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Patience Is Profit: Can LLM Agents Stabilize DePIN’s Token Rails?

TL;DR — A new framework (EconAgentic) models DePIN growth stages, token/agent interactions, and macro goals (efficiency, inclusion, stability). Its key finding: more patient LLM agents (i.e., slower to exit) can increase inclusion and stability with little efficiency penalty. Sensible—but only if token price formation, data integrity, and geospatial participation are measured rigorously. Why this paper matters DePIN (Decentralized Physical Infrastructure Networks) turns physical capacity—wireless hotspots, sensors, compute, even energy—into token‑incentivized networks. The promise is Uber/Airbnb’s distribution without the platform as rent‑extractor. EconAgentic contributes a general model that: ...

September 1, 2025 · 5 min · Zelina
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Agents of Allocation: Crypto Portfolios Meet Crew AI

In the volatile world of crypto, the only constant is change. This makes portfolio optimization a challenge — especially for traditional strategies that assume stability over time. A new study by Castelli, Giudici, and Piergallini offers a compelling solution: build your investment pipeline out of agents. Using a modular Multi-Agent System (MAS) framework implemented in Crew AI, the authors compare two crypto portfolio strategies over the 2020–2025 period: one static and one adaptive. The system orchestrates specialized agents to ingest, clean, analyze, optimize, and report on daily crypto prices — all in a transparent and auditable way. ...

August 3, 2025 · 3 min · Zelina