In May 2026 I started ARIB Research: one research workflow that puts macro, derivatives, on-chain data, news sentiment and technical structure side by side. Five tools later, these are the lessons that changed how I build.
1. Start from a question you can't answer quickly
Every tool began as a question I kept asking while trading. "Is the macro backdrop helping or hurting risk right now?" became Crypto Macro Intelligence. "Is positioning crowded?" became Crypto Derivatives Intelligence. A tool built from a real question has an obvious first screen; a tool built from a dataset doesn't.
2. One number, then the reasons
Traders don't want twenty charts. Each tool leads with a single summary, such as a 0–100 score or a regime, and then shows exactly which inputs moved it. The summary gets attention; the explanation earns trust.
3. Show your track record, even when it's unflattering
The narrative and sentiment tool keeps a public record of how its index has scored against price. A signal that hides its hit rate is asking for blind trust. Publishing it also keeps me honest about what works.
4. Say what the numbers are not
Every tool states plainly that it describes conditions and is not a forecast or financial advice, and notes how fresh and complete its data is. That isn't legal decoration; it sets the right expectations for how to use the numbers.
5. Free public data goes further than you think
Exchange APIs, public news feeds, on-chain data and macro releases cover most of what a trader needs. The work is in cleaning, scoring and explaining that data, not in finding a secret source.
6. Building it yourself makes you a better PM
Owning the whole stack, from data pipelines to the interface, taught me what every "small" feature really costs. That shows up in my day job at iTechGemini: my estimates got better and my feature lists got shorter.
This article is for education only and is not financial advice. Markets are volatile; do your own research and manage your risk.
