Baseline Skepticism Partners, LP Quarterly Letter to Limited Partners Q2 2026 (Interim)

Dear Partners,

We are pleased to report that the fund’s core thesis — that reality reliably underperforms its own marketing — continues to generate returns. Our benchmark, which we have titled the Narrative Discount Index, widened again this quarter across every sector we track. We remain positioned accordingly.

For new investors receiving this letter for the first time: our strategy is simple. We observed several years ago that a trading bot purchasing “No” on every non-sports prediction market was quietly outperforming most active managers. Not because the bot understood anything about any individual market. Because people consistently overprice the interesting outcome. The exciting prediction attracts liquidity the way a porch light attracts moths — not because the light is going somewhere, but because it is bright.

We have generalized this observation into a fund. What follows is our quarterly review of positions.

Position 1: The Provenance Discount

We maintain significant short exposure to trust derived from surfaces.

This quarter validated the position twice, in what we are calling the Verification Pair. In the first instance, a buyer acquired thirty WordPress plugins through a legitimate marketplace, in a transaction that looked entirely normal, and used the resulting access to install backdoors across hundreds of thousands of websites. The attack was invisible for eight months. The command-and-control infrastructure ran on an Ethereum smart contract, making traditional takedowns ineffective. WordPress.org had no mechanism to flag ownership transfers. The acquisition looked so ordinary that looking ordinary was, in fact, the attack.

In the second instance, a researcher investigated a compression library that had been formally proven correct in Lean. The proofs were mathematically sound. The compression and decompression functions did exactly what they claimed to do. The bugs were in the parser that fed data to the proven code and in the runtime that executed it — components that sat outside the boundary of verification but inside the boundary of trust. As one commenter noted, quoting Knuth: “Beware of bugs in the above code; I have only proved it correct, not tried it.”

We view these as the same trade. A plugin marketplace says “this developer is trusted” the way a proof assistant says “this function is correct.” Both statements are true within their own scope and misleading outside it. The interesting question is never whether the verification passed. It is where the verification stops. We remain short the assumption that the boundary of proof and the boundary of danger are the same line.

As a corollary, we note that a 158-year-old federal ban on home distilling was overturned this quarter by a court that observed, in effect, that the government’s claim to regulate what a person does alone in their own home was a trust surface with nothing behind it. We have added a small position.

Position 2: The Authenticity Spread

We are long the gap between what platforms say they are protecting and what they are actually protecting.

Consider two data points from the same week. A major mobile operating system now strips location metadata from every photo a user uploads through a browser. The stated reason is privacy — users might not realize they are sharing GPS coordinates. The unstated fact is that the platform retains full access to that same metadata through its own applications. The user’s data has not been protected. It has been rerouted. The photo, which once spoke freely about where it was taken, now speaks only to its landlord.

Meanwhile, a venture-backed startup was caught operating a farm of physical phones running hundreds of AI-generated social media personas — fake people with fake faces posting fake opinions to real platforms. The startup had raised money from one of the most prominent firms in Silicon Valley. When a hacker compromised the system and tried to post memes calling the investors the antichrist, the company assured everyone that no unauthorized posts were successfully published. We note the word “unauthorized” is doing extraordinary work in that sentence, given that every post the farm has ever published was, in a meaningful sense, unauthorized by the person it pretended to be.

The spread here is wide and, we believe, durable. One company strips authentic data in the name of protecting users. Another manufactures inauthentic data in the name of serving them. Both describe their work as building trust. We have found that when two opposing operations use the same vocabulary, the vocabulary is the product being sold, not the operation. Some websites, we are told, have begun hijacking the browser’s back button so that users who try to leave are redirected back to the page they were trying to escape. We view this as the logical endpoint of the authenticity spread: a door that performs the function of a door but is not, in any operational sense, a door.

Position 3: The Complexity Premium (Short)

We continue to short the assumption that complexity signals value.

One of our favorite indicators this quarter was an infrastructure engineer who wrote, with the weariness of someone who has been awake for a long time, that he simply wanted object storage that stores objects. The available options included a system that had pivoted to AI, a system that was “unnecessarily complex,” a system that was architecturally interesting but inexplicably slow, and an enterprise-grade distributed storage platform designed for exabyte-scale deployments. He needed a few gigabytes on a local network. He eventually found a tool that just used the local filesystem, which worked immediately and at full speed.

We track this pattern across sectors. The market consistently rewards complexity because complexity is difficult to evaluate, and things that are difficult to evaluate are easy to misprice. A simple tool invites the question “is this enough?” A complex tool invites the question “do I understand this?” The second question is more profitable for the seller because the answer is always no, and the buyer blames themselves rather than the product.

Our position is straightforward: when someone builds something simple that works, the market will initially ignore it. This is the window in which we buy.

Outlook

We are often asked whether our thesis is cynical. We would like to clarify that cynicism is a prediction about motives. Our thesis is a prediction about outcomes. We do not claim that anyone is lying. We claim that the interesting version of events — the one where the acquisition is strategic, the proof is comprehensive, the protection is real, and the powerful are playing chess — is simply priced too high. The boring version, in which the acquisition is normal, the proof has edges, the protection is partial, and the powerful are winging it, is where we find consistent alpha.

A colleague recently shared an essay arguing that we should stop attributing grand strategies to powerful people when the simpler explanation is that they are, in the author’s words, just doing dumb shit. We have not added this to our formal investment framework, but we have printed it and taped it above the coffee machine. It is, in our view, the single most underpriced insight in public markets.

The bot that buys “No” on everything does not understand any of this. It does not read the news. It does not evaluate claims. It does not distinguish between a prediction about geopolitics and a prediction about whether a celebrity will adopt a tiger. It buys “No” and it makes money. Not because nothing ever happens, but because what happens is almost never the thing that was exciting enough to bet on.

We remain positioned.

Respectfully,

The General Partners Baseline Skepticism Partners, LP

This letter is provided for informational purposes only and does not constitute an offer to sell or a solicitation of an offer to buy any securities. Past performance of reality is not indicative of future results, though we have found it to be a remarkably reliable guide.