Hello everyone 👋, I’m Rafael, CTO of Digital Gaia. We’re on a mission to ignite a regenerative agricultural revolution from the bottom-up, using open science and AI to empower the world’s 1 billion farmers and land stewards with decentralized tools to measure and monetize their regenerative performance.
Before embarking on this journey, I worked at the intersection of business strategy and software development computational modeling for over 16 years (6 of those at google). In my careerI’ve had a lot of mentors and seen a lot of useful patterns and primitives that help collectives achieve their goals – coming from various disciplines such as systems investment, corporate strategy, ecosystem development, computer science, and game theory.
Importantly, I’ve also seen a lot of stuff attempted in practice which fell by the wayside, despite best intentions, thanks to the Law of Unintended Consequences!
So how am I taking the lessons learned here and apply them to thinking around the problem of effectively financing planetary regeneration? In a nutshell, this problem is the ultimate instantiation of some classic strategy problems:
Planetary regeneration is obviously a good thing, yet we never seem to get enough of it.
Investors are willing to spend tons of money, yet results fail to materialize.
The entrepreneurs and leaders trying to make it happen on the ground are frustrated and starved of resources.
It treads similar ground to a previous article of mine from 2019, but ReFi has come a long way since then, and I’ve also learned some new lessons! Still – take it as a conversation starter, as I definitely don’t claim to have all the answers.
In the last few years, we’ve succeeded at making most world leaders aware of the risks posed by climate change and the loss of biodiversity and the need to mobilize resources towards solutions. We’ve obtained major commitments out of them. All the big tech billionaires and most governments are opening their checkbooks, and significant cash is starting to flow: an estimated $83 billion went to climate finance in 2020, and the overall “green economy” reached a market capitalization of $7 trillion in 2021.
Congrats! We’ve won, right?
Well, no. We can spend all those trillions of dollars and much more, and still get nowhere in terms of meeting our regeneration goals. Why? Because it's all being spent on projects that:
“look good on paper” but are ineffective, like big monoculture planting
Come with unintended negative consequences, like biofuels that compete with food crops, or conservation projects that just transfer deforestation to other regions
Are effective at small scales but have grown too fast or too large
could be effective if properly funded, but become chronically starved of funds so that investors can “mitigate risk” (also known as “peanut-buttering”)
are greenwashing or plain outright fraud, like phantom offsets or overly tech-centric solutions coming from Silicon Valley or Web3 circles.
A common objection is that with enough resources, we can brute-force our way through the solutions even without worrying about all this waste. Unfortunately, if not managed effectively, excessive money can actually reduce the overall results – for example, by attracting more snake oil solutions that outcompete good entrepreneurs (a phenomenon known as adverse selection).
In the extreme case, the entire sector just becomes discredited, all that money gets clawed back, and we’ve just wasted several years of people’s lives and credibility. Think of putting liquid through a funnel with a narrow mouth: if you try to force too much of it at once, it will just accumulate and overflow. If the funnel isn’t well-made, it can even break.
The key concept here is leverage: putting the right resources in the right place at the right time. And that’s what strategy is all about: finding the points of highest leverage in a system, identifying where we can feasibly intervene, and planning for how to best do it given limited resources. In the remainder of this article, I’ll give my personal view on how we can apply the classic concepts of strategy to do just that.
Richard Rumelt is one of the world’s leading strategy consultants and authors. Arguably his most classic book, Good Strategy/Bad Strategy, is entirely dedicated to the gap between good intentions and actual results. Although he focuses on corporate strategy, most of his insights are fully applicable to the problem at hand.
Drawing on his experience as a systems engineer at NASA Jet Propulsion Laboratory (JPL), he observes that the act of strategy is not like selecting an option from a menu of options; in any real-world scenario, there is an astronomical number of possible policies and projects to pursue, and it’s just impossible to exhaustively search for the optimal option. Rather, strategy is an act of creation: designing a course of action that solves the problem at hand. And the best way to do that is to use a scientific, iterative approach:
Developing a diagnosis or framing of the problem which points to a narrow region of the action space to explore;
Building a guiding policy or theory of change that focuses efforts on that narrow region;
Identifying coherent actions or tactics that appropriately integrate exploration/validation of the theory of change and its execution.
That is the approach I’ll take in what follows. (By the way, if you want to learn more about this framework for understanding and practicing strategy, my friend Dimitri Glazkov has written a great primer – check it out!)
The term “moonshot” has been watered down by overuse, but here I’m talking about the original kind. The Apollo program was likely the most complex effort ever undertaken by humanity. Even at a price tag of about $152 billion in today’s currency, it shows the incredible power of high leverage.
To create from scratch an array of entirely new technologies required to put humans on the moon and bring them back required a vast amount of independent, often competitive R&D from hundreds of private contractors. Yet that massive network of players – totalling some 400,000 people overall and spread across the US – had to somehow coordinate so that their contributions would actually fit together into a cohesive whole. And yet, all of this was accomplished in eight years, with the telephone, printer and punch-card computers as their sole information technologies.
Similarly, in order to achieve planetary regeneration, we don’t just need a lot of money, but also focused, coordinated effort towards a clearly articulated plan, combined with disciplined competition to find the right solution for each subproblem (and sometimes also competition to better understand the problems). In game theory, this can be framed as a positive-sum, multiplayer game with two classes of players:
Entrepreneurs: People who are connected to the beneficiaries of impact and other stakeholders, who have an understanding of the potential options and their pitfalls, and who are willing to invest immense amounts of time and energy to create, test, iterate and scale solutions.
Investors: People/organizations that have an interest in seeing the end goal achieved, access to significant resources, the ability to allocate those resources, but don’t have knowledge or capacity to generate and execute on solutions.
So another aspect to this framing is to understand how we’re playing this game today. Let’s start from the perspective of entrepreneurs.
Regenerative entrepreneurs are, by and large, not empowered to create impact. The most obvious manifestation of this is funding: being in the ReFi and impact spaces for a while, it’s an incredibly common sight to see incredibly promising but chronically underfunded projects being put on the backburner, or having to shut down due to lack of resources. The situation certainly improved in 2022’s climate tech boom, but even then, investment mostly accrued to sexy, “easy to scale” projects (especially if pitched by tech bros with SV credentials!), not necessarily the most impactful ones.
Even more critically, though, the problem is that we lean on the startup playbook so hard that regenerative entrepreneurs’ competitive juices are wasted on the wrong arenas of competition such as:
Funding, going through pretty ridiculous hoops – pitches, oblique grant forms, etc – to access the same limited resource pool.
“Owning the story”, and to find a “unique” framing for what they are trying to do – when it’s totally fine to be one of many people working on the same big story.
“Owning the market”, to appease investors obsessed with “winner take all” – when they should just be focusing on great execution.
scarce hires, access to data, IP, and other resources that by all rights should be (at least partially!) common goods.
So, not only are regenerative entrepreneurs underfunded in aggregate; each project actually ends up squandering much of what it does have on competitive activities that don’t actually help impact get created. And to think many investors are proud of this as bringing “market discipline” to regeneration!
This is not to say that regenerative and impact investors are happy about the situation either! Investors rarely have a clear, quantitative understanding of the true impact achieved by projects, let alone reliable forecasts. They also face a simultaneous lack of high-quality projects and excess of noisy, overpromising projects. Put together, it’s almost impossible to assemble a project portfolio that is coherent even in basic terms of financial metrics, let alone in terms of achieving the strategic goals of regeneration.
This pattern – an inability to close the gap between what the “leaders” want and what the “people on the ground” need to make it happen – is exceedingly common in large-scale strategy. In a nutshell, the problem is too large for top-down planning, and too wicked to be solved by winner-take-all competition or by democratic preference weighing. New tools are needed; in their absence, everyone ends up frustrated and wondering why we keep getting stuck when there’s so much enthusiasm!
Applied at the collective level, Rumelt’s understanding of strategy as design helps us see where different social structure archetypes (”superminds”, as MIT’s Thomas Malone refers to them) — such as markets, democracies, hierarchies, networks and ecosystems — are or aren’t useful.
By applying these structures in a coherent, principled way, we can create one massive regenerative moonshot, integrating competition and cooperation between funds and projects, that will greatly increase the regenerative movement’s leverage, agility and overall impact.
As the previous section indicates, there is no one-size-fits-all solution in strategy, but rather a continuous process of refinement. Luckily, we don’t have to reinvent the wheel: there are plenty of proven building blocks that can be used and iterated on. Some originate from the impact world itself, while others come from fields as diverse as game theory, financial planning and analysis, and system dynamics.
Here is a brief summary from the concept paper we wrote at Digital Gaia:
Covenant (also known as: consortium; social contract; ground rules)
Goal: Turn the participants of the decision-making process into a collective — get them invested in the process, produce a we-frame, etc.
Tools: DAO treasury smart contracts; “dumb” legal contracts like partnership agreements; financial services like escrow accounts; etc.
Common goals (also known as: shared vision)
Goal: Create a shared understanding of what the process is supposed to achieve.
Tools: predefined goal frameworks like SDGs; quadratic voting; etc.
Roadmap (also known as: dependency graph)
Goal: Define a theory of change as a structured object, hypothesize and validate interim objectives that are needed to achieve the common goals, providing a focusing lens and a pivot for strategic changes.
Tools: Tech Trees
Generative models (also known as: predictive digital twins; simulation engines)
Goal: Decouple upfront decision-making on “what to support” from retroactive decision-making on “what was useful (and should be rewarded)”.
Tools: Hypercerts; Requests for Proposals; etc.
Below is one of many possible examples of how the above tools can be combined.
A bunch of investors/funds get together and form a consortium to invest in regeneration. Others can join if they agree to ground rules.
Performs a round of quadratic voting to define top-level common goals.
stablishes a roadmap, working back from common goals to the critical dependencies needed to achieve them. This gets codified as a public baseline model.
Identifies gaps/opportunities based on what's already in the market or being developed. And prioritize opportunities using quadratic voting, and issue RFPs (Requests for Proposals) for each opportunity.
Entrepreneurs submit their project proposals, each including a model of their low-level theory of change to compare against the baseline model. Proposals are run through a simulation engine, optimization algorithm finds the combination of projects (portfolio) that achieves the best joint theory of change at the lowest total cost.
Investors privately assess entrepreneurs’ ability to execute proposals, compete with each other to invest in the best entrepreneurs, act as venture studios to shape projects into being, etc. Within each subproblem, normal competitive market dynamics apply: execution, natural competitive advantages, geographical barriers and other niche-creating factors.
Entrepreneurs and investors are rewarded retroactively using hypercerts.
Rinse & repeat. Steps 4-7 can be iterated very frequently, for instance, every quarter. Steps 2-3 need a bit more stability, and can be iterated every 1 year or so.
It’s interesting to compare the above model sketch to a real, ongoing program that has both good and bad parts to it: Horizon Europe, the European Commission’s 7-year, 95.5 billion euro research and innovation funding program. Sure, it uses legacy tools that limit the speed of deployment and iteration; and perhaps most critically, it does suffer from a lack of focus in trying to “prioritize everything”.
The program’s structure – a combination of top-down long-term goals, bottom-up, competitive innovation to tackle these goals, and incentives for partnerships between startups, universities and other kinds of organizations to generate a commons of shared resources – forms a good pattern that can be emulated and improved on.
The devil is in the details, yet perfection is the enemy of progress. Thus, the above should not be seen as a curmudgeon’s critique of the current state, nor a call to stop everything and start from scratch with a perfect tabula rasa.
Quite the opposite: it’s a call for us all, as co-designers of the future of the regeneration movement, to intentionally align our actions with the big picture, so we can all learn and iterate faster together, using all the coordinative and competitive structures at our disposal.
A final questions for reflection:
If you’re a regenerative investor:
Am I sending clear and transparent signals to entrepreneurs and other investors about my goals and theory of change?
Am I wasting entrepreneurs’ time?
How can I encourage more measurable and targeted projects?
How can I encourage coalitions of projects?
Am I making full use of today’s tools to create better outcomes?
If you’re a regenerative entrepreneur:
What is my big-picture theory of change? Can I point to where I fit into it?
What are my true unique comparative advantages? What is the one thing I can do better than anyone?
Can I join forces in a coalition to get more done?
If you’re implementing any of the above practices/structures in regenerative or impact investment, I’m really curious to know how it’s playing out for you! In particular:
If you’re working in regenerative agribusiness, either as an entrepreneur, investor, buyer, insurer, etc – let’s partner up!