2026-08-16 Domingo

Notícias de cripto - Página 709

Mantenha-se a par do mercado de cripto. Notícias em tempo real, análises, preços, histórias em alta e análise de especialistas — tudo num só lugar.

Three Frameworks for Ordinary People to Achieve AI Capability Leap: Say Goodbye to the Dilemma of 'Repeating Inputs Every Day'

Summary: This article outlines three frameworks for maximizing AI efficiency, moving beyond basic prompt usage. 1. **Three-Layer Evolution**: Users progress from (1) **Prompt** (one-off instructions, reset each session), to (2) **Project** (context-aware within a specific project), to (3) **Skill** (permanent, auto-applied knowledge). Most users stagnate at the first layer, repeating the same instructions daily with no cumulative improvement. Skills transform the AI from a chat tool into a personalized work system. 2. **Transaction vs. Compound Interest Mindset**: Using prompts is a linear transaction—effort and output are 1:1, and stopping resets progress. Investing time in building Skills is compound interest; a small initial time investment pays continuous dividends, as each Skill permanently elevates the AI's baseline performance. 3. **Thin Harness, Fat Skills**: The system architecture should prioritize thick, well-defined Skills (90% of the value—containing processes, standards, and domain knowledge) and a thin "harness" (the minimal technical environment). Avoid over-engineering the toolchain while neglecting the AI's actual knowledge. Skills are permanent assets that automatically improve with model updates. The key takeaway: Identify tasks you repeat, encode them into Skills (using tools like Claude's Skill Creator), and shift focus from daily prompting to building a compounding, self-improving AI system.

marsbit04/22 06:43

Three Frameworks for Ordinary People to Achieve AI Capability Leap: Say Goodbye to the Dilemma of 'Repeating Inputs Every Day'

marsbit04/22 06:43

VCs on 2025 Crypto Investments: 84% of 118 Tokens Break Issue Price, Only One Type of Company is Quietly Making Money

Crypto investor Ching Tseng categorizes the market into four quadrants based on two axes: crypto-native vs. traditional finance (TradFi)-oriented, and having traction vs. no traction. In 2025, 84.7% of 118 tracked token launches fell below their issuance price, with a median fully diluted valuation drop of 71%. Crypto-native projects without traction are experiencing massive capital destruction, often relying on speculative narratives without sustainable revenue or user retention. Crypto-native teams with traction, often built in prior cycles, generate real revenue but face structural challenges with their tokens lacking direct value capture mechanisms. While some have implemented successful buyback programs, the core issue remains finding growth beyond crypto volatility. TradFi-oriented startups without traction face long, costly enterprise sales cycles but benefit from a robust M&A environment, with crypto acquisitions reaching a record $8.6 billion in 2025. The current winners are TradFi-oriented companies with traction, particularly in the Real World Asset (RWA) tokenization space, which grew from $5.5B to $18.6B in 2025. They are winning through enterprise sales, building alliances, and improving unit economics on established compliance stacks. Their main risk is being bypassed by large incumbent institutions building their own infrastructure. The overarching theme is market maturation, where narrative alone is insufficient for long-term success.

marsbit04/22 03:44

VCs on 2025 Crypto Investments: 84% of 118 Tokens Break Issue Price, Only One Type of Company is Quietly Making Money

marsbit04/22 03:44

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