6 Lessons in Building Ratio1 as a Product People Need
General
Education
In the startup world, most tech products fail not because they can’t be built - but because they solve the wrong problem. From day one, we built Ratio1 - a decentralized AI meta-OS - with a developer-first mindset. Here are 6 key takeaways we embraced (inspired by Michael Skok’s classic lecture, originally introduced at Harvard Innovation Labs and still available online.) to ensure Ratio1 is something people actually need - not just something new.
Start with the Problem, Not the Idea
We didn’t begin by pitching “a cool blockchain AI platform.” Instead, we started by identifying three major pain points our target users faced, and we defined the problem in those concrete terms. First, development is costly and complex - even with modern tools (e.g. OpenAI’s Codex), building sophisticated ML solutions demands significant time, expertise, and budget. Second, deploying and managing AI (DevOps/MLOps) is notoriously difficult and resource-intensive for small teams. Third, cloud infrastructure is prohibitively expensive and comes with vendor lock-in. In other words, current AI deployment is too costly, too centralized, and too difficult without specialized expertise. Ratio1 was conceived entirely around solving these pains, not showcasing technology for its own sake. Yes, our idea involved a decentralized “AI cloud” of idle devices (a DePIN cloud-on-edge) to cut costs - but that’s just one pillar. We also built Ratio1 as a permissioned, resilient network (so it can serve applications needing reliable, compliant hosting) and focused on a developer-friendly experience (offering plug-and-play tools and SDKs so you can use our platform in your own language or container with minimal friction). In short, we let the problem guide the idea. Everything in Ratio1 - from leveraging distributed edge compute to enforcing trust/compliance and simplifying AI app development - was shaped by real user pain points, not by chasing buzzwords.
Use the 4 U’s to Qualify the Problem
We made sure our target problem checked the right boxes before diving in. In our case, the pain is undeniably Unworkable if left unsolved (many teams simply cannot deploy AI at scale under today’s costs and constraints). It’s Unavoidable as AI adoption grows - demand for compute is exploding, whether we like it or not, and those limitations will hit everyone. The problem is clearly Underserved by current solutions. In fact, existing platforms either force you into expensive vendor lock-in or lack key features for AI workflows, leaving smaller players in the lurch. That told us this wasn’t a mere inconvenience - it was a glaring gap in the market. And the Urgency was real: if we don’t solve this now, countless AI innovations in startups and under-resourced communities might never see the light of day. Ratio1’s mission hits multiple “U’s,” which gave us confidence that we’re working on something truly valuable (not just a nice-to-have).
Talk to Users - Don’t Pitch Technology
Before writing a single line of code, we spoke to AI developers, data scientists, and startup founders about their pain points. We asked things like: “What’s your #1 headache in deploying AI right now?” The answers we heard - budget-busting cloud bills, ops complexity, data privacy concerns - directly guided our design. This user-first approach kept us from getting lost in our own tech bubble. We weren’t trying to sell people on a fancy decentralized OS for its own sake; we were validating that our solution matched their needs. Those early conversations confirmed the struggle was real (our team’s own background in AI/DevOps told us that, but user validation was key). We only started building after we understood exactly what they needed. In short, we pitched Ratio1 in terms of user priorities (cost, ease, trust), not just tech jargon. By talking to users instead of talking up our technology, we ensured we were crafting a solution to their problem, not ours.
Focus on a Critical Need (Not a Nice-to-Have)
There’s a big difference between a latent pain and a critical pain. We aimed squarely at a mission-critical need: accessible and scalable AI infrastructure for those who currently can’t get it. For our users, this isn’t some “would be cool to have” feature - it’s often the make-or-break factor for their projects. If an AI startup can’t afford to train models, or if a company can’t deploy an AI service without risking outages or bankruptcy from cloud costs, that’s a serious problem. We knew Ratio1 had to solve a gut-level pain: the inability to harness AI due to cost or complexity. By enabling distributed compute at lower cost (and doing so in a way that maintains reliability and compliance), we’re helping prevent “outage-level” catastrophes for these teams. For example, not being able to serve users or iterate on a model because of infrastructure limitations is akin to downtime for a business. The litmus test we used was: does the user feel this problem deeply on a day-to-day basis? In our case, yes - teams feel the burn of cloud expenses, dev bottlenecks, and scaling headaches every single day. That told us the need we’re addressing is critical, not just a nice extra. It kept us focused on building core solutions, not fluff.
Don’t Settle for “Better, Faster, Cheaper” - Be Disruptive
Incremental improvements weren’t enough; we set out to be discontinuous and truly disruptive. Ratio1 isn’t just a slightly cheaper or faster compute platform - it’s a fundamentally new model of deploying AI. We combine blockchain and edge computing to do something that wasn’t possible before. In fact, Ratio1’s architecture turns idle devices (laptops, phones, even cloud VMs) into a trustless global supercomputer. That means anyone can contribute or utilize AI compute across a decentralized network with built-in trust and transparency. Importantly, the network’s permissioned design (nodes are licensed and vetted) adds a layer of reliability that typical “cloud-on-edge” platforms can’t offer. This isn’t just a 2× better solution, it’s a different paradigm altogether. By integrating features like on-chain coordination, decentralized storage, and even homomorphic encryption for data privacy, we created a platform that’s hard to duplicate. We’ve also woven in developer-centric innovations (like native Ratio1 SDKs and low-code tools) that other solutions lack, making our ecosystem even more robust. The defensibility comes from this breadth of innovation and the network effects of our community - nodes, developers, and data providers all reinforce each other in the ecosystem. Bottom line: we aimed for a product that changes the game, not one that just competes on minor improvements.
Make the Gain > 10× the Pain of Adoption
We know developers and companies won’t switch to a new platform unless the benefits overwhelmingly outweigh the effort. So we designed Ratio1 to offer a massive gain with minimal friction. How? For one, the cost savings and access to new compute sources can be dramatic - imagine running your ML tasks on hundreds of idle devices around the world for a fraction of the cost of a single cloud VM. Also, Ratio1 gives you capabilities (like built-in peer-to-peer orchestration, on-demand scaling, and integrated compliance) that you simply can’t get in traditional clouds without huge effort. At the same time, we worked hard to lower the switching pain: our tools feel familiar (a developer can deploy a container or AI model to Ratio1 with a one-liner, much like deploying to Docker or Kubernetes). The platform abstracts away complexity with low-code interfaces and automation, so onboarding is quick and easy - you can stand up an AI microservice in minutes instead of wrestling with weeks of DevOps setup. We also ensure data stays encrypted and nodes are vetted (KYC’d), which eases trust and legal concerns for businesses. All this means the benefit of using Ratio1 - faster go-to-market, orders-of-magnitude cost reduction, new revenue streams for node operators - vastly exceeds the cost (learning a new system or trusting a new network). We set a high bar for ourselves: if we couldn’t offer roughly a 10× improvement, we knew we still had work to do.
By following these six principles, we’ve grounded Ratio1 in solving a real, urgent problem with an innovative solution. It’s not about blockchain, or AI, or edge compute in isolation - it’s about delivering tangible value to users. As we continue to build and evolve, these takeaways serve as our North Star to make sure we stay aligned with what users truly need. In the end, the goal is that when people discover Ratio1, their reaction isn’t “Oh, cool tech.” It’s “Yes - this is exactly the solution to the problem I’ve been facing!” That’s when you know you’re building a product people will actually buy into. And that’s the philosophy driving Ratio1’s journey from a bold idea to a game-changing reality.
Petrica Butusina
Jul 12, 2025