxi driver, making the role less valuable.

On the flipside, computers automated tedious data entry for accountants. Because the hard part of human judgment remained, accountants used freed up time to solve complex problems, recasting their role from bookkeeper to financial advisor. Technology took away the easy part, making the worker more valuable.

The Myth of the Broken Apprenticeship

Critics argue AI will destroy the apprenticeship model by automating junior-level grunt work. Mindless data entry does not teach high-level strategy. When the drudgery is removed, young workers can focus on the hard part of the job from day one. Instead of destroying the apprenticeship, AI accelerates it.

We saw this exact fear when computer-aided design (CAD) replaced hand drafting. Senior architects worried young designers would never learn fundamentals without drawing every line by hand. Instead, the new generation learned to build vastly more complex structures. The AI transition will do the same thing for knowledge work.

Transition

This transition will not be easy. Just look at the struggle C-suite executives faced in embracing hybrid work. If leaders fought a simple change in where people sit, how will they handle the total upheaval of their embedded software and labor models? Will they stay stuck in the past, supervising the database updating? That is exactly why the most exciting companies today are run by 30-year-olds with zero legacy baggage.

Additionally, the timeline of that transition matters.

During the Industrial Revolution, technology eliminated old jobs long before new ones materialized. Economists call this brutal fifty-year gap (around 1790 to 1840) the Engels Pause, named after Friedrich Engels, co-author of The Communist Manifesto.

That gap between job destruction and job creation sparked a massive collective pushback against capitalism that the world came to know as Communism. Karl Marx directly observed this dangerous dynamic, writing that when an instrument of labor takes the form of a machine, it immediately becomes a competitor of the worker himself.

If the AI rollout creates a similar, disconnected trade-off in which jobs vanish first and new opportunities appear much later, we will see another collective pushback.

Conclusion

The post-AI labor market need not be a jobless dystopia or a science-fiction utopia. It will be a turbulent acceleration. The winners will be the agile companies buying cheap software and the workers using AI to skip the hazing of database drudgery. The ultimate test, however, is not technological. It is societal. We must ensure the gap between the jobs destroyed and the complex problems we invent is as narrow as possible. If we fail to bridge that gap, the next great innovation will not be a new software model. It could very well be a revolution.

[0xmelon @0x_melonn]

Repricing is the theme now in the AI agentic world.

[Sunday @sundayrobotics]

After 18 months in stealth, dozens of prototypes, millions of real-home demonstrations, and one final all-nighter, we’re thrilled for you to say hello to Memo

[0xmelon @0x_melonn]

👀

[Sunday @sundayrobotics]

November 19

[0xmelon @0x_melonn]

Interesting!

[Carlos E. Perez @IntuitMachine]

1/16

I just fell down a rabbit hole reading a new paper from economists at MIT & Harvard.

Their prediction is wild: We're on the verge of a "Coasean Singularity"—a future where AI agents make markets so efficient that the very idea of a 'company' starts to crumble. 🤯

A thread 👇

2/16

First, a quick 101: Why do companies even exist?

A Nobel-winning economist named Ronald Coase answered this in 1937. He said companies exist because using the open market is a pain.

Finding sellers, negotiating prices, writing contracts… it’s all “transaction cost.” Economic friction.

3/16

It's often easier and cheaper for a firm to just hire people and organize them internally than to deal with that constant market friction.

This friction is also where we, as consumers, lose. We're tired, we're biased, and we don't have time to compare every cell phone plan or read every review for a toaster.

Companies know this.

4/16

Now, enter the AI Agent.

And I don't mean a simple chatbot. The paper describes an autonomous system that acts on your behalf.

Think of it as your own personal, tireless, super-rational economist. It’s immune to marketing tricks and its only goal is to get the best outcome for YOU.

5/16

This is where the "Singularity" happens.

When everyone has an AI agent, those transaction costs that Coase talked about basically drop to zero.

The "friction" that made companies necessary in the first place? It evaporates.

And if the reason for something disappears… so does the thing itself.

6/16

But what does this future actually look like? This is where it gets weird.

Let's take shopping.

Your agent doesn't just browse Amazon. It might contact a manufacturer in another country directly, find 500 other agents whose users want the same thing, negotiate a bulk price, and arrange shipping.

All in milliseconds. The "storefront" becomes irrelevant.

7/16

Or think about hiring.

Instead of you endlessly scrolling LinkedIn, your agent scans the entire market for opportunities. It negotiates salary, benefits, and remote work policies with the company's agent.

You only get involved for the final human-to-human interview. No more cover letter hell.

8/16

But this discovery comes with a huge catch. The paper outlines a fundamental battle for the future of AI:

Will your agent be a "Bring-Your-Own" (BYO) agent that works only for you, across all platforms?

Or will it be a "Bowling-Shoe" agent, provided by the platform (like Amazon or Google), whose priorities might be... conflicted?

9/16

The "Bowling-Shoe" agent is convenient, but it might steer you toward the platform's own products.

The "BYO" agent is loyal to you, but platforms might try to block it or throttle its access.

This tension between user autonomy and platform control will define the next decade of the internet.

10/16

And that's not even the most interesting part. This new world creates bizarre new problems.

Problem #1: Agent Congestion.

What happens when millions of agents can create a perfect, customized resumé and apply for a single job in a nanosecond?

Employers get flooded. The signal is lost in the noise.

11/16

The paper predicts that to solve this, platforms will have to re-introduce friction.

Imagine having to pay a small fee for your agent to submit a job application, just to prove you're serious.

Costless actions will lose their meaning.

12/16

Problem #2: The Identity Crisis.

In a world full of bots, how do you prove you're a unique human? How does a company know it's not negotiating with 1,000 agents all controlled by one person trying to manipulate the market?

This is the "Sybil Attack" problem, and it's a big one.

13/16

This will lead to a boom in "proof-of-personhood" technologies. Systems that cryptographically verify you are one person, without revealing your personal data.

It sounds like sci-fi, but it'll be the essential plumbing for a world of AI agents.

14/16

Here's a new lens to see the world through:

Next time you use Uber (matching drivers/riders), Zillow (matching buyers/sellers), or Upwork (matching clients/freelancers)...

Don't just see an app. See it as a clunky, early prototype for the agent-driven markets of the future.

15/16

This isn't just about better shopping bots or smarter assistants.

It's a potential rewiring of our entire economy, away from the 20th-century model of the centralized firm and toward a 21st-century model of fluid, hyper-efficient, agent-mediated markets.

16/16
The 20th century was defined by the rise of the corporation.

The 21st may be defined by its slow, quiet dissolution.

[0xmelon @0x_melonn]

Intelligence is the computational part of the ability to achieve goals.

The best definition of intelligence

[Nick Timiraos @NickTimiraos]

NEW: Every living former Fed chair (Greenspan, Bernanke, Yellen) ...

have joined several former Treasury secretaries (Rubin, Summers, Paulson, Geithner, Lew) ...

and CEA chairs (Hubbard, Mankiw, Romer, Furman, Rouse, Bernstein) who served presidents of both parties ...

in an amicus brief to the Supreme Court warning a ruling against Lisa Cook's ability to stay in her job would significantly erode Fed independence https://t.co/oNa1wJoBau

[0xmelon @0x_melonn]

@Derivatives_Ape wdym by part of HL?

[0xmelon @0x_melonn]

Why the consumption is still on a strong level while most of the survey-based data is showing very low confidence in the comsuption future?

My answer is the K-shaped economy.

[0xmelon @0x_melonn]

3 years ago, if your Perp dex had intuitive user experiences, you are already a outlier.

Now almost every legit Perp dex has sleek UX, time to compete with how to use different tools, (usually not the product, but the expectation of incentives, incentives itself) to adopt some users and retain them

[Edgy - The DeFi Edge 🗡️ @thedefiedge]

We’re so used to narratives having a short shelf life. Something I’ve noticed is that some narratives can be sticky across multiple generations with each one bringing new opportunities.

Perp dexes are a good example. I’ve been bullish on this sector since 2020. You can think of sectors as different generations.

Generation 1:

Early projects like MCDEX were among the 1st wave. They were rough around the edges but showed it was possible to run perps on-chain.

Generation 2:

Then came @GMX_IO , @GainsNetwork_io , Levels, and @dYdX . This was the breakout era. Mf’ers got tired of token inflation and they started demanding projects with “real revenue.”

This generation improved on the previous protocols. They fixed liquidity problems, improved user experience, and made perps a lot more mainstream.

Generation 3 (today):

@HyperliquidX is still the clear leader, but now fresh challengers are emerging. @Aster_DEX , @Lighter_xyz , and @edgeX_exchange are stepping in, each aiming to take a piece of its crown.

Here are a few lessons from watching this play out:

• Some narratives stick around for multiple cycles. Perps are proving to be one of them.
• Every new generation needs to innovate. If you just repeat what came before, or you’ll get left behind.
• Missing one trade isn’t the end of the world. New waves always bring new chances.

The big idea? Pay attention to how each wave builds on the last. That’s usually where the best opportunities show up.

It’s interesting to see what other sectors this shows up in. I’m seeing this with Layer 1s obviously and some stablecoin protocols.

I guarantee we’ll keep seeing variations of Friend tech until the end of time (mf'ers gotta farm their followers)

I was hoping to see more innovation with GameFi but I haven’t seen too many yet.

I think we'll see this idea play across DeFAI and A.I. Agents.

[0xmelon @0x_melonn]

@Rewkang The market potential is absolutely insane. The entry barrier for this field is high, especially the controls system.

Great piece of work! Would love to have some skin in the game