
The New Blueprint For Impact Investing DAOs
A new wave of decentralized impact‑investment platforms is changing that. Using blockchain and tokenized governance, they enable communities, investors, and stakeholders to co-create and co-govern in real-time, with complete transparency. Decentralized Autonomous Organizations (DAOs) distribute governance tokens not just to investors but to community members, local NGOs, and even small business owners within the project area. Every proposal, regardless of whether it involves allocating funds for equipment, adjusting wage structures, or expanding services, is voted on and executed via smart contracts.
Governance Before Capital & Decision‑Making Before Deployment of Decentralized Finance
Ever since 2018, the World Economic Forum has acknowledged the potential of blockchain as 'a game-changing technology that can contribute to scaling impact investment by providing trust, transparency, and low transaction costs.' Few segments of finance are expanding this fast, and even fewer are so tightly linked to tackling the world's most urgent social and environmental challenges.
One company taking that idea further than most is Kula, a decentralized impact-investment platform that has spent the past four years building a governance-first model for how capital should flow.
Co-founded by Micah Yeackley, Chris Turner, and Samuel Chen, Kula's premise is simple but radical: before the money moves, the governance must be in place. Instead of fund managers dictating where investments go, Kula uses RegionalDAOs, decentralized autonomous organisations embedded in the very communities where projects are run. Residents, local operators, and investors all hold governance tokens that give them a direct vote on where capital is allocated. Smart contracts execute these decisions automatically, creating a permanent on-chain record. Every action can be audited in real time by all stakeholders, from local farmers to institutional investors.
'We start with governance because without it, the technology doesn't matter,' says Co-Founder and Chief Strategy Officer Samuel Chen. 'The token is not the product, it's the key to a treasury that communities and investors manage together, backed by legal structures that can stand up to institutional scrutiny.'
Kula's Blueprint for Impact Investing of Unlocking Growth Where It Truly Matters
Kula approaches impact investing as a critical avenue to build the future of worldwide communities, starting with the resources that sustain them. In Nepal's remote Tsum Valley, its hydropower project is bringing consistent, renewable electricity to a place where energy once felt distant and uncertain. The turbines power homes and schools, but they also power ambition, enabling local businesses, attracting new skills, and anchoring infrastructure that can serve generations.
Exhausted soil locks farmers in cycles of low yields and low income, with no surplus to invest. In Zambia's Ukwimi district, the Agriculture RegionalDAO is reversing that trend. A 3,000-hectare land gift is being restored through regenerative farming, and blockchain governance ensures farmers guide its future. Better harvests feed the communities, with profits reinvested into the systems that keep productivity rising. But when water comes in destructive floods or fails entirely in drought, even the strongest farms can falter. In Lusangazi, Kula's WaterDAO has introduced balance by utilizing smart systems to store rain during the wet season and release it during the dry season. Crops are safeguarded, incomes remain steady, and the region's agricultural and energy gains are protected for the long term.
Three places, three different constraints. Yet in each, Kula has stepped in at the pressure point and released the flow of progress. 'This is a landmark moment for us,' Yeackley says. 'Four years ago, we set out to build a platform that would treat governance as a first principle. The model brings capital and community together in a verifiable, auditable, and transparent way.'
Regulation: The Infrastructure for Decentralized Finance
By design, decentralized systems remove traditional intermediaries. This increases efficiency but strips away the layers of oversight that normally protect investors, verify claims, and ensure funds are deployed responsibly. Regulation fills this gap by setting governance, reporting, and transparency standards. Without it, even well‑intentioned projects risk being perceived as risky experiments, a perception that can shut the door to institutional capital and limit impact at scale.
Leading jurisdictions are approaching the challenge in different ways, offering distinct pathways for impact-driven DeFi. The UK has created a structured yet innovation‑oriented framework. The Financial Services and Markets Act (2023) defines digital securities, unbacked crypto assets, and stablecoins, embedding strict AML/KYC requirements into financial promotion rules. Its permanent Digital Securities Sandbox lets platforms trial tokenized impact models with direct regulatory oversight.
The EU's Markets in Crypto‑Assets (MiCA) regulation harmonizes standards across member states, mandating AML, KYC, governance, and reserve rules to support cross‑border scaling. Fully decentralized models are currently excluded, but reviews by ESMA and the European Commission signal that DeFi oversight is imminent. At the other end of the spectrum, the US remains fragmented: federal agencies enforce securities, commodities, and AML laws, while states like Wyoming lead with pro-crypto steps, such as DAO recognition and blockchain-specific banking. This opens up state-level opportunities, but the lack of unified rules can deter large-scale institutional investment.
Kula's governance‑first approach is underpinned by institutional‑grade compliance. In 2025, it became the first to obtain a VASP license under Mauritius's VAITOS Act, authorizing it to issue regulated governance tokens linked to real‑world projects.
Following the Governance Layer of Impact Finance
Kula has built its platform on a principle that challenges the norms of traditional finance: governance takes precedence over capital through RegionalDAOs that embed decision-making authority directly into the communities where projects are located. Farmers in Zambia, hydropower operators in Nepal, and water managers in Lusangazi all hold governance tokens, vote on proposals, and see every decision executed on-chain. Every outcome is recorded on‑chain, executed by smart contracts, and visible to all stakeholders in real time.
However, Kula is not alone. This approach sits within a growing constellation of impact-driven DAOs experimenting with how capital, verification, and community oversight can work together. GainForest, for instance, is a project focused on environmental incentives. It utilizes AI, drones, and satellite imagery to verify reforestation and then issues smart contract payments directly to land stewards when growth is confirmed. Donors can watch their impact unfold through dynamic 'NFTrees.' Another notable DAO, IXO Protocol operates as an 'Internet of Impact,' tokenizing verified social and environmental outcomes into digital assets that can be financed and tracked globally.
As regulations mature and institutional capital follows, tokens can evolve from speculative assets into instruments of accountability and shared ownership. If the future of impact finance is to be both inclusive and effective, Kula's blueprint outlines the path to achieve this arduous mission.
Hashtags

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles


Bloomberg
15 minutes ago
- Bloomberg
Lure of ‘Free Money' in Secondaries Nears a Mania
Demand for secondary funds focused on private markets is soaring, in part because some investors are seizing on an accounting quirk that allows them to buy assets at a discount and then revalue them at par. It's 'creating this sense that people are just picking up free money, and almost a mania,' Blue Owl Capital Co-Chief Executive Officer Marc Lipschultz said on a call with analysts recently. He said his firm avoids the practice, adding there is still a 'great business to be had being a really thoughtful buyer of secondary interest when you have more sellers today than you've ever had in the past.'


Forbes
15 minutes ago
- Forbes
AI Agent Types
In the big conversation that companies and people are having about AI agents, one of the major points is around the various different types of agents that we classify into different categories. In other words, there are AI agents, and there are AI agents. Some are fairly rudimentary – while others are extremely sophisticated and skilled. Another way to think about this is that neural networks are not the same as human brains: they're much more heterogenous. They didn't evolve collectively over millions of years, so they may not look like each other in the same ways that human brains do. That said, one of the biggest differences between AI agents is their memory. Stateful systems have some sort of recollection of data – it provides ongoing context for their work. By contrast, stateless systems just start over every single time a user session begins. You'll see the difference in a chatbot or AI agent that either remembers your history, or sees you as a brand new person each time you interact. Seven Types of Agents It also helps to think about AI agent memory within the framework that has developed to distinguish agent types. Experts like to classify AI agents in these seven categories:In terms of memory, perhaps the best distinction is between the first two types – simple reflex agents, and model-based reflex agents. An author simply named Manika at ProjectPro describes an example of a simple reflex agent this way: 'An automatic door sensor is a simple reflex agent. When the sensor detects movement near the door, it triggers the mechanism to open. The rule is: if movement is detected near the door, then open the door. It does not consider any additional context, such as who is approaching or the time of day, and will always open whenever movement is sensed.' And a model-based reflex agent this way: 'A vacuum cleaner like the Roomba, one that maps a room and remembers obstacles like furniture (represents a model-based agent). It ensures cleaning without repeatedly bumping into the same spots.' (Manika actually cites input by Andrew Ng at Sequoia, someone we've had on Imagination in Action forums and interview panels). Essentially, the stateful AI agent relies on having that consistent memory for specific capabilities. Daffodil provides these characteristics of a stateful agent:You can see how having the framework and context drives things like perceiving a shift in user intent, or leveraging a task or purchase history to predict a future outcome or preference. Acting Like Humans In a recent TED talk on the subject, Aditi Garg began with the idea of reconnecting with an old middle school friend: 'That's the beauty of human relationships, the fact that we don't have to reintroduce ourselves,' she said. 'We don't have to explain our inside jokes or our favorite stories. We just pick up where we left off. It's effortless, it's personal. It's what makes friendships so meaningful.' Contrast this with the current capabilities of an AI system that doesn't have vibrant memory…AI today, it can unpack physics, it can summarize books,' Garg added. 'It can also … compose some symphonies, but the moment you open a new chat window, it resets. It's like talking to a brilliant mind, but with amnesia. Machines can reason, but they still cannot remember.' Reimagining Memory Garg went over some of the ways that we are used to thinking about memory, with a suggestion that changing the framework will be useful in adding memory to AI systems. 'On a very fundamental level, we think of data as like a vast digital library with bytes and bytes of information that you can access,' she said. That idea, she noted, may need to be worked on. The memory of AI will need to be accessible in real-time, flowing through the system in the same ways that our own memory is instantly recalled by our biological brains. Making the analogy to a Ferrari that need to be refueled every lap of a race, Garg talked about how AI operations will waste enormous amounts of time trying to access these parts of an AI agent's system. On the other hand, she said, new systems will have immediate, transformed statefulness. 'If an AI system can access any piece of information, it can literally never forget. If it can maintain context across conversations (and) projects … the same storage breakthrough that keeps GPUs fed is the breakthrough that will keep your AI memory alive.' That goal, Garg suggested, has to do with locating the memory and the compute in the same place. Data Centers and Colocation Design I've seen this played out in data center plans where engineers actually put the data and the operations in the same place, along with the energy or power source. You can think of a mini data center sitting next to a nuclear power plant, with the storage banks tied directly into a centralized LLM that will use that data to its advantage. What do you get with these systems? We stand at the threshold of AI that remembers,' Garg concluded. 'When the speed of remembering finally matches the speed of thinking, we enable AI that transforms from a brilliant mind with amnesia, (to) your digital twin.' That might be the next big innovation in machine learning and artificial intelligence – you'll see the same models that you interact with today, endowed with better memory, and they'll seem smarter and more 'with it', because they will know a lot of the things that you would expect them to know if they had the memory of a human brain. By the way, it's a really good idea to know those seven kinds of AI agents, since they're going to remain part of the conversation for a long time to come. What do you see as the next major advance in AI?
Yahoo
18 minutes ago
- Yahoo
CoreWeave Crashes 46% After Lockup--Is This the AI Bargain of the Year or a Falling Knife?
CoreWeave's (NASDAQ:CRWV) post-IPO honeymoon may be ending. After skyrocketing more than fourfold by mid-June, the stock has come back to earthfalling 46% from its June 20 peak. The trigger? Over 80% of Class A shares just became eligible for sale as the IPO lockup expired. That timing came two days after CoreWeave's second earnings report, which revealed a wider-than-expected loss despite a raised 2025 revenue forecast. The stock has already dropped 33% this week alone, with analysts flagging the potential for more downside as early investors head for the exit. Warning! GuruFocus has detected 5 Warning Signs with CRWV. The selloff could create both risk and opportunity. CoreWeave now trades at a roughly $49 billion market cap, down from a June high of $88 billion. Its free floatpreviously under 15%could expand significantly as insiders begin selling. That's likely what spooked the market, according to Roundhill CEO Dave Mazza, who called it a challenging, even confusing setup. Citi's Tyler Radke echoed that sentiment, warning of short-term pressure but suggesting that a more liquid float might attract new buyers. Meanwhile, Nvidia (NASDAQ:NVDA)CoreWeave's key AI chip supplierisn't going anywhere. It actually increased its stake in Q2 to 6.5%, now worth about $2.4 billion. The long-term bull case hasn't vanished. CoreWeave is still spending aggressivelyup to $23 billion this yearto meet rising AI demand, and counts Microsoft as its largest customer. But execution risk is climbing, especially with its all-stock acquisition of Core Scientific looming. Hedge funds like Magnetar and Coatue may opt to ease out slowly to avoid triggering further panic. D.A. Davidson's Gil Luria has a $36 price target, implying over 60% downside from recent levels. Whether this marks a healthy reset or the beginning of a deeper unwind depends on who shows up to buyif anyone does. This article first appeared on GuruFocus.