You start by framing every trading move as a repeatable loop. In Minara’s Research Loop, you begin with a precise, schedulable question that always returns the same data structure—live market prices, on-chain flows, sentiment, macro indicators. Then you narrow in on one asset and pull six domains (Markets, On-chain, Signals, Derivatives, Predictions, DeFi) in a single prompt. Next you point the system at your own track record so it can grade your sizing, entries and exits. Finally you turn those readings into a hard-numbers thesis—specific entry, exit and risk rules rather than vague ideas. Once you have that thesis, Strategy Studio transforms it into a tradeable spec. You can type a plain-English sentence, fill out a form, drop in a YouTube clip or paste Pine Script and get back a structured strategy. You choose time-series or cross-sectional, or start from one of four templates (Momentum, Mean-Reversion, Arbitrage, Pairs). In seconds it runs a 10+ year backtest with venue-specific fees, slippage, funding and borrow costs—and surfaces drawdowns, volatility cones, exposure maps and out-of-sample checks. You compare return per unit of risk, not just raw gains. Before real capital ever moves, you promote a backtest to paper trading with one click. The same engine, fee model and risk hooks execute your strategy on live data without risking money. If performance holds up, you’ve earned the right to go live. If it doesn’t, you learned which assumptions break in real time. The article promises four more steps—scheduling, execution automation and closed-loop monitoring—but the core is this three-beat anatomy: research, strategy and execution all feeding each other inside one app.