What the experiment demonstrates
RN can move from an unresolved question to a bounded, testable public artifact: finding the decision, structuring the evidence, designing the interaction, implementing the system and documenting what it cannot claim.
100 QUESTIONS · 200 PUBLIC EXPERIENCES
THE 100start anywhere.
One hundred questions that were too messy for a single discipline—turned into working tools, visual arguments and inspectable records.
Each build has two ways in:A / USE IT — a functional tool, system or experiment
B / WATCH + EXPLORE IT — the LinkedIn cut, a motion argument and the richer interactive web version
Open an overview first when you want the question, purpose, RN's role, evidence status and limitations in one place.
THE PRACTICE BEHIND THE COLLECTION
Research that becomes something people can use.
RN's role
Across this independent collection, RN serves as researcher, strategist, information architect, interaction designer, builder, editor and QA lead. Individual build records identify deeper methods and evidence where certification is complete.
Method
Question → evidence → model → working A build → visual B argument → testing → record → lineage. Later builds inherit real capabilities from earlier ones instead of restarting from zero.
Prototype boundary
These are independent research-and-design prototypes unless a build explicitly says otherwise. They demonstrate thinking and implementation; they are not client endorsements, deployed institutional systems, legal advice or medical advice.
WORK WITH RN
Bring the question that does not fit neatly inside one discipline.
RN works across research, strategy, legal and regulatory systems, AI governance, knowledge architecture and public-facing explanation. The wider portfolio and tailored Selected Works provide the shortest path for a specific opportunity.
ON VIEW — released workIN THE LAB — working prototype; certification continuesA — USE THE TOOLB — WATCH THE CUT, EXPLORE THE ARGUMENT, USE THE WEB MASTER
FIND YOUR WAY IN
Start with your question—not Build 001.
Search the full collection or choose the visitor path closest to why you are here. Every result opens a plain-language overview before the working tool and visual story.
100 of 100 builds shown
Understand & structure the problem
10 SHOWN001 / 100FEATURED · ON VIEW
Human Review Design Framework
Determine whether a human reviewer can actually change or stop an AI-assisted decision.
002 / 100ON VIEW
Multi-Audience Meaning Architecture
Explain one defensible idea to different audiences without changing the underlying truth.
003 / 100ON VIEW
Unserved Decision Discovery
Find recurring decisions for which people have information but no usable decision system.
004 / 100IN THE LAB
Manual Intelligence Engine
Turn disciplined human research into a repeatable intelligence workflow before automating it.
005 / 100IN THE LAB
Service-to-Software Discovery
Decide which repeated service steps should become software, remain expert judgment, or disappear.
006 / 100IN THE LAB
Does This Actually Deserve to Be Software?
Test whether a tracker or process should become software, service, dataset, company—or stay simple.
007 / 100IN THE LAB
Feedback Loop Product Architecture
Design how use, corrections and outcomes improve a product over time.
008 / 100IN THE LAB
Decision-Ready Dashboard
Turn information displays into an actual accountable decision path.
009 / 100IN THE LAB
Place-Sensitive Technology Readiness
Test whether a technology can work in a particular place before assuming transferability.
010 / 100IN THE LAB
Give the Idea a Skeleton
Turn ambiguous concepts into validated entities, fields, relationships, constraints and source rules.
Actors, consequences, workflow & accountability
10 SHOWN011 / 100IN THE LAB
Entity / Ownership Resolution X-Ray
Determine when records refer to the same person, organization, product, policy, owner or relationship.
012 / 100IN THE LAB
AI Use Consequence & Control Mapper
Classify an AI use by consequence and generate proportionate control architecture.
013 / 100IN THE LAB
AI Workflow Consequence Scanner
Show where consequential risk enters and propagates through a real AI workflow.
014 / 100FEATURED · IN THE LAB
Legal Judgment Architecture
Separate research, interpretation, inference, strategy, approval and attorney-only judgment in legal work.
015 / 100IN THE LAB
Repeated Legal Task → Product Engine
Find which recurring supervised legal tasks can safely become reusable products or systems.
016 / 100IN THE LAB
Legal Workflow Mapping
Map actors, documents, authorities, handoffs, deadlines, decisions, risks and records across legal work.
017 / 100IN THE LAB
Regulated-Market Handoff Mapper
Find where responsibility, evidence, consent and accountability disappear between organizations.
018 / 100IN THE LAB
Institutional Friction Detector
Find bottlenecks, dead ends, repeated loops and avoidable burden inside institutional processes.
019 / 100IN THE LAB
Consequence-Aware Escalation Router
Route meaningful events to the right person, urgency, channel and next step.
020 / 100IN THE LAB
Decision Evidence Ledger
Reconstruct who decided what, when, from which evidence, with what result.
Access, data, privacy & inclusive systems
10 SHOWN021 / 100IN THE LAB
AI Vendor Claim / Procurement X-Ray
Test whether an AI vendor’s promises, evidence, controls and procurement answers are actually defensible.
022 / 100IN THE LAB
Human Consequence Map for AI Workflows
Show who can be affected by an AI workflow and how consequences travel to them.
023 / 100IN THE LAB
Consent & Data Rights Manager
Let people understand and control consent, access, correction, deletion, retention and downstream use.
024 / 100IN THE LAB
Data Minimization X-Ray
Determine which data a product truly needs and what can be removed.
025 / 100IN THE LAB
AI Implementation Readiness X-Ray
Test whether an organization can actually implement an AI use safely and operationally.
026 / 100IN THE LAB
Messy Data Trust X-Ray
Show what happened to messy data before anyone relies on it.
027 / 100IN THE LAB
Creator Ownership Stack Mapper
Show what a creator or founder owns, rents, depends on, licenses or could lose across platforms and assets.
028 / 100IN THE LAB
Finding Is Part of Knowing
Search a corpus by keyword, meaning, facets and evidence relevance without hiding ranking logic.
029 / 100IN THE LAB
Change & Consequence Explorer
Show what changed between versions and what downstream records or decisions are affected.
030 / 100IN THE LAB
Inclusive Experience Simulator & Repair Lab
Experience and repair an interface under different access, device, bandwidth, motion, color, language and cognitive conditions.
Evidence, reliability & AI behavior
10 SHOWN031 / 100IN THE LAB
Privacy-Conscious Product Behavior X-Ray
Decide what a product really needs to measure and what its telemetry reveals about people.
032 / 100IN THE LAB
Consequential AI Release Readiness Harness
Decide whether an AI-assisted system is ready for consequential real-world use.
033 / 100IN THE LAB
Adversarial System Explorer
Explore how a system could be misused, manipulated, broken or exploited—and what blocks those paths.
034 / 100IN THE LAB
AI Failure & Incident Reconstruction Lab
Reconstruct what happened when an AI-assisted system failed and test prevention or recovery.
035 / 100IN THE LAB
Data Exit & Portability Test
Test whether exported data is complete, readable, reusable and actually movable elsewhere.
036 / 100IN THE LAB
Resilience Mode / Offline Survival Test
Show what still works when internet, cloud or upstream services disappear.
037 / 100IN THE LAB
Feedback → Change Governance Lab
Show what happens after someone reports that a system is wrong or harmful.
038 / 100FEATURED · IN THE LAB
Domain AI Evaluation Studio
Define what “good AI” means for a specific task and consequence—not one headline score.
039 / 100IN THE LAB
Agent Work Trace Inspector
Audit whether an AI agent actually did the job well, not just produced a convincing answer.
040 / 100IN THE LAB
AI Stop / Escalate Engine
Test whether an AI knows when to continue, ask, abstain, fall back, escalate or stop.
Organizations, regulation, place & embodied experience
10 SHOWN041 / 100IN THE LAB
Who Owns the AI Work?
Show who is responsible for each AI tool, decision, vendor and workflow inside an organization.
042 / 100IN THE LAB
Give the AI a Real Job
Define an AI agent’s role, tools, boundaries, review points and stop conditions.
043 / 100IN THE LAB
Design an AI Team
Split complex work across specialized AI agents and people without losing control between them.
044 / 100IN THE LAB
Reuse the Parts That Regulation Keeps Requiring
Turn recurring approvals, consent, evidence, disclosures and records into reusable regulated components.
045 / 100IN THE LAB
Cannabis Care Access Journey
Show what a person must actually do, understand, pay for, travel through and overcome to access cannabis care.
046 / 100IN THE LAB
What Does This Island Depend On?
Reveal the external and local systems keeping island essentials working and what happens when one fails.
047 / 100IN THE LAB
Will This Work Here?
Test whether a policy, technology, service or program can actually work in a specific place.
048 / 100IN THE LAB
What Does This Rule Feel Like in Real Life?
Compare what a rule says with what people actually experience navigating it.
049 / 100IN THE LAB
What Works for You?
Build a private sensory and context profile from preferences, sensitivities, goals and past responses.
050 / 100IN THE LAB
Environment Assumption & Tradeoff Explorer
Make environmental assumptions, modeled tradeoffs and unknowns visible without treating a fictional room model as evidence or prescription.
Learning, adaptation, provenance & rights
10 SHOWN051 / 100IN THE LAB
Adaptive Cannabis Source Navigator
Route a fictional learner’s topic to dated authoritative sources while stopping before individualized health or legal advice.
052 / 100IN THE LAB
Synthetic Cannabis Comparison Literacy
Compare fictional product fields while preserving missing identity, composition, quality, effect, safety and legal evidence.
053 / 100IN THE LAB
Run a Tiny Experiment on Your Own Environment
Run a careful N-of-1 experiment on light, sound, layout, nature or other environmental factors.
054 / 100IN THE LAB
Make the Space Adapt to the Person
Generate explainable environmental configurations based on person, task, context and constraints.
055 / 100FEATURED · IN THE LAB
Let the Smart Home Explain Itself
Let a smart environment act while preserving explanation, authorization, override and recovery.
056 / 100IN THE LAB
What Do You Actually Own That Others Cannot Easily Copy?
Map the real defensibility of data, rights, relationships, workflows, trust, knowledge and feedback.
057 / 100IN THE LAB
Show Me Where This Content Came From
Trace a finished content object through sources, people, tools, AI involvement, rights and versions.
058 / 100IN THE LAB
Trace a Claim All the Way Back
Follow a factual claim to exact evidence, source, authority, date or version and verification state.
059 / 100IN THE LAB
Is This Legal Citation Real, Current, and Saying What the AI Claims?
Verify existence, proposition, jurisdiction, current status and treatment of a legal citation.
060 / 100IN THE LAB
Catch the IP You Create Before It Disappears Into the Workday
Identify and route potentially valuable brand, invention, creative, method, data and confidential know-how artifacts.
Durable memory & context
10 SHOWN061 / 100IN THE LAB
Why Did We Decide That?
Recover evidence, assumptions, alternatives, dissent and outcomes behind an important decision.
062 / 100IN THE LAB
The Interview Is More Than a Transcript
Turn interviews into people, claims, themes, evidence, contradictions and follow-up questions.
063 / 100IN THE LAB
Research That Stays Alive
Keep questions, sources, claims, gaps, updates and outputs connected as evidence changes.
064 / 100IN THE LAB
An Industry With Amnesia
Recover cannabis policy, legal, clinical, market and community memory across cycles.
065 / 100IN THE LAB
Fictional Cross-Setting Pathway Rehearsal
Rehearse a fixed fictional cross-setting administrative workflow. Its declared permission, record-sharing, acceptance, follow-through and outside-scope fields are fixture states only—not a trial, licensed-care workflow, peer-support protocol or real service.
066 / 100IN THE LAB
What Does the Legal Team Already Know?
Reuse prior matters, authorities, arguments, outcomes and lessons without violating confidentiality boundaries.
067 / 100IN THE LAB
What Should Your AI Know About You?
Let a person control what AI may know, infer, remember, share and forget.
068 / 100FEATURED · IN THE LAB
Let Your AI Act—Without Giving It Your Life
Let personal AI take bounded, previewable, reversible actions with explicit approvals.
069 / 100IN THE LAB
A Law Passed. Now What?
Track whether enacted law becomes real through rules, money, people, systems, contracts and delivery.
070 / 100IN THE LAB
Legalization Is a Lifecycle
Use a fixed fictional lifecycle to examine reform stages, blockers and unknowns without describing a real law, jurisdiction, implementation or outcome.
Shared decisions, comparison, consequences & evidence navigation
10 SHOWN071 / 100FEATURED · IN THE LAB
Fictional Medical-Cannabis Access Gates
Use invented records to examine separate gates between policy status and modeled access—without describing a real program, person or outcome.
072 / 100IN THE LAB
Fictional Island Access Comparison
Compare invented island scenarios to examine how modeled constraints can change an access path; no real island or community is represented.
073 / 100IN THE LAB
Access for Whom?
Use invented service scenarios to examine cost, geography, eligibility, disability, language and workforce as separate modeled access constraints; no real access finding or improvement is claimed.
074 / 100IN THE LAB
Is the System Actually Ready?
Compare fictional jurisdiction records on implementation-maturity fields without describing actual readiness, law, delivery or outcomes.
075 / 100IN THE LAB
Same Goal, Different Regulatory Machine
Compare invented governance designs that pursue a similar fictional goal; no real jurisdiction, policy effect or preferred regulatory model is claimed.
076 / 100IN THE LAB
What Is Actually Different Between These Laws?
Ask a bounded question across invented legal records and inspect source/provenance fields; this fixture does not state current law or provide legal advice.
077 / 100IN THE LAB
What Does This Change Actually Do?
Trace a fictional policy change through modeled actors, obligations, dates, risks and systems; no real legal consequence or deadline is represented.
078 / 100IN THE LAB
Translate the Evidence Without Breaking It
Translate fixed synthetic evidence records for different audiences while preserving uncertainty; no cannabis health finding or evidence-quality conclusion is made.
079 / 100IN THE LAB
Find the Psychedelic Evidence That Actually Answers Your Question
Match fixed fictional psychedelic-evidence records to a question, population, context and outcome; no clinical finding, recommendation or applicability conclusion is made.
080 / 100IN THE LAB
Turn Reporting Into Public Infrastructure
Rehearse how invented reporting, interview and record packets could become maintained public artifacts; no real source, right, clearance or publication outcome is represented.
Audiences, creators, relationships & operating intelligence
10 SHOWN081 / 100IN THE LAB
What Might People Be Struggling With?
Convert invented conversation records into bounded, reviewable unmet-need hypotheses—not verified needs, demand, trends or priorities.
082 / 100IN THE LAB
How Does This Audience Actually Think?
Map fixed synthetic audience contexts, language and trust hypotheses without inferring real identities, traits, preferences or behavior.
083 / 100IN THE LAB
Turn Real Work Into Public Proof Without Leaking the Work
Apply publication gates to invented work packets while keeping confidentiality, rights and clearance as unresolved human decisions; no real proof or safe-publication outcome is claimed.
084 / 100FEATURED · IN THE LAB
Who Created the Value—and Who Gets It?
Trace invented contribution, knowledge, agreement and benefit fields without determining real ownership, entitlement, rights or community authority.
085 / 100IN THE LAB
Who Is Shaping This Decision?
Map source-linked relationships in a fixed fictional decision network without accusation, causal inference or a claim about real influence.
086 / 100IN THE LAB
Use the Post as a Prototype
Use synthetic publishing signals to choose a bounded next research step; attention is not demand, validation, product evidence or a launch decision.
087 / 100IN THE LAB
Build Your Own Media System
Rehearse a fictional media workflow across research, rights, versions, publishing and reuse; no real permission, platform result or audience outcome is represented.
088 / 100IN THE LAB
Your Network Is Not a Contact List
Inspect fictional relationship records, commitments and open loops without scoring a real person or predicting response, revenue or conversion.
089 / 100IN THE LAB
Stop Being the Only Database in Your Company
Model a fictional founder operating-intelligence packet; priorities and risks are fixture bands, not advice, forecasts, ownership findings or business outcomes.
090 / 100IN THE LAB
Build a Research Team of AI Agents That Can Show Their Work
Rehearse a frozen research-agent workflow with synthetic citations and no live agents, browsing, tools, autonomous truth-finding or external effect.
Governed agents, ecosystems & convergence
10 SHOWN091 / 100IN THE LAB
What Is This AI Allowed to Remember?
Test local fictional memory permissions and a local forget receipt; the fixture does not prove deletion elsewhere, GDPR compliance or a universal right.
092 / 100IN THE LAB
Rehearse Work Across People, AI and Software
Model simulated people, tools, agents, approvals and exceptions across a frozen workflow with no live system, delivery or external effect.
093 / 100IN THE LAB
Fictional Regulated-Workflow Rehearsal
Test invented rules, states, approvals, fixture evidence, deadlines and handoffs without claiming compliance or completing real regulated work.
094 / 100IN THE LAB
Inspect a Fictional Evidence Chain
Reconstruct an invented evidence chain without calling the result an audit, proof, defensible compliance record or certification; legacy B copy remains under review.
095 / 100IN THE LAB
Institutional Conditions Observatory
Examine fictional institutional conditions and reported experience while preserving population limits, uncertainty and association—not causation; legacy B claims remain under review.
096 / 100IN THE LAB
Learn From Cannabis Experience Without Reducing People to Labels
Inspect fixed synthetic longitudinal records across composition, person, context and time without producing clinical evidence, a health inference or product advice.
097 / 100IN THE LAB
Personalization You Can See and Control
Test user-controlled adaptation from explicit fictional context while exposing every input and off switch; no physiology, trauma, disability, emotion or mental state is inferred.
098 / 100IN THE LAB
Psychedelic Administrative Handoff Rehearsal
Inspect fictional administrative records across education, preparation, care context, integration, referral and follow-up without delivering care or claiming safety.
099 / 100IN THE LAB
Fictional Archipelago Data Commons
Test invented capacity, dependency, asset, provenance and permission metadata without representing real authority, consent, ownership or sovereignty; legacy place-language remains under review.
100 / 100FEATURED · IN THE LAB
Island Resilience Scenario & Decision Room
Model a synthetic island shock, cascading consequences, interventions and tradeoffs as a planning rehearsal—not a forecast, emergency instruction or outcome claim.