Magistrate – Plaintext legal contracts for developers

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I made this because I think that if contracts were written in plain text files and managed more like software, from version control to IDEs, lawyers would work more quickly and intelligently for their clients, saving them money. But the entire practice of transactional law is stuck on Microsoft Word. My clients are mostly technology companies with an appetite for innovation. With their encouragement, I am moving my own legal practice away from formats like Microsoft Word and into plain text. Electronic signatures of plain text contracts is the starting point for that effort. The MVP is this developer API. If the reception to this product is positive, I'll continue to release the products that I build. In time, my hope is that plain text will supplant Microsoft Word in the drafting, negotiation and execution of contracts.

Visit product View on Hacker NewsJan 31, 2022

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Product HuntOn track for Day 1 leaderboard · Strong signals: plain · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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