Vision for Presearch: A Forward-Thinking Ideation Blueprint V-1

Dear Presearch Team & Community,

I wanted to share the initial version of my document outlining strategic ideas for Presearch, titled “Vision for Presearch: A Forward-Thinking Ideation Blueprint V-1”. This represents a culmination of considerable thought and effort, reflecting a comprehensive vision for our platform’s future.

Please consider this as a starting point; while I believe the document strongly conveys the core concepts and proposals, it’s marked as “V-1” acknowledging that there’s always room for evolution and further refinement.

I invite you all to peruse this blueprint. Your insights would be invaluable, and I look forward to hearing any thoughts anyone has on anything conceptualized herein or any additions people have to add to the concept.

Looking forward to your thoughts and continuing to build on these ideas together.

Best regards,

Google Document Link:


Hello, thanks for sharing and welcome to the Community Forum.


Thanks for pointing me here, I hope this document fosters some interesting discussions!


First of all thank you for the well developed professional product, Im sure this took considerable time. It is clean organized and articulate.

My personal feedback on the content:
I agree 100% on the need for user and community influence and some type of community governance.

I like your vision for Preo AI although I don’t support leveraging GPT-4 or Google Bard as both are not wholly transparent and open-sourced. They will never get all the databases in the world and therefore the market for niche alternatives that have focused AI on a specific topic will outperform these general AIs. They are also building in biases which will doom them to failure when other competitor AI starts to point out those flaws, biases, and better specific results than the general AI. What I would prefer to see is Presearch added all AI to their offerings so that all AI can be tried against each other on a single platform. If Presearch became the 1-stop AI comparative platform it would benefit from user feedback and could then leverage the best of all available new developments in AI to launch its own Preo or Presearch AI. Procure wholesale pricing access to all the AI options and sell to Presearch users at retail profiting off of others continual competition and developments. Eventually Presearch may get Exclusive AI offerings where new models are only available on Presearch driving even greater adoption. Meanwhile users get better search results based on what services the choose to pay for. and those queries could be leveraged with the already established nodes preserving user privacy when using others AI.

Regarding Privacy vs Monetization - If there is a way to do both effectively I think most would support. However, its difficult when the platform collects information on users how do you only collect on some or only sometimes what prevents or ensures the platform from turning that switch on and collecting anytime if the capability is built-in to do it. I don’t agree with your comment that people don’t care about privacy. There are half a dozen privacy focused search providers to include DDG and Brave among the bigger in this space who both continue to increase not decrease their marketshare. As more and more people wake up to the fact that they and their personal data are being used to not only profit big tech corporations that don’t share their values but are also being influenced by them unknowingly, there will be a massive turn away from those corrupt giants over the next decade. The best positioned alternatives will continue to benefit. Presearch needs to provide unique offerings that entice more to the platform. You can’t do the same at lesser quality and expect to get the masses to use it. The search experience either needs to be better or needs to have unique and appealing draws instead… then once you have lots of active users and sustainable revenue you can begin to take on the others in quality and user experience. Attempting to compete with Google, Bing, DDG, Brave, or Opera on user interface, ms response times, or 100 other features they have already mastered is a fools errand for sucha. tiny company and will bankrupt Presearch if they try. Instead they focus on unique offerings that no one else is doing and master those before the competition if they are of substantial interest and value to users, advertisers, etc. then you force the other big guys to play by your rules and you become a breakout leader in the search space at least for those features drawing many new users and revenue to Presearch.

I would support PRE liquidity pools and trying to create another income stream with that but I don’t support PREfi at least at this point I am concerned that would take substantial development and time away from what should be the focus and core product SEARCH. This would also expose Presearch to unnecessary and completely non existent, ambiguous, or unclear legal and regulatory concerns. As a distant future vision once regulations are clear and they have tacked SEARCH… maybe.


Thanks for this report and the many hours involved in writing this document. I have many remarks but let’s start with the naming/branding of the new cosmos chain and token.

Therefore, it’s important to understand the background of smart contract standards…

Smart contract standards have been proposed or adopted by many blockchain platforms and communities, with the most widely used and recognized ones being ERC-20 for fungible tokens on Ethereum, ERC-721 for non-fungible tokens on Ethereum, ERC-1155 for mixed fungible and non-fungible tokens on Ethereum, TRC-20 for fungible tokens on Tron, TRC-721 for non-fungible tokens on Tron, BEP-20 for fungible tokens on Binance Smart Chain, BEP-721 for non-fungible tokens on Binance Smart Chain, CW-20 for fungible tokens on Cosmos, and CW-721 for non-fungible tokens on Cosmos.

So, the most logical name for the token on Cosmos should be PRE (CW-20).

But I do agree that the name of the L1 chain should be just Presearch with PRE as the short chain ID.

PRE20 will only lead to confusion.

If you want to distinguish the PRE token on the Cosmos chain, call it PRE (CW-20), and for the Ethereum chain PRE (ERC-20).


I agree with your suggestions about calling this AI chatbot service “Preo” instead of PreGPT. I can also live with the proposed Preo Dapp UI / UX.

Preo: The underlying AI Technologies

Here, I don’t agree that we should primarily focus on the market leader OpenAI’s GPT-3.5 and 4.0. (and future releases).

I think that open-source “suppliers” such as Yi 34B, Falcon 180B, and Mixtral 8x7B can be as good as or compete with the big players as OpenAI and other market leaders such as Google Bard (Gemini), Meta’s LLaMA, Amazon’s “Q”, Anthropic (Claude 2), and Elon Musk’s Grok.

Below is an image of the competing field…

So, by starting with Mixtral (aka Mistral), the team can make a head start…

But I prefer, just like XRPRE to “bet” on multiple horses. Why not let the community, i.e. the users decide which one they prefer by offering all the main “providers”?

Preo can be unique and charge per query and use PRE for micro-payments. So, if you are not happy with Mixtral results… do the same query/task in another AI chatbot program. So, making Preo, the aggregator of all the best AI chatbots.

But most and for all, don’t choose one solution forever and stay flexible… it should be easy to switch from suppliers in case other suppliers are moving faster.


Elsewhere in this Community, I have often explained why the team shouldn’t restrict itself to the current stringent privacy rules (no third-party cookies, no search history savings)… and hence no form of any personalization.

By introducing privacy levels, we can respect everyone’s preferences concerning being more or less open to personalization for both search results and ads.

However, the way Presearch is now “extracting” search results from the main search engines (and the tool(s) it’s using), and the setup of the nodes network and gateways, don’t make it now possible to save individual search results AND use these for better personalization of search results (without having our own Web index solution).

For privacy level settings about what ads may be shown (and whether tracking or cookies may be used), it’s another story… this should be relatively easy to implement. (The first start has been made by locatilization of the PTAs).

So, yes, I agree that the team should improve monetization via privacy levels where users may opt-in/out for specific ad types, and/or set interests settings, or other forms that make it easier for advertisers to properly target them and where the user will see ads he prefers to see.

Rewarding these users with additional PRE for their monetization “flexibility” is a great way to stimulate this.

Although I’m a proponent for more personalization of the dashboard (i.e. home/start page and UX/UI), and giving users the feature to select their own data sources (both free and paid)… I think this whole PREfi proposal goes one bridge too far.

Yes, we can add some data sources (or add widgets) to show crypto news sources and real-time swap quotes/prices (and we can monetize these via affiliate links)… but the aimed comprehensive marketing intelligence, and advanced DeFi products such as Swap/Trade, DCA, Bridge, Liquidity Pools, Staking, Borrowing/Lending are too far out of scope.

These will take many years to properly develop and implement, where there is already huge competition… also the current team has no experience in these fields… and although properly described what you want… I think you underestimate what it involves.

(BTW, I was heavily involved and advised the management of Orion and RocketX Exchange, both DEX/CEX aggregators (where RVF also aggregates the aggregators), and do know what it takes to build just this part of your PREfi system)

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Agreed on all Ben’s comments. Also the contract IDs would be different ETH vs Cosmos which would be another differentiator between the 2x tokens.

Thank you for your thoughtful feedback and the time you’ve invested in reviewing the “Vision for Presearch: A Forward-Thinking Ideation Blueprint V-1”. Your insights are invaluable, and I wholeheartedly embrace this opportunity to delve deeper into the critical points raised, with a particular focus on the transformative potential of Pre-fi and the unprecedented advancements in AI technology.

1. Vision and Innovation Amplified: The skepticism surrounding the implementation of innovative ideas due to perceived challenges is a natural response. However, this perspective often overlooks the exponential growth trajectory of technology, especially AI. Historical precedents abound where seemingly insurmountable obstacles were overcome through the strategic deployment of emerging technologies and unwavering perseverance. The advancements in AI are not just incremental; they are revolutionary. With each iteration, AI capabilities are expanding at an unprecedented pace, making yesterday’s impossibilities today’s innovations. The notion that “we can’t do it” because it’s hard not only underestimates our collective potential but also disregards the essence of technological evolution.

Exponential Growth in Coding Efficiency with AI: Reflecting on the past three to four years, the evolution of coding with AI has been nothing short of revolutionary. The mindset that projects timelines based on historical coding speeds without AI is becoming increasingly obsolete. With tools like GitHub Copilot, approximately 55% of code is already being written with the assistance of AI, showcasing a fundamental shift in how projects are developed. This does not even scratch the surface of the potential speed increase when developers leverage GPT-4 for coding assistance. The precise acceleration—be it two-fold, four-fold, or even ten-fold—is hard to quantify, but the impact is undeniable. As we stand on the brink of welcoming GPT-5 and its contemporaries, dismissing the feasibility of ambitious projects due to perceived coding constraints is, frankly, illogical. The exponential growth in knowledge work, made possible by AI, is a game-changer, offering substantial increases in productivity at minimal cost. To argue against the feasibility of Pre-fi and other advanced features on the basis of current AI’s capabilities fails to recognize the imminent leap in productivity and efficiency that next-generation AI technologies will bring. It’s not just about doing the same work faster; it’s about unlocking the potential to tackle significantly more complex challenges with the same or fewer resources. This exponential growth factor in coding and development work heralds a new era where the impossible becomes possible, making any dismissal of ambitious projects not only nonsensical but a gross underestimation of our collective potential.

In the rapidly evolving landscape of AI, the development and integration of AI agents mark a pivotal shift in how knowledge work can be accomplished. OpenAI, among others, is at the forefront of this transformation, developing AI agents capable of performing tasks autonomously on users’ devices. These agents promise to revolutionize our interaction with technology, moving beyond mere text generation to executing actionable tasks, such as booking tickets or managing data across platforms​​​​.

Current applications of AI agents span a wide range of sectors, from healthcare and finance to e-commerce and smart homes, demonstrating AI’s potential to improve efficiency, accuracy, and user experience. Future applications are even more promising, hinting at a world where AI agents manage complex systems with autonomy, from personalized healthcare to smart city planning​​.

The move towards AI agents signifies a future where autonomous AI work becomes increasingly prevalent, arguing for a more ambitious approach in technological development and application. This shift towards utilizing teams of AI agents to accomplish knowledge work rapidly underlines the potential for solo entrepreneurs to build significant businesses with minimal human labor. It’s a clear indicator that the scope of what is achievable with AI is expanding, reinforcing the argument that our ambitions should grow in tandem​​.

OpenAI’s efforts to develop AI agents that can navigate web-based tasks and interact with applications on devices are especially notable. By training these agents with examples of human-computer interaction, OpenAI is laying the groundwork for a new era of AI capabilities, where AI agents could autonomously manage tasks that were previously thought to require human intervention​​.

This evolution towards AI agents and autonomous AI work highlights the necessity for projects like Presearch to not only stay abreast of these developments but to integrate them into their strategic planning. The advent of AI agents offers a unique opportunity to redefine productivity and efficiency, suggesting that now, more than ever, is the time to embrace ambitious, forward-thinking strategies that leverage the full potential of AI advancements.

2. Pre-fi as a Paradigm Shift: The Pre-fi concept is not just an addition; it’s a fundamental expansion of Presearch’s potential to generate revenue and deliver value. It represents a strategic pivot towards leveraging decentralized finance in ways that can significantly enhance the project’s scope and sustainability. The apprehension regarding its complexity and regulatory landscape is understandable, yet it’s essential to recognize that with the advent of AI, the capacity to develop, iterate, and refine complex systems is increasing exponentially. AI’s role in enhancing the efficiency and effectiveness of programmers cannot be overstated—what once might have taken years could now be achieved in months, making the vision for Pre-fi not only viable but essential for our forward momentum.

The PREfi concept stands as a transformative strategy within the Presearch ecosystem, aimed at deeply integrating with the crypto community and establishing a robust foundation for the project’s valuation. By focusing on Total Value Locked (TVL) as a key metric, PREfi positions Presearch to showcase a substantial and tangible measure of its financial health and operational scale. This approach not only solidifies a foundation for assessing the Presearch network’s valuation but also aligns with critical financial metrics valued by investors in the decentralized finance space.

Implementing a Coin Market Cap style informational system through PREfi extends the project’s reach and utility by becoming a go-to resource for crypto-related information. This initiative would not only serve the immediate needs of investors and enthusiasts looking for up-to-date data but also significantly enhance Presearch’s visibility within the crypto world. Despite the competitive nature of the market, the unique positioning of Presearch, coupled with the integration of cutting-edge AI technologies and a focus on decentralized search capabilities, provides a compelling value proposition.

The expansion into PREfi and the development of a comprehensive crypto information platform represent ambitious steps forward, leveraging the project’s strengths to capture greater market share and recognition. By doing so, Presearch can potentially achieve a more equitable valuation, reflecting its true contribution to the crypto ecosystem and its users’ value. This strategic move underlines the necessity of not just participating in the crypto space but actively contributing to and shaping its evolution.

Dismissing the potential and strategic importance of PREfi without thorough consideration overlooks the substantial benefits it offers in terms of project valuation, community engagement, and market presence. The decision to pursue such ambitious projects should be informed by a detailed analysis and an understanding of the evolving digital landscape, where AI and blockchain technologies play increasingly pivotal roles.

In this light, the argument for embracing ambitious initiatives like PREfi is not just about expansion but about positioning Presearch at the forefront of innovation and community integration in the crypto world. It’s a call to recognize the potential within the current technological and economic climate to make significant strides in value creation, visibility, and user engagement.

3. AI Integration and Open Source Considerations: Emphasizing the integration of diverse AI technologies, including open-source options, is crucial. However, it’s imperative to acknowledge the qualitative leaps being made in AI development. Comparing the capabilities of leading AI technologies to their nearest competitors isn’t just about noting differences; it’s about understanding the transformative impact these technologies can have on user experience and project outcomes. The cutting edge in AI isn’t merely a step ahead; it’s a quantum leap forward. As such, our strategy must be dynamic, capable of integrating the most advanced AI solutions available while remaining open to the burgeoning field of open-source AI innovations.

In considering the evolution from GPT-3.5 to GPT-4, and looking ahead to the emergence of GPT-5, it’s evident that we are not merely witnessing incremental improvements but rather, monumental shifts in AI capabilities. These advancements are not just quantitative leaps in processing power or data handling; they represent qualitative transformations in AI’s ability to understand, generate, and interact with complex data sets and human queries.

The leap from GPT-3.5 to GPT-4, for instance, has been characterized by significant enhancements in linguistic finesse, information synthesis, creativity, and complex problem-solving. GPT-4’s ability to process over 1 trillion parameters—substantially more than GPT-3.5’s 175 billion—has enabled it to craft responses with a depth and nuance previously unattainable, substantially reducing errors and increasing the relevance and accuracy of its output​​​​.

As we anticipate the arrival of GPT-5, the potential capabilities suggest an even more dramatic enhancement in AI’s computational intelligence. If GPT-4 represented a leap in AI’s effective “IQ,” then GPT-5 promises to redefine the upper limits of AI intelligence and capability further. This progression underscores the critical importance of aligning with the most advanced AI technologies to ensure our competitive edge and innovative capacity. The difference between leading AI models and their predecessors—or even their closest competitors—is stark, not merely in technical metrics but in the transformative potential for applications and solutions​​.

It is with this perspective that we approach the integration of AI technologies within Presearch. While the value of open-source AI models and their contributions to the field is acknowledged, the strategic imperative to harness cutting-edge technologies becomes clear. The qualitative difference in output between the most advanced AI models and others can be vast, underscoring the necessity of integrating these leading-edge technologies to maintain our innovative trajectory and deliver superior user experiences.

This commitment to staying at the forefront of AI development is not just about keeping pace; it’s about leading with innovation that leverages these exponential advancements. By embracing the most advanced AI technologies, we ensure that Presearch remains not just competitive, but pioneering in its approach to search and decentralized finance, ready to capitalize on the boundless possibilities these technologies unlock.

4. Data Privacy and Expanding Our Aperture: The concerns regarding data privacy and the challenges of balancing it with monetization strategies are well-taken. Yet, the premise that it’s too difficult to achieve both is a narrative we must challenge. In technology, the question isn’t if something can be done, but how. With the capabilities AI offers, developing systems that respect privacy while innovating on monetization is not only possible but imperative. As we advance, our approach must be one of expanding our aperture, not narrowing it—embracing broader, more ambitious project scopes that are increasingly feasible with technological advancements.

5. A Call to Action for Bold, Visionary Thinking: The path forward for Presearch demands more than just incremental thinking; it requires a bold, visionary approach that matches the pace of technological innovation. We stand at a pivotal moment where the confluence of AI development and blockchain technology opens up new horizons of possibility. The call to action is clear: we must be more aggressive in our aspirations, more open to expansive ideas, and unwavering in our belief that the technological landscape not only allows for such ambitions but necessitates them.

In conclusion, I invite you to join me in embracing this transformative vision for Presearch. Together, let us harness the exponential advancements in AI and the innovative potential of Pre-fi to redefine what’s possible, ensuring that Presearch not only meets the moment but shapes the future of search and decentralized finance. Your feedback, while pointed, is a catalyst for reflection and, ultimately, action. Let’s seize this opportunity to think bigger, push boundaries, and embark on a journey of ambitious transformation—one step at a time.

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As far as potential future roads for decentralized LLMs, I’d like to bring up the notion of things like Petals, which I think would be perfect to insert as a node role. It would also allow Presearch to be far more selective about models to use, and would keep us from needing a centralized compute provider. Something to consider.

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