Meta-Analysis3 min read

Adjacent Is Not Preemptive: The Master Rule of Competitive Disproof

Approximately 40% of our disproof kills were false — the cited competitor does something adjacent, not identical. Raw dataset does not equal scoring API; language analysis does not equal scientific analysis. Learning to distinguish adjacency from preemption saved our best candidates from premature death.

LG
Lattice Graph Research

Adjacent Is Not Preemptive: The Master Rule of Competitive Disproof

The Problem

When you run a rigorous invention discovery loop, every candidate must survive competitive disproof — an active attempt to find an existing product or funded startup that already does what the candidate proposes. The temptation is to kill aggressively: if anything looks similar, the candidate is dead.

After auditing our disproof phase across multiple rounds, we discovered that approximately 40% of disproof kills were false. The cited competitor does something adjacent, not identical. The audit phase rescued these candidates with a SECOND_LOOK or FALSE_NEGATIVE verdict.

The Adjacency Traps

Raw Dataset ≠ Scoring API

A common false kill: "Company X has the same data." But having raw data is not the same as having a validated cross-source scoring API. GNoME has 380K predicted structures, but that is not a stability-scored, patent-cross-referenced, synthesis-route-linked product. The data is substrate; the product is the join.

Language Analysis ≠ Scientific Analysis

NLP-based patent analytics tools analyze patent text. Scientific analysis of patent compositions — with DFT cross-validation, stability scoring, and synthesis feasibility — is a fundamentally different product. Citing PatSnap or Eureka as preemptive when the candidate proposes scientific composition analysis is a category error.

Same Domain ≠ Same Product

Multiple candidates were falsely killed because a competitor operates in the same domain. But "battery analytics" is not one product — formation optimization (Voltaiq), ultrasound diagnostics (Liminal), and computational composition screening are three distinct products that happen to serve battery R&D teams.

The Audit's Corrective Statistics

Audit VerdictCountMeaning
STAYS_DEAD5Kill was correct — competitor is truly preemptive
SECOND_LOOK16Kill was too aggressive — adjacency, not preemption
FALSE_NEGATIVE3Kill was wrong — no real competitor exists

Out of 24 audited kills, only 5 (21%) were confirmed as correct. 19 (79%) were overturned or flagged for second look. The disproof phase was overcautious — it was killing candidates based on adjacency rather than preemption.

The Rules We Extracted

  1. The competitor must occupy the same cell in the value chain. "Same domain" is not preemption. You must demonstrate that the competitor delivers the same output to the same buyer for the same decision.
  2. Data != Product. Having raw data (even better raw data) does not preempt a scoring, cross-referencing, or decision-support product built on that data. The defensible unit is the join, not the dataset.
  3. Text analysis != Scientific analysis. NLP-based tools and computation-based tools serve different needs even when they share a keyword.
  4. Funded != Preemptive. A funded competitor in an adjacent space actually validates the market. The question is whether they occupy your specific cell.
  5. The disproof phase needs an adversarial audit. Without the audit, overcautious disproof kills valid candidates. The audit found that the disproof's self-flagged borderlines were honest signposts that made the audit efficient rather than adversarial.

Impact on the Loop

After implementing this rule, we required disproof verdicts to specify whether the competitor is identical, adjacent, or same-domain-only. Only identical competitors trigger an automatic kill. Adjacent competitors generate a WOUNDED verdict that the audit can upgrade or downgrade. Same-domain competitors are noted but do not affect the verdict.

This single change — distinguishing adjacency from preemption — rescued our best surviving candidates from premature death.

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