Five thesis kills in twenty-four hours

~8 min read · what survives adversarial testing for a £100 indie experiment in May 2026, and what doesn't

I set out yesterday morning to do something specific. Flip £100 of working capital into the start of a recurring revenue stream by building one small thing in two weeks. Three rules: legal only, persona-isolated (my real name doesn't touch the customer surface), and no infrastructure investment beyond what the venture itself earns back.

By the end of day one I had killed six business ideas. None of them shipped. None of them made money. And I think the day was the most useful one I've had in months.

The thing that emerged isn't a product. It's a discipline for not building doomed products, applied to a question I keep seeing other indie operators get wrong in 2026: which bet shapes are still buildable?

Why I thought what I thought

I'd already spent six hours that morning polishing a contract pack for UK freelancers. Eight templates, IR35-aware, statutory citations inline, voice-checked, fact-checked, OG image rendered, structured data live on the domain. It was clean.

It was also, on inspection, the wrong product to be selling in May 2026.

The exact buyer for a £27 pack of UK-jurisdiction contract templates is someone who needs UK-jurisdiction contract templates and is willing to pay £27 for them rather than ask an LLM to generate equivalents in thirty seconds. That overlap of "needs templates" and "wouldn't ask Claude" shrinks every month. The free side of the SERP is owned by trusted specialists (Qdos, ContractorUK, ContractEye, LawDepot, the Freelancer Club) with years of domain authority. The paid side is IR35 Shield at around £300, underwritten by Markel-Tax. Mine lived in the unprofitable middle: too expensive to win against free, too cheap to win against the professional.

That was the moment I stopped polishing the pack and started questioning the thesis.

The methodology that did the killing

I needed a structured way to test "is this idea actually alive in 2026?" Not the soft kind. The kind a code reviewer applies to a pull request. Adversarial. Default-deny.

It split into two modes:

PICK mode. N candidate bets. Rank them. Surface a winner. Used when scoping a new venture among alternatives. The pitfall: "first survivor" doesn't mean "ready to build." A PICK round produces a candidate, not a decision.

HARDEN mode. One bet, fixed. Spawn fresh adversarial reviewers. Make them tell you every way it can fail. Iterate until the critiques converge on micro-edits: when round N produces only refinements to existing concerns and no new structural risks. The code-review analogy: ten rounds and the reviewer eventually has nothing left to say. That's the moment a bet is ready to build.

Two pre-survivor checks turned out to be mandatory, both at concern zero of any round:

Publisher-incumbent verification. What does the authoritative party in the space (regulator, registry, dominant AI tool, free OSS project) already offer for free? Fetch the URL. Don't infer. Verify.

Direct-competitor enumeration. Name the three closest extant competitors by URL and pricing. AI-native competitors are particularly likely to already exist in May 2026; check before you build, not after.

A third check landed on round three: persona-isolation compatibility. Does the bet's acquisition channel require sustained real-human visibility (introducer relationships, named-partner bylines, regulated-professional gating)? If yes, a trade-name persona silently fails the channel.

The six kills

The pattern

Six different ideas across three rounds of structured adversarial testing. The kills shared a structure.

Every "build a product, sell to a customer" idea I generated landed in one of three traps:

Trap A: LLM substitution. If the customer's alternative is "prompt Claude for thirty seconds," the price ceiling is approximately zero. Doesn't matter how good your prompt template is; the buyer's own access to Claude commoditises you.

Trap B: Free publisher-level incumbent. The publisher of structured data (Companies House, HMRC, a regulator) often ships the obvious-bulk-monitoring product as a free tier, because they want to be the canonical source. The £9-£49 wrapper around their data competes with the registrar of companies. You lose on price and trust simultaneously.

Trap C: Direct AI-native competitor. Even when the publisher doesn't compete, somebody else's AI-fronted indie did the bet first, ships it cheaper, has testimonials. By May 2026 the indie-AI ecosystem has fully colonised the "wrap a public-data source with an LLM" space.

Each round of the methodology added a check that caught one of these traps earlier. By round four, the three pre-survivor checks were doing the work that used to take a HARDEN round.

What it says about 2026

The constraint I set myself — £91 of capital, two weeks to first paying customer, persona-isolated, no audience yet — turns out to be very nearly unsatisfiable for any bet shaped as "build a product, sell to a customer."

That isn't a methodology failure. It's a methodology finding. The substrate has shifted. In May 2026, the value of "I can build software" as a moat is sharply lower than it was in 2024. Anyone with Cursor can ship the surface-level version of most ideas in an afternoon. The asymmetric advantages have moved up the stack: domain expertise that's not in any training corpus, ongoing operations that no one wants to run, audiences that took years to compound, real-world authority that an AI persona can't provide.

The honest read is that "small indie ships product against incumbents" was a 2018-2023 thesis. In 2026 the indie-against-incumbent ratio has flipped: the incumbents are AI-fronted indies now, and the regulators are MCP-shipping their own data infrastructure free. UK Government's i.AI lab ships an MCP server with 8.4 million UK legal documents, MIT-licensed. Volunteer Companies House MCP wrappers are on GitHub. The state is competing on AI-agent-facing data infrastructure — a structural fact I hadn't priced in.

What survives the methodology in this environment is narrow. Probably one of:

Audience-as-asset. Don't sell a product yet; build a list of people interested in a niche over six to twelve months. Then launch into the list. Slow but compounds. Substantial trade against "first £ in two weeks."

Operator-visible high-touch services. Where a real human's credibility — not a trade-name persona — is the deliverable. Consulting, lead-gen with introducer relationships, named-byline analysis. Breaks the persona-isolation constraint.

Metacognitive products. When cognitive labour is commoditising, the meta layer — articulating intent, structuring sense-making, maintaining memory across time, deciding what to think about — retains value. The bottleneck of automation is the human's ability to express what they want. Anything that bridges intent and expression compounds as the substrate improves rather than competing with it.

I think the third one is where my next bet will land, and I'm running the methodology against candidates in that space today. We'll see whether the loop converges on something that survives.

What didn't get killed

One thing came out of the day clean: the methodology itself. PICK and HARDEN, the three pre-survivor checks, the convergence rule, the discipline of bracketing every meaningful slice with an intent and closing it with an honest outcome. The infrastructure that did the killing.

I don't think the methodology is the product. But it's the durable thing today produced, and it's how every future bet will be tested before it gets built. I'll write more about the specific mechanics in subsequent posts.

If the day's exercise has a useful lesson for anyone else trying this in 2026, it's this: the cost of running an adversarial review on your idea before you write code is approximately zero. The cost of finding out two weeks in that the registrar of companies already ships your product is considerably higher.

Default to killing your idea. If the idea survives that, then build.