Retroactive public goods funding

This is the final post in our Opening up the Ballot Box series for 2024. Changes planned for Retro Funding 2025 will likely reshape how we analyze voting behavior.

In RF6, our results (as an organization) reflected a critical issue with Retro Funding in its current form: subjective visibility often outweighs measurable, long-term impact.

We had two project submissions:

1. Insights & Data Science (work like this series of posts): awarded 88K OP, the highest of any submission in the round.
2. Onchain Impact Metrics Infra (open data pipelines for the Superchain): awarded 36K OP, despite being a much larger technical and community effort.

We are humbled by the support for our Insights & Data Science work. Retro Funding has made our work at OSO possible, and we are deeply grateful for this affirmation. But we can’t ignore the underlying signal: the work that is most visible-—like reports, frontends, and ad hoc analysis—-tends to receive higher funding than work that delivers deeper, longer-term impact.

Open-source projects power innovation across industries, yet they often face a significant challenge: securing sustainable funding. Retroactive funding offers a promising solution by rewarding impactful contributions based on past results, but today’s retro funding rounds are complex, time-consuming, and infrequent, making them unreliable sources of support for public goods.

This inspired us to build AutoRF during ETHGlobal San Francisco 2024. AutoRF makes retroactive funding continuous, simple, and scalable by removing the barriers that hold current models back.

Optimism’s Retro Funding Round 5 (RF5) just wrapped up, with 79 projects (out of ~130 applicants) awarded a total of 8M OP for their contributions to Ethereum and the OP Stack. You can find all the official details about the round here.

In some ways, this round felt like a return to earlier Retro Funding days. There were fewer projects than Rounds 3 and 4. Venerable teams like Protocol Guild, go-ethereum, and Solidity were back in the mix. Voters voted on projects instead of metrics.

However, RF5 also introduced several major twists: voting within categories, guest voters, and an expertise dimension. We’ll explain all these things in a minute.

Like our other posts in the “opening up the ballot box” canon, this post will analyze the shape of the rewards distribution curve and the preferences of individual voters using anonymized data. We’ll also deep dive into the results by category and compare expert vs non-expert voting patterns.

Finally, we'll tackle the key question this round sought to answer: do experts vote differently than non-experts? In our view, the answer is yes. We have a lot of data on this topic, so you're welcome to draw your own conclusions.

The voting results for Optimism's Retro Funding Round 4 (RF4) were tallied last week and shared with the community.

This is the last in a series of posts on RF4, analyzing the ballot data from different angles. First, we cover high-level trends among voters. Then, we compare voters’ expressed preferences (from a pre-round survey) against their revealed preferences (from the voting data). Finally, we perform some clustering analysis on the votes and identify three distinct “blocs” of voters.

Retro Funding aims for iteration and improvement. We hope these insights can inform both the evolution of impact metrics and governance discussions around impact, badgeholder composition, and round design.

You can find links to our work here.

This post is a brief exploration of the before-after impact of Optimism’s Retro Funding (RF) on open source software (OSS) projects. For context, see some of our previous work on the Optimism ecosystem and especially this one from the start of RF3 in November 2023.

We explore:

1. Cohort analysis. Most RF3 projects were also in RF2. However, most projects in RF4 are new to the game.
2. Trends in developer activity before/after RF3. Builder numbers are up across the board since RF3, even when compared to a baseline cohort of other projects in the crypto ecosystem that have never received RF.
3. Onchain activity before/after RF3. Activity is increasing for most onchain projects, especially returning ones. However, RF impact is hard to isolate because L2 activity is rising everywhere.
4. Open source incentives. Over 50 projects turned their GitHubs public to apply for RF4. Will building in public become the norm or were they just trying to get into the round?

As always, we've included source code for all our analysis (and even CSV dumps of the underlying data), so you can check our work and draw your own conclusions.

Voting for Optimism’s fourth round of Retroactive Public Goods Funding (“Retro Funding”) opened on June 27 and will run until July 11, 2024. You can check out the voting interface here.

As discussed in our companion post, Impact Metrics for Optimism Retro Funding 4, the round is a significant departure from the previous three rounds. This round, voters will be comparing just 16 metrics – and using their ballots to construct a weighting function that can be applied consistently to the roughly 200 projects in the round.

This post is a deeper dive on the work we did at Open Source Observer to help organize data about projects and prepare Optimism badgeholders for voting.

Filecoin’s first RetroPGF round ("FIL RetroPGF 1") concluded last week, awarding nearly 200,000 FIL to 99 (out of 106 eligible) projects.

For a full discussion of the results, I strongly recommend reading Kiran Karra’s article for CryptoEconLab. It includes some excellent data visualizations as well as links to raw data and anonymized voting results.

This post will explore the results from a different angle, looking specifically at three aspects:

1. How the round compared to Optimism’s most recent round (RetroPGF3)
2. How impact was presented to badgeholders
3. How open source software impact was rewarded by badgeholders

It will conclude with some brief thoughts on how metrics can help with evaluation in future RetroPGF rounds.

As always, you can view the analysis notebooks here and run your own analysis using Open Source Observer data by going here. If you want additional context for how the round was run, check out the complete Notion guide here.

Open Source Observer is working with the Optimism Collective and its badgeholder community to develop a suite of impact metrics for assessing projects applying for Retro Funding 4.

Introduction​

Retro Funding 4 is the Optimism Collective’s first experiment with Metrics-based Evaluation. The hypothesis is that by leveraging quantitative metrics, citizens are able to more accurately express their preferences for the types of impact they want to reward, as well as make more accurate judgements of the impact delivered by individual projects.

In contrast to other Retro Funding experiments, badgeholders will not vote on individual projects but will rather vote via selecting and weighting a number of metrics which measure different types of impact.

The Optimism Foundation has published high level guidance on the types of impact that will be rewarded:

• Demand generated for Optimism blockspace
• Interactions from repeat Optimism users
• Interactions from Optimism users with high trust scores / onchain reputations
• Interactions of new Optimism users
• Open source license of contract code

The round is expected to receive applications from hundreds of projects building on six Superchain networks (OP Mainnet, Base, Frax, Metal, Mode, and Zora). Details for the round can be found here.

At Open Source Observer, our objective is to help the Optimism community arrive at up to 20 credible impact metrics that can be applied to projects with contracts on the Superchain.

This page explains where the metrics come from and includes a working list of all metrics under consideration for badgeholders. We will update it regularly, at least until the start of voting (June 23), to reflect the evolution of metrics. The first version metrics was released on 2024-05-16 and the most recent version (below) was released on 2024-06-24.

RetroPGF generated a considerable amount of noise, both during and after the main event. Now that the results are in, we need to find the signal. These are the messages, intended or not, that will likely reach the wider community.

We can learn a lot by plotting and analyzing the distribution patterns of tokens to projects. In domains where the signal is too weak (ie, impact > profit) or too strong (ie, profit > impact), the Collective should be more explicit in shaping the distribution patterns it wants to see and then making tweaks to the RetroPGF process and game design.

In this post we will take a look at:

1. 30,000 foot view: the signals that everyone in crypto should pick up on
2. Box seat view: the signals that badgeholders and engaged community members should pick up on
3. In the arena view: the signals that live players and builders should pick up on

I also want to make sure I don’t bury the lead:

• Less than 20% of the RetroPGF 3 allocation went to projects that directly contribute to sequencer fees.
• Every badgeholder and citizen who wants the best for Optimism probably feels that this allocation level is too low.
• This is not a sustainable trend, given that sequencer fees are the long-term revenue engine for this whole experiment.

Many factors likely contributed to this outcome. In a previous blog post, we discussed how the round’s game dynamics could make it difficult for voters to express their true preferences.

RetroPGF is a unique kind of repeated game. With each round, we are iterating on both the rules and the composition of players. These things matter a lot. To get better, we need to study whether the rules and player dynamics are having the intended effect.

This post looks at the psychology of the game during Round 3, identifies mechanics that might have caused us to deviate from our intended strategy, and suggests ways of mitigating such issues in the future.

Disclaimer: I was a voter and had a project in Round 3. I also made a lot of Lists.