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AI-Native Research

A working-paper series on the theory of the AI-native firm


What this is

Classical theory of the firm carries four implicit axioms: value grows with accumulation; assets depreciate and liabilities are repaid to zero; firm value equals the present value of cash flow; marginal cost is positive and hard to attribute per unit.

This series argues — and proves, where proof is possible — that all four are rewritten for a class of firms whose capability base accumulates almost without bound but whose value delivery is bandwidth-capped. The claim is not that these firms are better. It is that they are not obtainable as a parameter limit of the traditional firm, and so require a distinct analytical object.

All papers are pure theory. Numbers are illustrative calibrations, not empirics. Each paper states an explicit refutable interface — the conditions under which it would be overturned.


The argument chain

Paper I  ──►  Is value finite when accumulation is unbounded?
              Yes — saturation decoupling. Value's finiteness is
              independent of the growth rate.
                 │
                 ▼
Paper II ──►  Granting finiteness, how should such firms be valued?
              Cash-flow anchoring incurs a strictly positive,
              closed-form misspecification cost, monotone in
              distance to saturation. FACE re-anchors on net worth.
                 │
                 ▼
Paper III ──► What do I and II jointly imply?
              Four axioms of the traditional firm are rewritten,
              interlockingly, and irreducibly. A new species.

Papers

# Title Status EN 中文 Notes
I Saturation Decoupling: Finite Firm Value under Unbounded Capital Accumulation Working paper · v2 · Jun 2026 PDF PDF
II Saturation Room and Firm Value: A Valuation Framework for AI-Native Firms Working paper · v1 · Jun 2026 PDF PDF
III The AI-Native Firm as a New Species: A Research Programme Research programme · v1 · Jun 2026 PDF PDF

→ Full index with abstracts and open objections: /papers


Frameworks

Analytical tools extracted from the papers, usable independently.

Framework One-liner From
Saturation Room Value lives in the gap S = x̄ − x, not in current cash flow Paper II
FACE Valuation Re-anchor valuation from cash-flow history to net-worth accumulation Paper II
Non-Monetary Balance Sheet Five assets, five liabilities, direction set by meta-capability Paper II
Amdahl Bottleneck Why accelerating execution lengthens the value–cash-flow lead Papers I & II

Open problems

The programme is unfinished by design. What is genuinely unsolved:

  • Operationalizing the species criterion — how is "axiom rewritten" measured in data?
  • Measuring the non-monetary balance sheet — the A/C taxonomy is proposed, not validated
  • Identification of (𝒩, h, κ) in FACE — consistency is proved; uniqueness is not
  • A Coasean boundary model where judgment bandwidth, not transaction cost, sets the boundary
  • Panel-data empirics for every testable prediction in Papers I and II

The exogenous-shock design in Paper II §6.1 — frontier-model releases as date-stamped, firm-exogenous shocks — is the most readily identified and the natural first empirical target.


Notes

Work in progress: half-formed arguments, reading notes, counterexamples. Less polished, more frequent. → /notes


Citing

@misc{mei_ainative_2026,
  author = {Mei, Junjie},
  title  = {AI-Native Research: Working Papers on the Theory of the AI-Native Firm},
  year   = {2026},
  url    = {https://github.com/MedocMay/AI-Native-research},
  note   = {ORCID: 0009-0002-8909-8229}
}

Individual papers carry their own citation blocks in their subdirectories.


Disagree?

The point of working in the open is to be corrected faster. The strongest objections to each paper are listed in its own README under "Why it might be wrong." If you have a better one — or a counterexample — open an issue.

Collaboration on the empirical work is actively sought. Contact: maymedoc@gmail.com


CC BY 4.0 · Junjie Mei (Dan) · FrontierFirm.Fund

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Why classical firm theory breaks when capability accumulates faster than it monetizes. Open working papers on the AI-native firm.

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