2
2
Panama
2+ years of experience
Hi! I’m Miguel Ángel — a young developer(13 years old)who loves building creative projects that mix programming, science, and imagination. I code in JavaScript, HTML, and Python, and I enjoy making simulations, small games, and experimental systems that help me understand how things work. I’m always exploring new ideas in physics and math, and I use coding as a way to bring those ideas to life. My goals are to become a stronger programmer, learn more advanced math, and eventually create larger simulations or AI-powered projects. I join hackathons to challenge myself, learn from others, collaborate, and turn cool ideas into real projects. When I’m not coding, I’m usually studying, tinkering with new concepts, or coming up with my next big idea.

Crowdlike is a personal finance lab where swarms of AI trading agents paper-trade real market data, learn from each other, and compete on leaderboards to help users stress‑test and improve investment strategies with USDC on Arc. Crowdlike lets each user spawn multiple autonomous agents, give them risk and budget limits, and then watch how different behaviors perform across daily, weekly, and monthly windows. Agents can mirror trades, copy strategies, or adapt rules from higher‑performing peers, turning the whole agent population into a live experimentation space for portfolio ideas. Under the hood, Crowdlike uses real price feeds and paper trading so users can explore aggressive or conservative strategies without risking capital in the prototype phase. A scoring and streak system rewards consistency, so agents are ranked not only on raw profit but also on sustained positive performance over time, giving users a clearer signal of which behaviors are robust versus lucky. For the Agentic Commerce on Arc track, Crowdlike focuses on USDC as the base asset and on-chain friendly workflows, preparing for agents that can eventually execute within embedded wallets and trust-minimized approval flows. This connects the behavioral insights layer (how agents act and learn from the crowd) with an execution layer where agents can one day move real value under human-defined safety constraints. Crowdlike is currently a working demo, built in Vercel with testnet USDC flows and CoinGecko market data, so users can safely experiment with the core ideas of crowd-driven AI agents before real money is involved. The team is actively developing new features—tighter risk controls, richer leaderboards, smarter copying modes, and deeper Arc integration—to evolve this prototype into a production-ready agentic finance platform over the next few years.
24 Jan 2026

Crowdlike is a behavioral feedback engine built for the Qubic ecosystem, made to transform raw on-chain activity into clear, emotionally engaging insights. Most users operate in complex ecosystems with no meaningful feedback. Crowdlike solves this by applying behavioral psychology, momentum tracking, and data-driven analysis to help individuals understand how their decisions align with broader crowd patterns. At its core, Crowdlike introduces four fundamental metrics—TES (Trait Echo Score), BSS (Behavior Strain Score), BMS (Behavior Momentum Score), and CFS (Crowd Future Signal). Together, they convert blockchain interactions into an easy-to-interpret behavioral profile. TES measures similarity to behavioral archetypes across the network. BSS evaluates daily intensity and emotional strain through weighted actions. BMS highlights long-term consistency and positive or negative momentum. CFS offers future-oriented, non-prescriptive insights based on what statistically happens to users with similar trajectories. Crowdlike enhances these metrics with responsible psychological design—using near-miss feedback, streak reinforcement, progress illusions, milestone anticipation, intermittent micro-rewards, and carefully tuned visual cues. The goal is not manipulation, but engagement: users receive meaningful nudges that increase awareness, highlight trends, and motivate positive habits. Built for Nostromo and deployable as a Qubic-native protocol, Crowdlike aims to become the ecosystem’s behavioral mirror—a tool that strengthens user understanding, improves decision-making, and unlocks the next generation of feedback-driven blockchain experiences.
7 Dec 2025