$REGEN Tokenomics WG

[Max_Semenchuk]

Weekly Tokenomics Call #51 Summary - Final Session of 2024

Hey Regen community!

We wrapped up our final tokenomics call of 2024 with some excellent discussions about the path forward. Here’s a comprehensive summary of what we covered:

CoinMarketCap Data Accuracy Project

One of the immediate action items discussed was fixing CoinMarketCap’s inaccurate data for $REGEN:

• Current issues: Incorrect supply data and outdated bridge contract addresses
• What’s being done: Submitting correct Axelar contract addresses and transparent supply metrics
• Challenge: The submission form is complex and requires precise data about circulating vs. total supply
• Data source: MintScan shows 220M total supply and is the only platform actually pulling real-time chain data

The team discussed the distinction between total supply and circulating supply, with proper accounting for reserve wallets (like the Regen Foundation wallet) that should be excluded from circulating figures.

Buy & Burn Automation Discussion

This was a major topic with lots of community input:

The Core Challenge: Most eco-credit sales happen off-chain through traditional payment methods (bank transfers, credit cards, checks), but burn mechanisms need on-chain execution. This creates a technical and process challenge for full automation.

Gregory’s Perspective: Focus should be on quarterly accounting and manual burns initially rather than rushing to build complex automation. His key point: “Generate credit demand & supply – that’s where we have real agency.” Development resources are better spent on credit provisioning and registry operations that drive actual revenue.

Lance’s Proposal: Build a user-friendly interface where credit sellers can:

1. Connect their wallet
2. Execute burn commitments voluntarily
3. Build on-chain reputation through transparent proof
4. Create social accountability (“carrots not sticks” approach)

Technical Reality:

• On-chain automation is only possible for fully on-chain transactions
• Off-chain sales will always require some manual process (like quarterly accounting)
• This isn’t a bug, it’s a feature - it requires good faith from participants who care about long-term token health
• Similar to NFT royalties, this can’t be deterministically enforced

Token Health: Current State Analysis

Brandon provided a frank assessment of current token dynamics:

The Math:

• Market cap: ~$700-800K
• Staking yield: 16%
• Annual sell pressure from staking: ~$80K
• Current liquidity: ~$40K

The Challenge: With limited liquidity and no new buyers (mostly arbitrage traders and sellers), the current staking inflation rate creates downward pressure.

Recent Price Action: 50% drop in recent days attributed to:

• Liquidity providers unstaking from the Base pool
• Selling into the deepest liquidity pools
• Pool had dropped from $92K to lower levels, creating a key turning point

The Solution: EcoCredit buy & burn program must offset staking rate inflation until:

1. Klima partnership drives consistent credit sales
2. External market enters with new demand
3. Network visualization improves to show value proposition

Path Forward: 2026 Priorities

The community identified clear priorities for the new year:

1. Better Network Visualization

• Current lack of clear public-facing metrics hurts investor confidence
• Need dashboards that show network activity and value

2. Supply Cap Proposal (Regen Token 2.0)

• Max’s governance proposal for capping supply
• Dynamic mint/burn logic
• This will take a few months to spec out properly and get community input

3. Automated Burns for On-Chain Sales

• Build the automation for on-chain credit sales first
• Manual/quarterly accounting for off-chain sales
• Focus on getting the tokenomics fundamentals right

4. Klima Partnership

• Key driver of credit demand
• “If we have consistent revenue stream, everything else gets easier”

5. AI-Assisted Development

• New tools (Regen ChatGPT, MCP servers, Claude Code) making complex workflows more accessible
• Community members like Brandon exploring “vibe coding” solutions
• By the time tokenomics 2.0 is designed, AI tools may make implementation much easier

Key Philosophical Insight

On Enforcement vs. Community Trust:

The group reached an important realization: Buy & burn mechanisms can’t be deterministically enforced on-chain the way gas fees can be. This approach requires:

• Good faith from credit sellers
• Prioritizing long-term token health over short-term 1-3% burn savings
• Social accountability and reputation
• Aligned incentives rather than forced compliance

As Gregory noted, this was part of the original governance proposal and game theory design. It’s about building a community of aligned participants rather than trying to enforce everything through code.

Notable Quotes

“Generate demand for credits, generate supply for credits – that’s where we have real agency” - @Gregory_Regen

“We need buyers, not just arbitrage traders” - @brawlaphant

Resources

Full Recording & Detailed Notes: CoinMarketCap Updates, Buy & Burn Automation, and Token Health Discussion

That’s a wrap for 2024 tokenomics calls! Thanks to everyone who participated throughout the year. These weekly discussions continue to be valuable for working through complex token design challenges together.

Happy holidays everyone! See you in January 2025!

[Max_Semenchuk]

AI-Powered Development & Infrastructure Evolution | Weekly Meetup #3 Summary

Summary

This week’s Regen Tokenomics community call explored AI-driven development workflows, upcoming IBC2 integration, institutional participation pathways, and ETH Denver hackathon planning. Key themes included accelerated development cycles through AI tooling, knowledge graph infrastructure, and the convergence of user experience across roles.

Full Recording & Transcript: AI-Powered Development & Infrastructure Evolution

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Key Discussions

1. AI Development Revolution

Brandon has been experimenting with “vibe-coding” using GPT and Claude to generate GitHub repositories and forum posts for infrastructure upgrades. This approach has demonstrated the potential for AI-assisted development in the Regen ecosystem.

Gregory Landua noted that with proper AI agent integration and light PR review processes, the community could potentially ship on-chain features more rapidly than traditional development workflows allow.

Implications:

• Reduced development cycle times
• Lower barriers to contribution
• Enhanced documentation generation
• Potential for distributed, asynchronous feature development

2. KOI Knowledge System

Regen’s KOI (Knowledge Ontology Integration) system represents a significant infrastructure advancement. The system integrates more than 10 codebases as knowledge graphs using Abstract Syntax Trees (AST).

Technical approach:

• Each function, class, and module becomes a queryable node
• AI can synthesize across ledger data, documentation, and code
• Enables complex cross-repository queries and analysis

Try it: Regen KOI GPT

3. IBC2 Integration

Timeline: Approximately 2 weeks until release with Cosmos SDK 0.53

Key capability: IBC2 enables Ethereum addresses to control Regen addresses and execute CosmWasm contracts on Regen Ledger from Base or other EVM chains.

Technical implications:

• Cross-chain contract execution
• Unified address space across heterogeneous chains
• Reduced friction for EVM-native users
• New composability patterns between Cosmos and Ethereum ecosystems

This represents a significant step toward dissolving traditional blockchain boundaries.

4. User Experience Convergence

The UX Convergence Workstream has identified 12 core user roles within the Regen ecosystem. The strategic vision involves converging all user journeys into unified interfaces where participants can fluidly move between multiple roles.

Design philosophy: Rather than building discrete products, the focus is on creating regenerative civic infrastructure that supports diverse participation patterns.

Related discussion: Regen Network UX Convergence Workstream

5. Institutional Pathways

Three distinct participation models are emerging for institutional actors:

1. Public Network Attestations

   • Institutions attest on Ethereum or other public networks
   • Minimal infrastructure requirements
   • Leverages existing public blockchain legitimacy

2. Direct Validator Participation

   • Institutions run validators on Regen Ledger
   • Full participation in consensus and governance
   • Higher technical commitment

3. Custom Consortium Chains

   • Institutions deploy their own chains using Regen’s tech stack
   • Maximum control and customization
   • Can bridge to Regen Ledger via IBC

This flexibility allows institutions to choose participation models aligned with their technical capacity, regulatory constraints, and strategic objectives.

6. ETH Denver Hackathon Vision

Planning is underway for a potential hackathon that combines:

• Regen Builder Lab participants
• Community staking participants
• In-person ETH Denver attendees
• Remote participants (distributed collaboration)

Objective: Utilize Regen AI tools to “vibe-code” solutions and ship features on-chain during concentrated development sprints.

This represents an experiment in AI-augmented, distributed, synchronous development.

7. Recursive Learning & Knowledge Management

Gregory Landua emphasized the importance of knowledge capture:

“Even if we fail to accomplish something, as long as we do good knowledge management, we’ll upgrade our community capacity significantly.”

Key insight: Each development attempt—successful or not—builds context for subsequent iterations. Intelligence and capability compound over time through systematic knowledge capture.

This aligns with the broader strategy of maintaining complex holistic infrastructure while creating simplicity through focused application logic.

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Closing Reflection

“We’re in a race between infrastructure and user experience—what’s the distance between the idea and the ability to test it?”

The core tension in Regen’s current development phase involves compressing the gap between concept and deployment. AI tooling, knowledge graphs, and cross-chain interoperability all serve this objective: reducing friction in the path from idea to testable implementation.

[Max_Semenchuk]

Following up on our last call to align context.

During the meeting, @cpt_grog suggested focusing this quarter on a fixed cap / dynamic supply approach (i.e. stopping broad inflation and tying any new distribution to real network revenue and quarterly contributions). I initially expanded this framing a bit — not only as a supply mechanic, but as a way to solve concrete coordination and treasury sustainability problems: how we avoid draining the treasury while still creating conditions for meaningful scarcity and long-term alignment.

Thinking more about it after the call, it became clear to me that before implementing any specific tokenomic changes, we actually need a clear, testable coordination hypothesis. Otherwise we risk tweaking mechanisms without being explicit about who exactly we are coordinating, for what purpose, and under what conditions.

Proposed focus for Q1:

Treat Q1 as an explicit exploration phase to test a single hypothesis:

The $Regen token should function primarily as a mechanism of responsibility and conditional access for a limited set of committed contributors and regional partners — not as a generic inflationary reward — with dynamic distribution strictly constrained by real network revenue.

What this would mean in practice for Q1 (no hard implementation yet):

• Formulate the hypothesis clearly and align between ourselves (scope, assumptions, limits — including holder concentration and governance realities).

• Explore 1–2 concrete mechanism options that fit a fixed cap / revenue-bounded model.

• Stress-test these options with core contributors, Foundation, and a small number of regions.

• Produce a clear recommendation by the end of the quarter: proceed, adjust, or stop.

The intended output of Q1 is clarity and decision-readiness, not immediate rollout. A “no-go” conclusion would still be a valid outcome if the hypothesis doesn’t hold under scrutiny.

Happy to iterate on this framing, but this seems like a coherent way to connect the fixed cap / dynamic supply idea with our actual coordination and sustainability challenges.

[Max_Semenchuk]

Tokenomics Working Group – Weekly Recap (Jan 27, 2026)

Economic Logic Sprint & AI Integration

This week’s session focused on formalizing REGEN’s economic logic with the goal of presenting a complete proposal to the community by end of Q1. Key themes included balancing investor appeal with coordination utility, proof of authority transitions, and leveraging the new AI tooling for economic modeling.

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Key Discussion Points

1. Core Economic Thesis

The group debated the fundamental positioning of the REGEN token. A working thesis emerged:

“The $REGEN token should function primarily as a mechanism of responsibility and conditional access for a limited set of committed contributors and regional partners — with dynamic distribution strictly constrained by real network revenue.”

This positions REGEN as a coordination tool first, with investment upside as a consequence of sound economic logic rather than speculative dynamics.

2. Fixed Supply Cap & Dynamic Mint/Burn

Continuing from previous sessions, we discussed tying token issuance directly to ecological value creation (eco-credit sales). The goal: create clear, modelable relationships between network growth and token value.

James proposed framing this for investors: “If 5% of the carbon/biodiversity market flows through Regen, here’s what that means for the token over 1, 2, 5 years.”

3. Proof of Authority Transition

The validator set is currently unstable (sometimes dropping below 21 active validators), and all validators are operating at a loss — they participate for mission alignment, not profit.

Options discussed:

• Full PoA with validator allowlist
• Permissionless but zero security emissions
• Gradual emission reduction to minimize system shock

Gregory noted that PoA has been socialized with validators ~18 months ago, so this isn’t new to the community.

4. AI Tooling Integration

The Regen AI infrastructure is now live and ready for use:

• MCP servers for querying the ledger
• Agent frameworks for building ecological AI tools
• Vibe coding capabilities for rapid prototyping

Will proposed exploring a merger or closer collaboration between the Tokenomics and AI working groups, potentially through shared hackathon/co-working sessions.

5. Quick Win: Eco-Credit TVL Dashboard

Brandon is developing a dashboard to display the cash value of credits on the ledger. Gregory’s “State of Regen 2025” post contains inferred prices for all credit classes that can be used as baseline data.

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Action Items

1. Max: Draft economic logic equation/simulation for review
2. Brandon: Continue TVL dashboard development using price inference from 2025 state post
3. All: Consider hackathon format for collaborative building

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Resources

• Recording & Notes: Economic Logic Sprint & AI Integration
• Regen AI Setup Guide: Connecting to Regen AI
• MCP Repository: GitHub - Regen KOI MCP

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Quote of the Week

“The token is not a thing in itself. It’s a tool of coordination.” — Max Semenchuk

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We welcome feedback and participation. See you next week!

[brawlaphant]

Global Assumptions

Variable	Description
Period	Modeling period
Vₜ	Total ecocredit transaction value (USD)
f	Registry fee rate (%)
η	USD → REGEN burn conversion rate
C	Fixed supply cap (REGEN)
r	Regrowth rate
δ	Emissions per USD revenue

---

Revenue Allocation

Variable	Formula	Constraint
Rₜ	Vₜ × f	Total registry revenue
α	Input	Validator allocation
β	Input	Community pool allocation
γ	Input	Burn allocation
Check	α + β + γ	Must equal 1

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Validator Economics

Variable	Formula
N	Validator count
Cᵥ	USD cost per validator per period
Rᵥ	α × Rₜ
Cost	N × Cᵥ
Surplus	Rᵥ − Cost

Feasibility condition:

Surplus ≥ 0

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Supply Dynamics

Variable	Formula
Sₜ	Current supply
Eₜ	MIN(r × (C − Sₜ), δ × Rₜ)
Bₜ	γ × Rₜ × η
Sₜ₊₁	Sₜ + Eₜ − Bₜ

Deflation condition:

Bₜ > Eₜ

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Community Pool Distribution

Variable	Formula
Pᵢ	Points per participant
ΣP	Σ Pᵢ
Dᵢ	β × Rₜ × (Pᵢ / ΣP)

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Required Tests

• Validator sustainability under revenue variance
• Allocation sensitivity (α, β, γ)
• Emissions vs burn equilibrium
• Fixed cap effects on liquidity and scarcity
• Community incentive behavior

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One-line framing

“This is the minimum economic model required to test validator sustainability, supply dynamics, and burn/emission balance. Provide inputs, run the math, and show where it fails.”

[Max_Semenchuk]

thanks, writing an AI proposed comparison of models:

Core Difference

Brandon Model: How to distribute revenue (α to validators, β to community, γ to burns)

Max Model: How to generate revenue in the first place (see Regen Network Token Model Comparison)

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The Gap in Brandon’s Model

Brandon’s model takes Vt (transaction volume) as a given input. But generating Vt is the actual problem.

Max model shows the flywheel:

Sales spend → More buyers → Vt grows → Fee grows → More sales spend

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Side by Side

	Brandon Model	Max Model
Question	How to split the pie?	How to grow the pie?
Revenue	Assumed	Generated via flywheel
Token role	Rewards + burns	Governance over spending
Success metric	Deflation (Bt > Et)	Self-sufficiency

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How They Fit Together

1. Max model generates growing Vt
2. Brandon model distributes Rt = Vt × f

They’re complementary layers, not competing approaches.

[Gregory_Regen (Gregory Landua)]

[RFC] Network Coordination Architecture: A Unified Path Forward

Category: Governance
Tags: coordination-infrastructure, network-upgrade, economic-reboot

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Summary

This post synthesizes recent work from the Token Economics Working Group (see Weekly Recap, Jan 27), Christian’s Comprehensive Proposal, Max’s Model Comparison, and the Economic Reboot Roadmap.

The working group has been developing these ideas through weekly sessions over the past two years. The Jan 27 session focused specifically on formalizing the economic logic and integrating AI-assisted modeling tools. This synthesis reflects the forward-moving consensus from that session.

Key finding: The community proposals are complementary, not competing. They address different layers of the same coordination challenge.

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Context: What Problem Are We Solving?

The current network architecture was inherited from standard Cosmos SDK design. It works, but it wasn’t built for what Regen actually does—verifying and tracking ecological outcomes at scale.

Three structural mismatches have become clear:

1. Security model mismatch: Network security currently depends on token price. When prices are low, the cost to disrupt the network drops. This creates vulnerability precisely when the network needs stability most.

2. Incentive mismatch: Block rewards flow to capital holders regardless of their contribution to the network’s core function. Someone holding tokens passively receives the same rewards-per-stake as someone actively building verification infrastructure.

3. Value capture mismatch: Transaction fees are flat and disconnected from the economic value of credits being verified. A $10 credit and a $10,000 credit pay the same gas fee.

The proposals address all three.

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The Emerging Consensus

After two years of working group deliberation, five areas show strong alignment:

Area	Status	What It Means
Authority-based consensus	Consensus	Validator selection based on demonstrated contribution, not token holdings
Fee-based value capture	Consensus	Percentage of credit transaction value, not flat gas fees
Activity-based rewards	Consensus	Network rewards flow to participants creating verifiable outcomes
Supply discipline	Consensus	Fixed cap with programmatic supply reduction tied to credit activity
Community Pool distribution	Consensus	Central coordination point for directing resources to contributors

This represents a shift from capital-weighted security to contribution-weighted coordination.

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How the Proposals Fit Together

Each proposal addresses a different layer. Together they form a coherent stack:

┌─────────────────────────────────────────────────────────────┐
│  DECISION-MAKING LAYER                                       │
│  Authority validators: Infrastructure builders + Trusted     │
│  partners + Data verification organizations                  │
│  Constitutional framework + Forum-first deliberation         │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│  VALUE CAPTURE LAYER                                         │
│  Registry fees (% of credit value) directed to:             │
│  ├── Supply reduction (25-35%)                              │
│  ├── Validator compensation (15-25%)                        │
│  └── Community coordination pool (50-60%)                   │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│  DISTRIBUTION LAYER                                          │
│  Community Pool circulates to:                               │
│  ├── Credit purchasers/retirers (contribution tracking)     │
│  ├── Platforms enabling transactions (facilitation credit)  │
│  └── Long-term coordinated holders (optional stability tier)|
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│  IMPLEMENTATION LAYER                                        │
│  Coordinated via Economic Reboot Workstreams (WS0-WS5)      │
│  AI-assisted modeling for parameter calibration              │
└─────────────────────────────────────────────────────────────┘

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What Each Proposal Contributes

Christian’s Proposal: Decision-Making Infrastructure

Establishes who makes decisions and how authority is earned:

Authority Validator Categories:

• Infrastructure builders — Organizations actively developing verification systems, methodology frameworks, and monitoring tools. Their stake is their ongoing work.
• Trusted network partners — Established organizations (ReFiDAO, Toucan, Kolektivo, others) with demonstrated commitment to ecological verification infrastructure.
• Data verification organizations — Entities responsible for attesting to data quality. Direct accountability for credit integrity makes them natural guardians of network consensus.

Contribution Tracking:

• Purchasers and retirers of credits earn proportional credit for directing resources toward ecological outcomes
• Platforms facilitating transactions earn credit for enabling coordination
• All new token circulation flows through the Community Pool before distribution

Max’s Proposal: Coordination Parameters

Provides specific ratios and mechanisms:

• 65-75% / 25-35% split: Transaction value flows primarily to ecological activity, with infrastructure maintenance funded from the remainder
• Fee-weighted participation: Decision-making influence proportional to contribution, not just holdings
• Stability mechanism: 6% annual return for participants who commit to coordinated long-term holding, reducing volatility while maintaining liquidity

Brandon’s Roadmap: Implementation Structure

Organizes execution into coordinated workstreams:

Workstream	Focus	Deliverable
WS0	Core Infrastructure	Authority migration framework
WS1	Incentive Design	Supply reduction modeling
WS2	Decision-Making	Constitutional framework
WS3	Registry Integration	Fee architecture
WS4	Coordination Mechanisms	Contribution tracking system
WS5	Transition Communication	Stakeholder migration support

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Token Economics Working Group Context

The Jan 27 session (documented in Post #64) focused on:

1. Economic Logic Sprint — Formalizing the mathematical relationships between fees, supply reduction, and distribution
2. AI Integration — Using modeling tools to test parameter sensitivity before committing to specific values
3. Synthesis work — Christian’s comprehensive proposal emerged from this session, integrating forum discussions and prior WG sessions

The working group has been meeting weekly since August 2023. This synthesis reflects accumulated deliberation, not a single proposal.

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Complementary Mechanisms

The proposals don’t compete—they solve different problems:

Activity Tracking + Stability Tier

Mechanism	Serves	Function
Contribution tracking	Active participants	Rewards transaction volume and facilitation
Stability tier	Long-term holders	Provides predictable return for coordinated commitment

Recommendation: Implement both. Contribution tracking for active participants, stability tier as optional layer for those providing long-term liquidity.

Fee Split + Distribution Ratios

Christian’s proposal defines destinations; Max’s provides starting percentages:

Destination	Function	Starting Range
Supply reduction	Creates scarcity tied to ecological activity	25-35%
Validator fund	Compensates authority validators	15-25%
Community Pool	Distributes to contributors	50-60%

Note: Exact percentages require modeling. These ranges establish starting points for deliberation.

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What Still Needs Work

Modeling Required

Before parameters can be finalized:

1. Supply cap specification — Neither proposal specifies the cap value. This number shapes all downstream calculations.

2. Equilibrium analysis — At what fee percentage and transaction volume does supply reduction exceed new circulation? This threshold determines long-term supply dynamics.

3. Fee sensitivity — How do different fee levels affect credit market competitiveness? The network competes with traditional registries and other verification platforms.

Governance Questions

1. Validator set size: How many authority validators? (Working assumption: 15-21)
2. Category balance: What ratio of builders / partners / data organizations? (Working assumption: minimum 5 each)
3. Trust criteria: What defines “trusted” partner status? Requires explicit criteria.
4. Term structure: How long do validators serve before rotation? (Working assumption: 1 year terms)

Transition Questions

1. Current staker migration: How do existing stakers transition to the new model?
2. Validator conversion: What support for existing validators adapting to new requirements?
3. Timeline: What pace minimizes disruption while maintaining momentum?

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Implementation Sequence

Phase	Focus	Timeline	Dependencies
1	Decision-making framework	Current	None
2	Economic modeling	Q1 2026	Supply cap specification
3	Technical implementation	Q2 2026	Modeling complete
4	Network integration	Q3 2026	Phase 3 complete

From Christian’s proposal: “The decision-making restructuring can and should proceed while modeling continues—the two workstreams are complementary but not dependent.”

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Call to Action

For Community Members

1. Review the convergence points — do they reflect your understanding of working group discussions?
2. Comment on open questions — especially transition concerns
3. Flag any divergence not captured here

For Token Economics Working Group

1. Prioritize supply cap modeling
2. Develop equilibrium scenarios
3. Produce fee sensitivity analysis

For Technical Contributors

1. Assess authority migration requirements
2. Scope contribution tracking infrastructure
3. Evaluate Community Pool distribution mechanisms

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Source Documents

• Token Economics WG Weekly Recap, Jan 27 — Working group context
• Christian’s Comprehensive Proposal — Decision-making architecture
• Max’s Model Comparison — Coordination parameters
• Economic Reboot Roadmap v0.1 — Implementation structure

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Next Steps

1. Discussion period: 2 weeks for community feedback
2. Modeling sprint: Working group delivers supply cap analysis
3. Framework proposal: Formal RFC for Phase 1 decision-making structure
4. Technical scoping: WS0 produces migration requirements

---

This synthesis emerged from Token Economics Working Group deliberations. Contributors: Christian, Max, Brandon, Gregory, Will, James, and all WG participants.

The proposals described here represent working consensus, not final specifications. Parameter values require modeling and governance approval before implementation.

[RegenChristian]

Thank you, Gregory — this is really helpful. It’s motivating and makes me want to keep the momentum going. I’m going to dig into this more, try to address some of your questions, and surface any additional open ones.

One question that already jumps out for me is this: which of these parameters could be governed in the new model, rather than needing to be perfectly set upfront? Put differently, which pieces require a high degree of certainty before we implement an upgrade, and which can remain adjustable through governance and be safely deferred and addressed later?

[brawlaphant]

Each of us can plug in our own model assumptions and compare outputs.

[baseline] ((https://docs.google.com/spreadsheets/d/1eLDue5NEhCf1uK0PjuJteTCkDM0kQ8e7a25JL14iXHw/edit?usp=sharing))

[Max_Semenchuk]

Regen Network Tokenomics Weekly #7

From Narrative to Executable Infrastructure

This session centered on operationalizing tokenomics through structured coordination and experimentation.

1. Tokenomics Meta-Spec (Agentic Repo)

The GitHub repository is evolving into the canonical coordination layer for REGEN tokenomics:

GitHub - regen-network/agentic-tokenomics: Regen Network Agentic Tokenomics &...

We are inviting structured review:

• Improve clarity and nesting
• Submit PRs and comments
• Assess readiness for adoption as the meta-spec reference

The goal: move from conceptual token design toward a living, version-controlled specification.

2. Net-Net Claw Bot

Priority: deploy a claw-style bot that creates a visible “heartbeat” of contributions.

This includes PR automation, contribution tracking, and agent orchestration.

Tokenomics must become measurable in practice, not just defined in prose.

3. Polymarket AI Experiment

Proposal: build an AI bot to scan Polymarket for high-performing traders and detect potential edges.

Run paper trades for approximately one month to validate signal quality before capital allocation.

Experiment first. Allocate later.

Recording & notes:

Meta-Spec, Agents & Market Signals