When I joined Airaa, there wasn't a product to improve — there was only an idea: a platform that could help Web3 projects identify genuine contributors from on-chain and off-chain signals. I owned product design end to end, working directly with the founder. Over 18 months we shipped the wrong thing, learned why, and rebuilt around a different question.
- 20K+
- users joined the platform within five months
- 15+
- Web3 projects launched campaigns through Airaa
- $250K+
- in rewards distributed across campaigns
Airdrops were rewarding spam
We didn't have to go looking for the problem — founders and contributors were already arguing about it in public. Three complaints kept surfacing:
- Airdrops pay for volume, not for participation
- Sybil farms make launch metrics meaningless
- Money-gating doesn't fix it; genuine contribution has to be identified
ResearchThe conversations this came from
Rather than run a formal study, I collected the argument where it was already happening. This is the wall I kept: posts from founders, protocol leads, and researchers between October 2023 and February 2025, each one landing on some version of the same complaint — farmers gaming allocations, sybil wallets inflating launch numbers, and no reliable way to tell a real contributor from a hundred wallets belonging to one person.
Read together they pointed somewhere specific. Nobody was asking for a better dashboard; they were asking for a way to know who actually showed up. That framing is what eventually separated Airaa's second version from its first.
The wall — months of the same argument, in public, from people running launches.That third point is the thesis Airaa was built on: if spam can't be priced out, the product's job is earning the signal that tells genuine contribution apart.
We built the wrong thing first
The first version focused on helping users research projects. It aggregated publicly available on-chain and social data into a searchable interface where users could discover projects, analyze sentiment, and explore market activity.
The research platform: explore projects, read sentiment, query the terminal. (3 screens)Although useful, we quickly realized the biggest limitation. Everyone had access to the same public information. The product wasn't creating unique value.
Early explorationsWhat the first version actually shipped
Five surfaces, all built on public data: a Project Explorer for browsing protocols, an AI Research Terminal for open-ended questions, Trending Projects, a Sentiment Dashboard, and Universal Search across the lot.
It worked. That was the problem — it worked exactly as well for us as the same data worked for everyone else. Better visualization of a commodity input is still a commodity, and none of these surfaces gave a project a reason to bring us data nobody else had.
The question that changed the product
The problem wasn't how we displayed information — it was where the information came from.
That changed how we thought about the product. Instead of asking "How can we help users discover projects?", we started asking "How can we help projects discover their most valuable contributors?"
Rather than building another analytics platform, we designed a contributor ecosystem where projects could launch campaigns and reward meaningful participation — which meant Airaa now generated its own contributor data instead of renting everyone else's.
Four surfaces, one loop
Campaigns brought projects in, profiles kept contributors coming back, and each fed the other. The platform reduced to four surfaces serving that loop.
Campaign discovery, a project page, a contributor profile, and the AI terminal. (4 screens)InsightWhat each surface did
Campaign discovery — browse active campaigns, understand rewards and eligibility, and participate without leaving the platform.
Project pages — a dedicated space per protocol holding campaign history, activity, contributors, updates, and reward information.
Contributor profiles — an identity assembled from participation history, rankings, reputation, and achievements, rather than an anonymous wallet address.
AI terminal — the research assistant from v1, kept but re-pointed at Airaa's own contributor data rather than the public feeds anyone could query.
Growth is a product feature
Airaa only worked with an active contributor community, so acquisition couldn't sit downstream of the product as a marketing job. It had to be built into the thing itself.
Aura Score, tier progression, and the profile cards built to be posted. (3 screens)Together these turned engagement into a loop that fed itself: participation earned standing, standing was worth showing, and showing it brought the next contributor in.
InsightThe mechanics behind the loop
Every action on the platform contributed towards an Aura Score, giving users a measurable reputation across campaigns. As contributors earned more points they progressed through tiers, unlocking exclusive rewards, custom visual identities, and collectible profile cards drawn from their X profiles.
A referral system rewarded users for bringing others in. Milestones, profile cards, and achievements were all designed to be posted — personal progress doubling as the distribution channel.
The design constraint throughout: a mechanic had to reward participation worth having. Anything that paid out for volume alone would have rebuilt the spam problem we started from, one layer up.
Where it landed
Over 18 months, Airaa went from an experimental research platform to a contributor ecosystem Web3 communities actually used — projects launching campaigns and distributing rewards, contributors getting a transparent account of what their participation was worth.
What I carry forward
Building Airaa reinforced that early-stage product design is less about creating perfect interfaces and more about reducing uncertainty through continuous iteration. Three ideas shaped how I approach product design today.
Ask where the data comes from, not how it looks. The first version was a competent interface over an input everyone else already had. No amount of design would have fixed that, and eighteen months of polish wouldn't have found it either — the reframe did.
Simplicity wins. The first version exposed too much information. By reducing complexity and focusing the experience around campaigns, contributors, and rewards, the platform became easier to understand and more valuable to both projects and users.
Ship, measure, repeat. Working in a small startup meant designing with incomplete information. Rapid iterations, close collaboration with the founder, and continuous user feedback consistently led to better outcomes than trying to perfect designs before launch.