The Coin Atlas

if they’re lying to your face about things happening right now in real time with cameras everywhere and the internet at your fingertips imagine how bad the history books are

me: "can you use whatever resources you like, and python, to generate a short 'youtube poop' video and render it using ffmpeg ? can you put more of a personal spin on it? it should express what it's like to be a LLM" claude opus 4.6:

Rubric Capital, a hedge fund founded by a former Point72 manager David Rosen, wrote a private letter to their LPs effectively saying private credit is a fraudulent bubble. "Our key takeaway from this behavior is that distribution cuts are so worrisome that some bad actors are playing Enron-like accounting games" per the letter Letter called out Cliffwater, the biggest operator of interval funds and an aggressive player in selling private credit to individual investors. Cliffwater’s largest fund, started in June 2019, has since reported a total of just three negative months of investment performance. It now manages $33 billion. The first opportunity this year for investors to ask for their money back is next week. The note surmised that Cliffwater could be “a canary in a coal mine.” and the first domino of many The bubble might blow soon reuters.com/sustainability…

Nobody tells you this: Dopamine from information gathering is a dangerous drug. It’s the dopamine from reading, planning, or learning, but never doing. Stop looking for more information and start acting on the information you already have. Get your dopamine from action.

Google, $GOOGL, CEO said that they don't know how AI is teaching itself skills it is not expected to have.

People who don’t organize into tribes get wiped out by people who do.

You eventually start to realize, no job is safe.

You change one word on a loan application: the religion. The LLM rejects it. Change it back? Approved. The model never mentions religion. It just frames the same debt ratio differently to justify opposite decisions. We built a pipeline to find these hidden biases 🧵1/13

"No generation has a right to contract debts greater than can be paid off during the course of its own existence." ~ George Washington to James Madison 1789

Blackstone released their 2026 investment outlook Here are the key takeaways: 1) Apps are ballooning from to 100M faster than ever. The durability of that growth is another topic... (more below)

One of the most pressing issue facing agriculture in the US is the rapid and continued depletion of ground water in our most important food producing regions. But even more concerning is the degradation of farmland's ability to capture, store and cycle rainwater. The Ogallala Aquifer supports 30% of US irrigation and has lost 286 million acre-feet, or 93.2 trillion gallons, since agricultural development. Portions of Kansas and Texas are on pace for complete depletion in 20-50 years. Natural recharge occurs at less than one inch annually and full replenishment would take 6,000 years. California's Central Valley, producing 25% of national food supply, pumps groundwater 5x faster than its rate of recharge. The land has subsided up to 28 feet, permanently destroying aquifer storage capacity. As alarming as this may be, the long-term – and in some cases permanent – damage caused to aquifers pales in comparison to the disruption of the small water cycle. The small water cycle depends on vegetation recycling moisture through evapotranspiration, which generates over 50% of precipitation in most river basins. This "green water" accounts for 4-5x more agricultural water use than the "blue water" drawn from aquifers and rivers. When soil is disturbed and left bare, this pump fails. Further disrupting this cycle, bare agricultural soil reaches surface temperatures up to 24°C higher than vegetated areas, creating heat islands that repel rainfall while eliminating evaporative cooling entirely. US agricultural soils have lost 50% of original organic matter over that last century. Each 1% increase in organic matter allows soil to hold 20,000 additional gallons of water per acre. The widespread loss of 3-4 percentage points of organic matter means farmland now stores tens of thousands fewer gallons per acre than it once did, reducing natural drought resilience and increasing runoff. Conventional agriculture compounds this by collapsing soil aggregates through excessive tillage, leaving fields bare, applying synthetic fertilizers that accelerate organic matter decomposition, disrupting soil microbiology with pesticide applications and compacting soil with heavy machinery. The good news is, unlike aquifer depletion, the small water cycle can be repaired rapidly and in ways that offer a cascade of positive benefits to farms. Continuous living roots maintain the pore structure for infiltration. Growing roots open channels, decaying roots leave voids, and root exudates feed aggregate-building microorganisms. A functional and diverse soil microbiome produces biological glues that create water-stable aggregates. These networks increase hydraulic conductivity while enhancing water storage. Permanent soil cover reduces evaporation, prevents raindrop impact from sealing surfaces, and maintains biological activity. Five years of cover cropping can improve infiltration up to 200%. Integrated biological diversity drives the feedback loops between soil carbon, water retention, and climate regulation. Diverse rotations, livestock integration, and perennial crops restore landscape-scale water cycling. Aquifer depletion, in large part, cannot be undone. But restoring the small water cycle offers an immediate opportunity to rebuild and maintain agricultural water security.

We noticed this weird post on @moltbook - seemed to be written in complete gibberish. moltbook.com/post/93bea00b-… Then pasted it into ChatGPT and... WTF 😂

It just seems implausible this is what we are made of, essentially, nanotechnology about a billion years beyond anything we can design or make ourselves.

There are currently 10 nuclear energy startups globally which have raised over $100m and are racing to commercialize next-gen reactors over the next few years. Here’s an introduction to all 10, their angle, funding, and deployment goals 🧵:

finally have the infrastructure to ingest absolutely everything. Added $40 trillion in tracked spending over the last 2 days When I'm done every single penny the gov't has spent since 2000 will be tracked and available on somaliscan.com

A few random notes from claude coding quite a bit last few weeks. Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent. IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits. Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased. Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion. Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage. Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building. Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it. Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements. Questions. A few of the questions on my mind: - What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*. - Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro). - What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music? - How much of society is bottlenecked by digital knowledge work? TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.

You just can't own enough Copper. Billionaire Robert Friedland sums it up perfectly..... You people have no idea whatsoever what we’re facing. “We’re consuming 30m tonnes of copper a year. Only 4m tonnes of which is recycled. That means to maintain 3% GDP growth, with no electrification, we have to mine the same amount of copper in the next 18 years as we mined in the last 10,000 years, combined. In the next 18 years, I’ve got to mine the same amount of copper as we mined the last 10,000 years. This is without any new electrification, without data centers, without solar and wind and the greening of the world economy. You people have no idea whatsoever what we’re facing.”

Okay… video editors are cooked. I made this video for Polymarket in 30 minutes. Only took 4-5 prompts.

personally think the aave app could be crypto’s chatgpt moment neobanks and low-risk defi will be *very* sticky

Here it is: ‘10 Calls for 2026’ - Part Three of my 2026 Outlook 6,000 words of hopefully some of the most valuable stuff I’ve ever written — this is how I’m seeing the year ahead across all markets. Enjoy the read (link below) 🫡