🤖 DCP-32: DappRadar DAO's Agentic Vision Proposal

vandynathan · April 25, 2025, 6:27pm

Summary

Welcome to the next Progressive Decentralization Workstream Budget (Q2 +3 2025) Proposal which also outlines our Agentic Vision moving forward.

At DappRadar, we truly believe that agents will be end-game for crypto UX. The ability to delegate access for agents to transact and access dapps, data and assets cross-chain, simply by using plain language, it allows for a massive x10 in crypto UX for everyday users. Over the past several months, DappRadar has made substantial progress in integrating autonomous agents into its ecosystem, ultimately laying the foundation for a robust agentic trust layer. We’ve acted as a trust layer for dapps for the past six years, and by evolving to also being a trust layer for autonomous agents, we will enable secure, transparent interactions and foster a more efficient decentralized ecosystem.

DappRadar’s ongoing partnerships with Binance, OKX, and Cointelegraph will be key to expanding DappLaunch and supporting agent-driven projects and more within the ecosystem. This proposal will take a conservative approach but allow for the DAO to reconsider the budget in the next three months. The goal is to outline the strategic roadmap and budget for the development of this infrastructure, focusing on enhancing the app layer, consolidating our node operations and expanding our support of decentralized agents and more.

Assessment (Q1 and Q2 2025 Progress)

The DappRadar Foundation has made significant strides toward realizing the agentic vision, with notable achievements including:

1. Strategic Vision Alignment

Completed the foundational roadmap for an Agentic Trust Protocol, focusing on community contribution, agentic infrastructure, and staking mechanics.

2. DappLaunch Expansion

Strengthened partnerships with Binance, OKX, and Cointelegraph to expand the DappLaunch network, fostering more decentralized applications and projects.
Developed a comprehensive DappLaunch project pipeline, ensuring smooth integration of new applications into DappRadar’s ecosystem.

3. Community Engagement & Governance

Drafting formal governance frameworks with By-laws to enable transparent decision-making and increased focus on increasing community involvement in the agentic system’s development.
Continued to grow the DAO’s active participation, ensuring ongoing feedback and alignment with the broader community.

4. Finance and Operations Team

Leveraging AI to build out financial reporting using dashboards and KPIs that provide real-time insights and drive better decision making
Develop strategies for managing liquidity and ensure effective treasury management to support the growth and stability
Streamline and improve operational finance

Strategic Vision Moving Forward

The success of this initiative will be measured through the following key performance indicators (KPIs):

1. Building the Trust Layer for Agents

Finalize and launch the Agentic Trust Protocol whitepaper	Publish framework and get initial ecosystem feedback
MVP implementation of agent scoring system	Number of agents scored in alpha version (target: 10+)
Developer & partner adoption	Number of integrated agents/protocols (target: 5 in H2)

2. DappLaunch Growth

Expand pipeline of AI x Web3 projects	Number of projects onboarded (target: supporting 5 projects)
Strategic partnerships activation	Signed BD agreements with Binance, OKX, Cointelegraph

3. Community & Governance Involvement

Finalize and ratify the DAO By-laws	Governance framework adopted by snapshot vote
Launch and onboard the Advisory Board	Advisory Board Blog posted
Improve contributor onboarding & participation	# of active DAO contributors (target: 50+ by Q4)
Governance participation rate	Voter turnout % in governance proposals (target: 5%+)

4. Finance and Operations Team

Define DAO treasury strategy	Published treasury policy incl. allocation & yield plan
Integrate AI Agents into treasury operations	Testing of AI agents to manage treasury ops and/or reporting

Budget Allocation

The proposed budget for this phase of development is as follows:

Category	RADAR	USDC	TOTAL in USD
Core Contributor Fees	660000	112000	113650
Other Operational Costs	0	13800	13800
Community Initiatives	3360000	0	8400
Technology Development	0	8100	8100
TOTAL	4020000	133900	143950

Conclusion

DCP-32 marks an important milestone in DappRadar’s evolution, as it expands its focus beyond traditional apps to embrace the growing agentic ecosystem. By developing the Agentic Trust protocol, scaling the app layer, and expanding DappLaunch with key partners, DappRadar will ensure its leadership in the decentralized and AI-driven future. We look forward to community feedback and refining this proposal to align with the collective vision for DappRadar’s future.

Vote

Accept new Progressive Decentralization Workstream
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0 voters

madeafterdeath · April 27, 2025, 11:12pm

this sounds good cant wait too see the community grow =D

vandynathan · April 28, 2025, 7:39am

Indeed. I think the excitement from a strong and clear vision will create more opportunities for contributions and grow the community - strap in

nederob · April 28, 2025, 8:13am

The proposal is nice, and looking forward to see the results. However, I had to read things 2 or 3 times in order to filter out the essence. I will get to what I mean in a bit. Also, happy to see the KPIs mentioned, think we’re on a good direction.

Purely when it comes to judging the DAO on its performance, I’d like to see things presented as follows:

Current situation A
DAO initiative B to make A better
Required budget for B
Goals for B to improve A
And then in the after math: the actual results.

In short, what do we have, why and how will we improve it, what are the expectations, and then in 3 months check on the actual results.

Yes, I can kinda find this information here… but I am just having some difficulties with the presentation tbh.

madeafterdeath · April 28, 2025, 2:30pm

Totally get what you mean here rob.
I have been asked to ask some questions as well about all this so here goes these might be some tough ones and i don’t know how to explain it all so hopefully someone can jump in who does know what they know.

Integration of autonomous agents that can manage transactions and data across different blockchains using natural language.
Creation of a trust layer: Evaluate and certify agents through a whitepaper and scoring system.
Expansion of DappLaunch: Strengthen alliances with major players to integrate more applications and AI projects.
Community and Governance: Establish formal governance frameworks and rules to involve the community in decision-making and the development of the agents.
Financial and Operational Management: Incorporate AI to improve decision-making, including in treasury management and reporting.
Budget: $143,950 allocated for collaborators, operational costs, initiatives, and technological development.
to me? smoke… not clear enough… what they really building? what’s the goal? why would it benefit dappradar?
mantle built AI agents, they’re ok… for those who dont know where to swap (ridiculous…)
goal? create FOMO i guess…
benefits? not sure… to say something good… i’d prefer AI building reports instead of team, AI tends to be raw, not hiding bad data
User experience: advance users know what they do, doesnt need AI, non-experts doesnt need complex operations. so i dont see the use case.
Automation/Efficiency: AI agents may be better at this topic, but are we firing people from the team cos now we got AI doing their work?
Cross-chain operability: Bridges are dangerous enought to make it even more riskier with AI doing crosschain operations, humans can guess a price oracle is working bad, AI may struggle doing it.
Trust and Security layer: im ok… i trust more robots than humans… but humans are building it… so how we guarantee people wont game the system? bad actors…
just raising some valid concerns… its worth? i dont think so…

(^^^^^ this is from a community member ^^^^^) Be nice if you could answer that.
They also followed it on with questions i should ask so lets go ahead and ask them =D

what u should ask:
user segments benefiting most from AI agents?
natural language interactions will significantly improve UX over existing intuitive interfaces?
more detailed technical specifications for the Agentic Trust Protocol
How will the whitepaper and scoring system be designed to prevent manipulation (audits, security reviews?)
integration with existing systems, especially given the risks already associated with cross-chain bridges?
safeguards will exist if the AI misinterprets data or if a price oracle behaves unexpectedly during cross-chain operations?
any prototypes or early-stage testing data that demonstrate effective performance?
can think on more, but still think its not worth to discuss it… if teams want it, they’ll do it, theres no community

I’m sure there all valid and good questions to ask.

anyways ill leave it at that for now.

Alex-Mammoth · April 30, 2025, 11:58am

As always, madeafterdeath, thank you for your questions. They are crucial

What are we really building, and why?

We’re not just building agents or handing them out. Others are already building agents, and many more will follow. The real question is, what do agents actually need?
They need data. But more importantly, they need trusted data. You can’t just trust any agent or any data source. That’s where DappRadar plays a critical role. Our data is built on open community contribution, strong onchain foundations, brand consistency, and accuracy. That already makes it a trusted layer for users.
Now we’re aiming to extend that trust to agents. Not just by plugging them into data, but by building a system that validates agents themselves. We want to track their behavior, verify their actions, and ensure there are no unexpected failures.
We’re not building an AI hype machine. We’re building infrastructure that lets agents connect to DappRadar the same way dapps/projects/users do today, with a layer of accountability on top.

Let me answer some of your questions to the best of my ability.

“Advanced users don’t need agents, and non-experts will get confused”

That’s exactly the challenge agents aim to solve.
Done right, noobs won’t need to learn how to use DEXs or bridges. They’ll be able to give an agent permission and say something like “buy $XYZ under $10.”
Advanced users, can use agents to automate repetitive tasks, portfolio strategies, and data analysis.

“What if AI makes bad decisions?”

We agree this is a risk. That’s why we’re not advocating blind trust in agents. As mentioned in DAOnloading RADAR, the system being explored is based on community-led validation, curation, and scoring. And importantly, no one will be forced to use agents. This is about giving users optional tools, not taking control away.

“Cross-chain = dangerous. AI cross-chain = more dangerous.”

Totally fair. We’re not building bridges or letting agents move funds on their own. What we’re exploring is how agents might interact with trusted protocols, but with strict limits, alerts, and human approval.

“Why not just use AI for reports?”

If you’re referring to DappRadar reports, then yes agents could absolutely be plugged into our data to pull charts, trends, and stats. The idea is to let humans focus on curating and refining insights, while agents handle the raw data and analysis work. It’s still early, but this is a direction we’re actively exploring.

“Any prototypes or early data?”

Yes and no. Internal development is ongoing. Once we have something stable, we’d love to open testing, possibly starting with PRO users first.

“User segments benefiting most from AI agents?”

Noobs: users who just want to say “swap my $X for $Y” without learning how DEXs or bridges work

DAO and treasury managers: automating reporting, budgeting, and onchain actions with precision

Investors and alpha hunters: discovering early-stage dapps, token movements, and trends faster

Everyday Web3 users: catching up on new airdrops, proposals, or usage spikes without digging through dashboards

Dapp fans: tracking updates, performance, and activity for their favorite apps

Builders and dev teams: integrating agent support into their platforms using live, curated data

Analysts and researchers: pulling custom data for reports, dashboards, and decision-making

Chains and ecosystems: L1s and L2s like Polygon, Avalanche, Starknet, and Berachain looking to offer agents as part of their developer stack

Wallet providers: adding agent-powered prompts and automation to improve UX and user retention

Social and content platforms: projects like Farcaster, Lens, or Overherd using agents to surface trends, hot dapps, or creator analytics

Curators and indexers: using agents to automate dapp discovery, classification, and tagging

Agent developers: needing trusted data and validation layers to make their agents reliable and production-ready

“Natural language UX > current interfaces?”

Yes, for many real-world use cases. It removes complexity, lowers the learning curve, and speeds up interactions.

“Trust Protocol safeguards?”

DAOnloading RADAR introduced the concept at a basic level, but we’ll go deeper into multi-layer validation, scoring, and curation in the upcoming framework.

“Cross-chain security risks?”

Agents won’t manage bridges directly. Instead, they’ll interact through whitelisted, verified endpoints, with fallback logic in case of anomalies.

“What if AI misinterprets data?”

That’s why we need proper validation, curation, and scoring in place. These layers help make sure agents aren’t acting blindly. It would make sense to start with simulation modes, where agents only suggest actions instead of executing them. Some transaction-level limitations should also be considered. The goal is to make agents helpful, not reckless.

“If teams want it, they’ll do it. There’s no community.”

Sure, the team can build things. But DappRadar is already the world’s dapp store, and it runs on open community contribution by listing dapps and other stuff. To scale that, we need more people adding and curating data.
The same goes for agents. Building a useful agent layer isn’t just about tech. It needs community-led curation, validation, scoring, and more. That’s why we will be inviting builders, validators, data analysts, and contributors to shape this together.
If this unfolds as planned, trust in data will come from the community, and trust in agents will too. That’s how we see the foundation of a proper validation layer for agents.

Alex-Mammoth · April 30, 2025, 12:18pm

Appreciate the feedback, Rob.

We don’t always share the full “current situation” publicly for every initiative. Some of what we’re building is still sensitive or in early exploration, and revealing too much too soon can work against us. People don’t want promises, they want results.

That said, I hear you, ser, and I agree. So here’s a breakdown of one of the main areas I’m leading: the DAO Contributor Initiative.

Current situation:

We needed better presence on X, faster community support, and more consistent data contribution from the community side.

DAO initiative to improve it:

We launched a contributor program while ago with Berry, Sidney, Ashley, and Rhizen. Each one is focused on a core area:

Daily Twitter content and growth

Community support and research

Submitting new dapps and helping grow our data coverage

They’re following a structured task system I manage while we continue building a more formal contributor framework in the background.

Budget:

This initiative currently requires about $2,000 worth of RADAR per month to sustain contributor efforts.

Goals and actual results so far:

X (Twitter): We’ve seen strong growth and improved visibility through consistent daily posting and sharper DAO messaging

Support: Response times have improved, and we’ve introduced a feedback form to strengthen the feedback loop

Research: Focused on agentic infrastructure and broader industry trends, with Rhizen actively contributing to ecosystem mapping

Data contribution: Ashley is averaging over 15 new approved dapp submissions per month, which accounts for roughly 10% of total new listings

Yep, the structure you outlined makes sense. I’m balancing execution with clarity, but I’ll work on presenting the value of the DAO contributor efforts more clearly. You know I’m putting together a one-page monthly community lead report, and that should help surface more of this.