
CTO: Chief TheFinals Officer @Sign
Irvine
Joined April 2012
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Jack Xu retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.
- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.
The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.
So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability.
The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code.
But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along.
So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions.
TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
We closed out UN Week with a warm evening in New York, cohosted with @MoCTI_SL last Friday.
Our founder @realyanxin joined Chief Minister @dsengeh, Minister @SalimaMBah, Ambassador Dr. Abu Bakarr Karim, @ChristexFndn founder @c_ogoo, and many friends to reflect on our journey together and share what comes next.
We and Sierra Leone are thinking much bigger.
Having worked with these guys over the past 3 years, they have my full trust and endorsement.
CODESPECT is more than a smart contract audit firm.
We are an offensive cybersecurity company operating across Web3 and Web2. We combine smart contract expertise with application security and adversarial testing to review the full attack surface: contracts, websites, APIs, bots, backend systems, and off-chain logic.
Our work is neither AI-only nor manual-only. It is a rigorous combination of advanced tooling, AI-assisted analysis, and experienced human security researchers.
We are not positioned as the cheapest provider, nor are we priced for appearances. Our pricing reflects the depth of work, responsibility, and skilled team required to protect serious protocols.
We have maintained this standard even in a difficult market because security cannot be reduced to a checkbox. It is a shared responsibility between protocol teams and auditors.
Our team holds certifications including CRTP, OSCP, CEH, and eCPPTv2, with experience across private institutional engagements and competitive reviews such as SpecSiege.
In DeFi, our expertise spans vaults, options, RWAs, leverage, order books, lending and borrowing, and more.
Clients come to CODESPECT for a review. They return for a long-term security partnership.
Code. Inspect. Protect.
bitcoin:native
So far price is playing out as expected,
Didn't sweep the dL, so it's possible we might clear it after testing the TWO and wVWAP.
Overall nothing much to update, the plan is still the same - Pump into the zone above and then reject from there.
bitcoin:native
Here's what I am looking over the weekend,
After sweeping the range highs at 81.3k, price dumped to 76.9k.
Now we are chopping into the weekend and what I am expecting next is,
The sweep of dL (77.3k) followed up by a pump to the high probable lower high levels/zone, which are:
TWO (78976)
wVWAP (79085)
We also got a 15 mins OB above, which could give a decent rejection.
Overall, this is what my weekend plan looks like based on the thesis I gave in the previous post.
Following consensus from Sign Foundation and the majority of our backers, we are updating the $SIGN token unlock schedule.
The first three unlocks remain unchanged: 1/24 monthly through July 2026.
After that, unlocks will move into spaced tranches:
• Jan 15, 2027: 1/4
• Jul 15, 2027: 1/4
• Jan 15, 2028: 1/4
• Apr 15, 2028: final 1/8
The revised schedule is being synced to CoinMarketCap
coinmarketcap.com/currencies…
All investor and early contributor tokens remain fully unlocked by April 15, 2028. This is a timing restructure, not an extension. There is no preferential acceleration.
The purpose is to reduce continuous monthly overhang and turn unlocks into managed liquidity events aligned with stronger business and market windows.
We are also launching Forward Claim, a dedicated venue for locked tokens, allowing eligible holders to rebalance through an OTC-style forward market without impacting spot liquidity.
More details will follow.
Our LZ receiving libraries have been pinned. Thanks for the heads up @EbisuEthan. Also, the same pinning should be done for every network that the OFT supports, not just Ethereum.
Lost aura, gained security, A-OK.
Updated our tooling to detect pinning. github.com/Built-by-Sign/lay…
layerzero solosig dependency check in
if you haven't hardened your config, you are sitting on an unnecessary dependency on layerzero 3/5 solosig.
if it gets compromised, it could instantly drain all the adapters that rely on the default receive library. after the kelp exploit, the vulnerable adapters tallied to $3.13 billion. after some outreach, the number has dropped to $178 million.
good progress, but still not enough. there is still a long tail of projects that have ignored this advice.
i will make this simple for you. here is a full list with exact calls for how to pin the default library.
gist.github.com/banteg/cbf75…
Jack Xu retweeted
#Bitcoin days are numbered. It seems like just a matter of time before it suffers the same fate as online gambling.
Today, we are open-sourcing a toolkit ported in Go that parses and writes SWIFT MT messages as a part of our ongoing CBDC work.
Aside from being used for international wire transfers, the MT format is also core to certain RTGS systems in central banks.
github.com/Built-by-Sign/swi…
In light of recent events, we are open-sourcing a local web tool that helps projects easily manage their LayerZero OFT wiring configurations, when the OFT delegate is a Safe multisig.
Configurations can be imported or exported as JSONs for convenience.
github.com/Built-by-Sign/lay…
This weekend KelpDao lost $292M. @LayerZero_Core just published their incident report.
The protocol worked as designed. The smart contracts were fine. The money left through an RPC poisoning attack on a single-DVN configuration that multiple parties had warned against.
A thread on what this teaches us about every attack surface. 🧵

























