Comprehensive “How to Design Tokenomics” Guide Funding Proposal
The completion of a comprehensive and practical guide to tokenomics for builders. The guide comprises two parts 1) tokenomics fundamental concepts and history, and 2) a market-tested step-by-step process to design and optimize tokenomics complete with frameworks and template quantitative models in Excel and Python. The guide condenses hundreds of blogs, videos, threads, papers, frameworks, and tools on tokenomics into one helpful nor merely informational guide. The entire emphasis is practical, evidence backed tokenomics design approaches builders can directly apply to their protocols, rather than surface level descriptive summaries.
A few months ago, I was speaking with teams that had just graduated from a Web3 accelerator. All of them were grappling with the same tokenomics questions in parallel - trying to educate themselves on the same fundamental topics, research the same standard practices and parameters, build the same models, and optimize for roughly the same objectives.
It was immediately clear to me that these teams were in need of a comprehensive guide to tokenomics, not just to save them time and resources, but to maximize their chances of success. I’m sure everyone on this thread can fully relate. A practical and comprehensive guide to how to design tokenomics from scratch, complete with prescriptive steps, frameworks and quantitative models simply does not exist.
You can read the initial chapters of the guide, and find a complete outline of the eventual full contents of the guide on Notion:
This funding proposal covers 2-3 months of work to fully complete the guide, including template frameworks and models. As the author, this funding proposal covers my considerable time in researching, compiling, writing, and model building.
I come from an applied industry background, rather than an academic one. My experience includes quant finance (algo trading for one of the world’s largest hedge funds) and technical founder (Python) of a VC funded machine learning startup. I have been in crypto since 2015 and as a tokenomics engineer I have worked with protocols building marketplaces, lending platforms, yield aggregators and more on chains such as ETH and SOL, in addition to helping the Stacks protocol (a Bitcoin L2 layer with $3.7 billion peak market cap) with its own tokenomics and consensus mechanism optimization. My tokenomics work has comprised research, data analysis, technical and non-technical documentation, and custom model building - including both simple deterministic Excel models and stochastic models custom built with Python employing Monte Carlo simulations as well as supervised and unsupervised machine learning techniques.
I am filing this proposal with the support of several senior members of the Tokenomics DAO, and at the bequest of Stewards/SMEs from the TEC community such as @ygg_anderson#4998. This funding would allow me to allocate the required resources to complete the guide as specified, within the allotted timeframe.
In the interest of full transparency, the Stacks Foundation has partially contributed to completing this extremely time and resource intensive guide. The guide however is in no way specific to the Stacks ecosystem, nor does it even cover Stacks explicitly - the guide is entirely chain agnostic.
TEC’s funding would allow for further development, more rigorous quantitative modeling templates, and perhaps most importantly, forever attach TEC’s name to this comprehensive tokenomics guide. Buy-in from the TEC community would increase the quality, rigor, and credibility of the guide, while also making a significant contribution to TEC’s corpus of tokenomics resources for protocol builders.
Total request for 12,000 xDAI
100% of the funds will be used to fund contributors time in researching, compiling, writing, editing, modeling, and reviewing feedback from SMEs.
This breaks down to roughly 4,000 xDAI per month, with the guide fully completed no later than 3 months from this proposal review.
Via Twitter and Discord as new chapters (and models or frameworks) are published, as well as via Notion, where the document itself lives, and will be updated live, with full TEC community transparency, and ability to comment and provide their productive input, at any given time.
Primary author: MattyTokenomics (https://twitter.com/MattySTX)
Content reviewers and contributors:
- Albert Liang, founder at Stacks Web3 Founders Lab
- Florian Strauf, founder at Tokenomics DAO
- Maximillian Gusche, core contributor at Tokenomics DAO
- Jeff, founder at Mechanism
… more names with large audiences and practical tokenomics experience in the works