From Stablecoin Decisions to DeFi Radar: Our First Strategic Pivot

After questioning Strategy League, we moved from simulated behavior to a real user task:

I already hold stablecoins. Where should I put them, why, and what could go wrong?

This was a better starting point because capital, intent, and alternatives already existed. The product did not need to manufacture a game before it could help.

A real need is not necessarily a large opportunity

A stablecoin decision assistant could compare yield, liquidity, protocol risk, asset risk, bridge exposure, incentives, and transaction costs. That is genuinely useful. It is also narrower than it first appears.

Many holders do not move funds often. Larger users have established processes. Smaller balances may not justify optimization after gas and switching costs. Recommendations also age quickly, creating a heavy data and monitoring burden.

“Users ask this question” proves that a problem exists. It does not prove that the market is large, frequent, or willing to pay.

The best part was also the hardest part

Rate aggregation is straightforward. Trustworthy judgment is not.

To say one opportunity is better than another, defi.io would need current data, a defensible risk model, transparent assumptions, and a clear way to handle uncertainty. The product would also need to explain why a higher yield might come from token incentives, leverage, duration risk, bridge risk, or a less proven protocol.

This was where the product could create value—and where its liability and operating costs would rise.

Revenue could undermine neutrality

Referral fees and protocol sponsorship looked like natural business models. They also created an immediate conflict. If defi.io recommends the venue that pays most, the decision product loses its reason to exist.

Subscription revenue would align incentives better, but it required enough recurring value to justify payment. We had not established that frequency.

Why Radar became the next answer

The stablecoin tool was constrained by a single asset class and an occasional decision. DeFi Radar broadened the job from “tell me where to allocate” to “tell me what changed and why it matters.”

The distinction was important:

A decision assistant says, “Given your amount and risk tolerance, I recommend this option.”

A radar says, “This changed. Here are the facts, sources, and visible risks. You decide whether to act.”

Radar reduced the pressure to give personalized financial advice. It also created more reasons to return: changing rates, incentives, incidents, governance, and new products.

But the pivot introduced a different risk. We could end up operating a high-cost research feed whose users consumed information without taking action or paying.

Once again, this was a strategic hypothesis, not a market result. We had moved closer to real events and real capital, but still had no proof of retention.

The next rebuttal pushed the product even narrower. If a broad radar was difficult to defend, perhaps defi.io should appear only at the highest-value moment: immediately before a user or agent takes action.