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DARC, Decentralized Autonomous Regulated Corporation

Hacker News

DARC, Decentralized Autonomous Regulated Corporation

Hey HNs, I am lidangzzz, a core developer and contributor to Project DARC. In simple terms, we have designed two components: 1. DARC is a company virtual machine that can be compiled and deployed on any EVM-compatible blockchain. It includes a set of opcodes and a plugin system. The opcodes correspond to the daily operations and activities of a company, including handling equity (tokens), cash, and designing and operating plugins. Plugins in DARC represent the company's bylaws, contracts, articles, or rules. Each plugin can approve or reject specific situations. Therefore, a DARC with a complete plugin system functions like a conventional shareholder company. Adding, enabling, or disabling plugins also requires adherence to existing plugins and rules. Additionally, DARC supports an infinite hierarchy of tokens. Different tokens are restricted based on voting weight, dividend weight, and different plugins, facilitating the creation of various assets such as Class A/B stocks, bonds, boards of directors, committees, executives, common stocks, preferred stocks, commodities, NFTs, and more. 2. By-law Script is the world's first programming language used to describe and execute laws. Users can operate DARC by writing By-law Scripts or design and deploy plugins. By-law Script features sweet syntax like operator overloading, allowing users to quickly draft various laws for DARC, such as anti-dilution of equity, Bet-on agreements, employee RSUs, employee salaries, employee options, bonds, boards of directors, independent directors, dividends, procurement, subscriptions, and other rules. In summary, our goal is to completely abstract traditional legally registered corporate entities from government oversight. In a world with only blockchain and smart contracts, we aim to abstract the legal system entirely into the DARC virtual machine deployed on the blockchain. We use the plugin system to fully express the consensus and constraints of major shareholders, investors, founders, executives, employees, and customers, transferring the entire operation, legal framework, and consensus of the company to the blockchain. This realization enables the creation of anarchist blockchain business entities to create value and provide services. We are open-source enthusiasts, believing in the power of open source to guide the improvement and security of the DARC project. We have already completed the basic architecture and whitepaper of DARC, but there is still much work to be done. We will release our mainnet and testnet at the appropriate time, allowing developers to test and explore the design and operation of anarchist business entities. DARC repository: https://github.com/Project-DARC/DARC DARC whitepaper: https://github.com/Project-DARC/DARC-whitepaper

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports, including, compatible · Missing: reddit linkedin, podcasting, created
98%98% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, existing · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, user, code · Missing: agents, macos, agent
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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