Research program
IP in a World of Abundant Intelligence
This program asks which parts of an advantage remain scarce when capable models and competent software are widely available. Assume intelligence, research, and engineering keep getting cheaper, and protect the parts of an advantage that remain scarce under that assumption. It matters because today's implementation difficulty should not be mistaken for a durable advantage.
Which parts of an advantage remain scarce when capable models and competent software are widely available?
Use a harder starting assumption
Do not build a strategy around what current models cannot do. First identify the actual obstacle: missing context, data, permission, tools, evaluation, orchestration, compute, physical access, regulatory authority, or a genuinely unsolved capability.
If ordinary software work, analysis, drafting, simulation, or integration is the obstacle, treat it as temporary until evidence says otherwise. A future competitor should be assumed to have strong financing, competent people, and AI several capability generations ahead.
Run compression and resilience together
The compression test asks how much of the advantage disappears as AI improves. The resilience review asks what remains scarce afterward. They are two views of the same asset and should use the same assumptions, horizon, and evidence.
High compression does not mean a patent is useless. It means today's implementation difficulty should not be mistaken for durable Native Alpha™.
Track where scarcity moves
Engineering labor, search, drafting, documentation, analysis, design iteration, and routine software may become cheaper. Proprietary data, customer access, regulatory position, workflow control, trust, physical access, contractual rights, historical knowledge, and time-dependent learning may become relatively more important.
The review should record past scarcity, present scarcity, likely future scarcity, and the event that would change the view. Old assets can gain value when a missing component becomes cheap. New assets can decay when the hard part becomes ordinary.
Attack the boundary
Ask a well-funded competitor to deliver the same customer result without using the proposed claim. Generate alternate architectures, substitutions, workflow bypasses, regulatory routes, manual alternatives, and different data sources. Record the cost and performance penalty for each route.
Classify the result from trivial substitution through commercially unattractive or technically impractical. The aim is not to produce a large list. It is to find the easiest credible escape before money and time are committed.
Use the wind tunnel
The wind tunnel is the full stress test. It combines prior art questions, alternative implementations, design-arounds, substitute technologies, cost reduction, future capability assumptions, regulatory alternatives, business-model alternatives, and adjacent uses.
Generated possibilities are research leads. They do not prove prior art, enablement, conception, inventorship, validity, or infringement. Material legal conclusions stay with qualified counsel.
Keep negative know-how
Knowing what fails can save more time and risk than knowing one successful route. Record failed technical approaches, hidden operating problems, rejected workflows, regulatory dead ends, bad thresholds, and the conditions under which each failure appeared.
Some failure knowledge belongs in a patent or defensive publication. Some should remain confidential know-how. The choice depends on whether others can discover it, whether disclosure helps the commercial position, and whether secrecy can be maintained.
Review the half-life
Native Alpha™ can decay as models, platforms, standards, regulation, costs, and customer behavior change. It can also strengthen when a new right, data source, distribution path, or enabling technology appears.
Review an asset when a material condition changes, not simply once a year. Record the change, the evidence, the effect on scarcity, and the decision it alters.
Stress-test record
Keep the assumptions visible. A composite score must not hide one fatal weakness.
| Dimension | Working question | Failure signal |
|---|---|---|
| Compression | What becomes cheap or easy? | Most value sits in routine implementation |
| Resilience | What remains scarce? | No scarce asset can be named |
| Design-around | How can a rival preserve the result? | Low-cost equivalent route |
| Half-life | What change erodes the advantage? | Near-term change removes the constraint |
| Negative know-how | Which failed paths save real cost? | Failures are unrecorded or public |
Research notes
Adversarial design-around report
Give a capable future competitor the customer outcome and ask for credible routes around the proposed boundary. This report shows whether the boundary holds: each route is ranked by how much penalty it carries, so a reader sees which boundaries are real and which a rival can walk around cheaply.
AI compression test
This note gives a test for how much of an asset's claimed advantage survives when AI makes ordinary reasoning and software cheap, so a reader can see which advantages disappear and which remain. It is a scenario test, not a forecast. Assume capable AI makes ordinary reasoning and software cheap, then identify how much of the claimed advantage disappears.
AI resilience score
Test what remains scarce after a competitor gains better models, tools, and engineering capacity. The score reviews dimensions such as proprietary data, legal rights, and workflow control, supports each score with a source and contrary case, and rejects resilience that depends only on today's model weakness.
Negative know-how ledger
This note gives a ledger of failed approaches, so the cost of a failure is not paid again when a person or project leaves. It records the conditions that make each approach fail and what design decision the lesson changes, and it keeps evidence and uncertainty attached rather than folklore. Preserve failed approaches and the conditions that make them fail before the lesson leaves with a person or project.
Scarcity migration and half-life review
Review where scarcity sat, where it sits now, and which change will move it next. The review ends in a decision to protect, test, move effort, open a layer, license, sell, maintain, or stop. A date without a named change and evidence is guesswork, not an asset half-life.
Related
- Which entirely new forms of work become possible with modern AI?
- Zero Neo
- AI compression test
- AI resilience score
- Scarcity migration and half-life review