Did friend.tech give us a glimpse at reputation onchain?

In late Summer 2023, we saw our first real taste of Social-fi for the cycle: friend.tech.

The idea was simple:

  • When a user signed up for friend.tech from Twitter, the app created a “private chat” for that user.

  • Other users would buy those keys to gain access to that chat, providing the unique ability to connect with crypto influencers and knowledgeable participants who were, otherwise, out of reach.

  • Most importantly, friend.tech designed these keys on a bonding curve, meaning every time a user bought into the private group, the price of the chat’s key increased. This meant the most influential people had very expensive keys.

This idea quickly extended its reach beyond crypto- anyone from NFL legends to TikTok influencers could join friend.tech, create a private chat, and give fans a chance to connect with them directly. A truly unique, novel, and interesting new product had emerged in Social-fi. Deep in the bear, this caught people’s attention quickly.

A few weeks in, Paradigm announced that they had invested—and the game changed. Not only was this a new and compelling product that captivated the market, but Paradigm knew how to incentivize early usage of protocols and reward them with tokens.

This attracted farmers wanting an early shot at a potential future token (points, which later became $FRIEND) - and money flooded into friend.tech. As people scrambled to buy up different keys and lock money into the contract to yield farm, they quickly ran into a problem: whose keys do you buy?

From Kyrian Alex’s article, “A Deep Dive into friend.tech”
From Kyrian Alex’s article, “A Deep Dive into friend.tech”

Due to this bonding curve, key’s price could be volatile. In the same way the price increased when users purchased a key, it could just as quickly decrease when users sold their key.

Top keys would quickly rise to a few thousand dollars, but people realized something quickly: that person’s key price was directly tied to their reputation. What if they did something that others didn’t agree with? What if they launched a project and pulled the rug? That key price was likely to come screaming back down.

Users suddenly had to consider financial risk when it came to buying into someone’s key and their associated reputation.

Farming required trust

In order to farm the protocol for points, there needed to be trust in people, their keys, and their reputation.

If you wanted to farm points with 1e, you wouldn’t dare buy a key of someone you didn’t know, especially considering it could drop to 0.1e if that person did something irreputable.

This kicked off the era of (3, 3) on friend.tech, which is a reference to The Prisoner’s Dilemma. In a (3, 3) relationship, two users agreed to buy each other’s keys, increasing the price of each of their keys. This allowed them to cooperate and yield farm with less risk. If either of the parties exited the (3, 3) relationship, people recognized that as defecting from cooperation. This was generally frowned upon unless both parties agreed to exit the relationship (or stop farming) together.

So in order to farm in friend.tech, you had two options:

  1. Buy a key of someone you trusted or who was “noteworthy” (e.g. an influencer, or a user with an already valuable key)

  2. Enter (3, 3) relationships with your friends, drive your key price up, and farm “safely”

As people evaluated what keys to buy or what relationships were worth entering, users started building dashboards on top of friend.tech’s transaction data. These dashboards provided insightful information on evaluating the reputation of other friend.tech users. Who had defected from (3, 3) relationships? Who had done it the most consistently? Many dashboards even went as far as to define a “quality score” to use when deciding whose key to buy or enter a (3, 3) with.

This was our first glimpse at a “credibility score,” and has been a huge inspiration for what we’re building at Ethos.

@0xBreadguy's original (3, 3) dashboard
@0xBreadguy's original (3, 3) dashboard

Credibility Instrumented

The game of (3, 3) also attracted people looking to make a quick buck.

Since it is difficult to judge people’s past credibility in crypto, we have often leaned on poor evaluations like how many Twitter followers a user had to evaluate if they should be trusted.

This led to bad actors entering (3, 3) relationships with multiple people to help drive up their key price. Once they convinced dozens of people to buy their key, these bad actors would dump all the keys they held to make a profit, defecting on all of their (3, 3) relationships.

This behavior isn’t surprising in crypto, but for the first time there was documented, onchain proof of a bad actor’s behavior.

This is when I realized how impactful friend.tech could be if:

  1. Credibility could be measured onchain and

  2. Credibility was hard to spoof because of

    1. unique identities tied to public profile on Twitter

    2. economic security in the price of keys

I vividly remember tweeting about it. It was my “aha” moment for what made me so bullish as a trader on friend.tech:

This was the top of (3, 3) mania, when friend.tech’s TVL was at an all time high, and when the grifters starting piling in. People pumped and dumped their keys, and even though it was now measurable, there was still a significant loss of capital in those scams. It became clear that we needed additional instrumentation, alongside the bonding curve, to help show who could be trusted.

These two tweets are the origin story of Ethos. It’s when I reached out to my co-founder Ben, who decided to leave his web2 career because he too saw the opportunity to help tackle the most important problem facing crypto today: onchain fraud and scams, and how that ultimately hinders further adoption.

What did we learn from Friend.tech?

Friend.tech opted not to lean into (3, 3) or any of the credibility components and focused exclusively on launching their token and expanding their room key use cases.

It turns out that, for most people, the (3, 3) logic combined with the bonding curve meant that the capital risk of trusting someone was too much to bear. Additionally, the relationships created unique challenges for well-intentioned users who were trying to exit their farming positions when friend.tech started to lose attention. These honest “exits” muddied the data on defections and their “credibility scores.” Unfortunately, the fidelity of onchain reputation data fidelity was lost.

Friend.tech indirectly gave us insight that in crypto:

  1. Economic security (aka backing someone with “capital”) has the ability to bolster someone’s reputation and credibility, and

  2. That documentation of past positive and negative experiences onchain is extremely valuable for future evaluation of credibility.

With Ethos, we’ve tried to tackle these concepts head-on.

To address economic security, we’ve introduced the idea of “vouching.” Instead of buying keys on a bonding curve, users stake eth against people who they trust.

For documenting trust and reputational signals without the financial aspect, we’ve brought a simple review system on-chain.

And for calling out and reprimanding people who step out of line? We just borrow from the Proof of Stake slashing model for Ethos.

With your help vouching, reviewing and slashing - combined with other metrics - we’ll be able to produce Ethos credibility scores for every participant. An easy, succinct way to evaluate trust. We can rewrite financial incentives from fraud and grift to more meaningfully reward crypto’s most reputable participants.

Join the waitlist today.

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