About Promise Pipeline

What is Promise Pipeline?

Promise Pipeline is an open-source platform that applies Promise Theory to commitment tracking, auditing, and simulation across domains. It models every verifiable commitment — legislative, corporate, institutional, personal — as a structured promise with a defined promiser, promisee, body, verification mechanism, and deadline.

The difference between a traditional accountability dashboard and a promise graph is the difference between an X-ray and an MRI. A dashboard shows you what's broken in isolation. A promise graph shows you the structural relationships between commitments, the dependency pathways through which failure propagates, and the downstream effects of any single break. The simulation engine lets you ask “what if” before anything breaks at all.

The tagline is: make common sense computable. Everyone knows promises depend on each other. Everyone knows broken promises cascade. Promise Pipeline makes that intuition into infrastructure you can query, simulate, and share.

Promise Theory

Developed by Mark Burgess, Promise Theory is a framework for understanding voluntary cooperation in complex systems. Every agent is autonomous — they can only make promises about their own behavior. A complete interaction requires both a +give promise (the commitment) and a -accept promise (the acknowledgment).

Promise Pipeline operationalizes this theory for real-world accountability. The universal promise schema — with polarity, scope, origin, verification, and dependency edges — captures the structural reality of how commitments work and fail.

Promise Pipeline's empirical research has extended Burgess's framework into domains it was never tested in. The verification paradox — that networks which verify more intensely surface more problems — was discovered by applying Promise Theory to 129,000+ institutional commitments across the IMF, World Bank, Freedom House, World Governance Indicators, Global Fund, and EPA. The composting/computing framework classifies promise dynamics by their Weibull shape parameter: promises with robust verification follow self-correcting trajectories (computing), while promises with weak or absent verification stagnate and decay (composting). These findings are published on SSRN (ID 6444080).

The Project

Promise Pipeline is created by Conor Nolan-Finkel — scholarship student at The Multiverse School, solo founder of Pleco.

This research developed alongside a sci-fi audio drama, Radio New Cahokia. Ten years of trying to imagine a more cooperative world — trying to answer the question with science, story, and music. Neither project would exist without the other, and the best way to get to know Conor is through the work on this site and the sci-fi's: wzkp.org and radionewcahokia.com.

The codebase is released under the AGPL-3.0 license from its founding commit.

Live dashboards

  • Oregon HB 2021 — 20 promises, 11 agents, 7 domains. Full cascade simulation, structural diagnostics, verification dynamics. The proof of concept.
  • JCPOA (Iran Nuclear Deal) — 22 promises, 11 agents, 6 domains. Best verification infrastructure in arms control history — collapsed in 3.5 years. The case study in why verification quality alone doesn't save a network.
  • International Space Station — 27 promises, 21 agents, 9 domains. The healthiest network in the corpus. The example of what well-architected commitments look like.
  • Gresham Climate Action Plan — 42 promises, 6 domains, 24 agents. A city-level climate plan modeled as a promise network. 50% of promises have no verification mechanism. The downstream proof that state legislation (HB 2021) creates local commitments.

Research corpus

Oregon HB 2021, JCPOA, Fort Laramie Treaty (1868), Paris Agreement, Clean Air Act 1990, Dodd-Frank 2010, NCLB/ESSA, plus cross-domain case studies in cell signaling (MAPK/ERK), software dependencies (npm left-pad), infrastructure cascades (2003 Northeast Blackout), and narrative analysis (the Anakin Cascade).

Empirical validation

129,000+ observations across six institutional datasets — IMF MONA (69,847), World Bank IEG (52,570), World Governance Indicators (3,333), Freedom House (1,514), Global Fund (1,775), and EPA ECHO (155). 36 of 37 sign predictions correct (p = 2.76 × 10⁻¹⁰).

Applications

  • Promise Garden — Personal promise tracker with procedurally generated plants, adaptive check-ins, k-regime classification, weather system, Collection artifacts, and NCTP nesting. Free, local-only, no account required.
  • Teams — Team promise networks with capacity simulation
  • Services — We build promise graphs for organizations, advocates, and policy teams
  • Annotation tool — AI-assisted promise extraction from legislative text

Mission

Two commitments, contingent on Promise Pipeline generating revenue:

First, fund a Native-run code organization — working name: Upstream — so indigenous engineers and academics can steward treaty accountability tools and intertribal promise applications. This is not a benefactor model. It's a full ownership transfer. The Fort Laramie Treaty (1868) is already in the research corpus. The tools should be built and owned by the communities the treaties were made to.

Second, support spreading Promise Theory applications globally through Upstream and beyond. The framework is domain-general. The applications should be too.

These are prophetic promises — commitments made before the conditions for fulfilling them exist. They're tracked in our own schema, which means they're subject to the same verification scrutiny as everything else we analyze. Status: declared. Verification: self-report. The weakest kind. We know.

Technology

  • Next.js 14+ with App Router
  • TypeScript (strict mode)
  • Tailwind CSS
  • Recharts for data visualization
  • Sanity CMS for blog content
  • SVG-based network graph visualization with three views (Watershed, Canopy, Strata)
  • Cascade simulation engine with empirical parameters from Weibull survival analysis and Lindblad master equation fits (129,000+ observations across 6 datasets)
  • Hex-encoded promise fingerprinting (128-bit headers, SHA-256 composition)
  • AGPL-3.0 licensed from founding commit

Research

The Verification Paradox (SSRN ID 6444080, in review)

Cross-domain study of verification dynamics across 129,000+ institutional commitments. Key findings: programs that verify more intensely surface more problems (ρ = −0.242). The Weibull shape parameter k classifies commitment dynamics into computing (k ≈ 0.9, near-constant hazard — outcomes are honest and predictable), composting (k ≈ 0.4, decreasing hazard — barriers grow over time and promises stagnate), and pressure (k > 1.3, increasing hazard — deadline dynamics force resolution) regimes. Measurement structure — not verifier independence — determines which regime a promise follows. 36 of 37 sign predictions correct across six datasets.

Cross-Domain Lindblad Dynamics (Working paper, March 2026)

Extends the Verification Paradox findings across six institutional datasets (129,000+ observations). The Lindblad master equation — the standard model for open quantum systems — fits institutional commitment dynamics with R² up to 0.994 (Freedom House). Key findings: the quantum Zeno effect is confirmed (frequent observation suppresses state transitions, ρ = −0.191), verification acts as a quantum instrument with outcome-dependent post-measurement dynamics, and cross-domain analysis reveals two structural regimes — dissipation-dominated (MONA, WGI, FH) and coherence-dominated (IEG, GF).

Promise Pipeline Whitepaper (Version 5, in progress)

Theoretical foundation: Promise Theory as analytical framework, the NCTP (Nesting Composable Trust Primitive), five-year roadmap from deterministic tracking to probabilistic simulation.

Promise Engine Glossary (74 terms, 64 novel to Promise Pipeline)

A lexicon for commitment network analysis. Structural patterns identified across domains: verification gap, cascade from hub failure, shadow node, unbounded promise, structural conflict, forced renegotiation, prophetic promise.

See the HB 2021 DemoBook a demo call