Referrals & Staking

Quality Over Quantity

Referrals are pivotal to scaling the Prism community economically, and staking will be the primary mechanism to frictionlessly check quality by leveraging existing personal connections and trust.

Recommenders (i.e. connectors) can stake tokens in their referral recipient (i.e. talent or client) as a signal of confidence in the recipient. Connectors will either receive interest on their stake or lose their stake, depending on the short- (and potentially long-term) performance of referral recipients.

In this manner, staking operates as shortcut to “proof-of-merit." By placing the conector's reputation and compensation on the line, we can discourage false or inflated recommendations, thereby checking quality.

Referrer and recipient reputations/wallets are also “bonded,” encouraging parties help each other succeed because there is upside for maximizing performance.

We also envision successful connectors will be in high-demand and should be rewarded disporportaionately for their contributions, further incentivizing connectors to build their own reputations.

Work Distribution

We believe that access to opportunities is essential to foster diversity, equity, and inclusion from the ground up. Interest on stakes provides a system to explore incentivization structures that might influence supply and demand, and opportunity distribution.

For example, less experienced talent is arguably riskier, so the greater the risk - the greater the reward. We propose offering tiered interest, descending by talent level. As such, Prism is "staking" in its talent base and passing the reward along to connectors and clients.

The reward would manifest as newly minted tokens. Connectors could receive tokens as interest on their stake in a successful referral. Clients could receive token as a percent reward on the contract fee for offering an opportunity to a "riskier" freelancer.

The following is an example interest scheme:

Talent Level	Connector Interest on Stake	Client Reward on Fee
Level 1	20%	10%
Level 2	15%	7%
Level 3	10%	5%
Level 4	5%	2%
Level 5	0%	0%

This system ultimately aims to distribute work across talent levels, which contrasts with Web2 marketplaces where jobs disproportionately flow to top talent. The result of providing more opportunities to less experienced talent is, theoretically, a more engaged talent long-tail and increasingly experienced base over time.

Note, in the above interest scheme, there is no additional incentive to hire the highest level of talent who will arguably see organic demand. In fact, we anticipate outsized demand for top talent and could offer rewards for freelancers to pass along excess work to other freelancers. In these situations, freelancers acts as connectors - they rely on their expertise to vet talent, either known or uknown, on behalf of employers. "Connector-freelancers" would also be incentivized to help their referral recipients succeed.

Lastly, a similar reward scheme can be used to incentivize talent applications to new, earlier-stage, and potentially riskier startups.

Engagement

We believe that staking will not only drive long-term platform quality but also maintain user engagement with the Prism during periods where either freelancers or clients are not actively recruiting.

Users are free to make a referral at any time and as such, can build a "portfolio" of referrals with potential for upside. Perhaps there are opportunties to double down stakes on talent/clients that are particularly promising and/or who request support to obtain more token liquidity.

Key Questions

• When can you stake? E.g. only through a unique referral or at any point?

  • Can a client stake in talent that they loved? What is the mechanism and consequences?

  • If at any point, can more than one party stake in specific talent? What are the consequences?

• Should connector's level affect the "weight" of their referral, and how should this be reflected in the system?

• What is the risk profile and distribution of target clients? E.g. does preference skew towards greater experience or lower cost?

• What is an appropriate reward to incentivize a change of client behavior (i.e. hire Level 2 instead of Level 4)?

• What is the risk profile and distribution of connectors? E.g. how many people in a connectors' network would a connector be willing to stake money or reputation on?

• How does staking in clients work?

• Can you stake in connectors?