Cunningham’s Law

“The best way to get the correct answer on the Internet is not to ask a question, it’s to post the wrong answer.” — Ward Cunningham (attributed; popularised on Wikipedia)

The Claim

A stated-but-wrong answer extracts correct information from experts faster and more reliably than a sincere, well-posed question. People who would ignore a question feel compelled to correct an error. The psychology of correction is stronger than the psychology of altruistic help.

Why It Holds

Three overlapping motivations produce the effect:

1. Correction is higher-status than explanation. Pointing out that someone is wrong is an opportunity to demonstrate expertise; answering a question is work.
2. Errors violate the reader’s norms. Misinformation that passes uncorrected feels like a failure — especially for experts who see amateurs encountering the wrong answer downstream. The urge to correct is partly defensive.
3. Wrong answers are more engaging than questions. Questions are abstract; wrong answers are concrete claims. Concrete claims have more attack surface, which makes them easier to refute in detail. (This is the same reason negative reviews are richer than positive ones.)

The effect is amplified by scale: any sufficiently wrong claim on a sufficiently visible platform will attract corrections from the small subset of readers who are both expert and annoyed.

In This Wiki

• An applied inversion to knowledge discovery. The conventional path (“ask for the answer”) is slow and uncertain; the inverted path (“propose the wrong answer”) extracts the same information faster. Inversion applied to epistemology.
• Adversarial bayes-theorem. A confident wrong answer shifts the expert’s mental model from “passive observer” to “active corrector” — which increases the information content of their response. You’re not trying to receive knowledge; you’re trying to provoke an update that you can absorb.
• A niche of Naval’s “tweet first” heuristic. Naval’s rule: “When you tweet something, you quickly learn what’s right and what’s wrong.” Short, sharp, concrete claims attract concrete feedback. Cunningham’s Law is the stronger form: wrong claims attract correction faster than ambiguous ones attract engagement.
• A tool against dunning-kruger-effect. If you’re unsure whether you understand a topic, post your understanding. The corrections — or their absence — are evidence. Silence from experts is often genuine confirmation that your model is adequate.
• Tempered by hanlons-razor. The internet’s correction-attackers often assume malice in the original claimant (they must be spreading misinformation!). Cunningham exploits this, which is why the technique feels manipulative to some. Be honest about what you’re doing, at least with yourself.
• Connects to Linus’s Law. “Given enough eyeballs, all bugs are shallow” — Linus’s Law is Cunningham’s Law applied to code. A wrong implementation, once public, attracts many independent reviewers who surface bugs a single author couldn’t have seen. The PR review process depends on this dynamic.
• Connects to Gall’s Law. Post a simple wrong first version; iterate toward the correct version through feedback. This is the normal path of knowledge-building on the internet. Working systems evolve from simpler working systems — including simple wrong ones.

Applications

• Technical writing. Drafting a concrete (even if flawed) hot-take on a topic and sharing it with knowledgeable peers extracts more information than asking “what do I need to know about X?”
• Code review. Submitting a working-but-suboptimal implementation as a draft PR produces richer reviewer engagement than describing the problem and asking for suggestions. Reviewers see a specific solution and evaluate it; they don’t have to do the design work themselves.
• Startup validation. Launching a wrong/incomplete product produces actionable feedback faster than market research. Users tell you what’s wrong because they can use it and observe the failure; they cannot tell you what they want in the abstract.
• Learning. Writing down your current understanding and inviting correction is more efficient than passive consumption. The “teach it to learn it” method is Cunningham with a friendly audience.

Limits

1. Backfire at scale. Confident wrong claims on contentious topics attract more wrong claims, not correction. The dynamic depends on the audience having experts and the topic having a defensible correct answer.
2. Social cost. Repeatedly posting wrong things to learn is expensive on reputation. Use sparingly, and in contexts where the “I was wrong” update is cheap.
3. Doesn’t work for things with no right answer. Aesthetic, political, and preference questions don’t have corrections to extract. Cunningham’s Law is about facts, not opinions.
4. Adversarial exploitation. Some bad actors have learned to leverage Cunningham dynamics for attention and engagement, degrading the information quality of the platforms on which it operates (see much of the 2020s attention economy).

The Deeper Principle

Cunningham’s Law is really a specific case of a more general epistemic rule: concrete claims are easier to evaluate than abstract questions. The move from vague to specific — even if the specific claim is wrong — always helps the conversation because it creates something the other party can attack.

This is why first-principles-thinking asks specific questions (“what is actually true here?”) rather than general ones (“what should I believe about this?”). Specific questions and specific claims have specific answers; abstractions don’t.

Sources

• source—laws-of-software-engineering — in the Decisions cluster.
• Attributed to Ward Cunningham (inventor of the wiki). The formulation appeared in Steven McGeady’s keynote at OSCON 2010.