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brew install make

git clone https://github.com/ggml-org/llama.cpp

cd llama.cpp

cmake -B build

cmake --build build --config Release -j $(sysctl -n hw.ncpu)

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Boris Cherny (the creator of Claude Code) 15 rules and the 6-step system, alongside advanced workflows, officially recommended best practices, and deep-dive strategies.

1. The Core Execution Engine (System Setup)

• Parallel Workspaces: Run 5 to 15 Claude instances simultaneously across different terminal directories. Number your tabs 1-5 and use system notifications to ping you when an agent finishes a task or needs input.
• Auto Mode: Use a classifier to automatically approve safe commands, allowing you to run multiple agents in parallel without constantly babysitting them.
• Permission Management: Use the "fewer permission prompts" skill, which scans your history and whitelists common safe commands to reduce repetitive approvals. Seasoned users also alias Claude (e.g., alias cc='claude --dangerously-skip-permissions') to stay in a flow state.
• Adaptive Effort Levels: Rely on the "extra high" default effort level. The model adaptively decides how much "thinking" a task requires, whi

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OpenClaw: Personal AI OS — Video Supplement

A complete reference guide to the systems, pipelines, and prompts demonstrated in the YouTube video by Matt (Peter Steinberger) 📺 Watch the original video

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Acknowledgement

All system designs, prompts, pipelines, and concepts in this document are based on the original work of Matt (Peter Steinberger) as presented in his YouTube video. This document is a fan-made educational supplement intended to help viewers follow along, implement, and extend the ideas he shared. The original prompts and ebook are available via links in the video description. Please support the creator directly on YouTube and through his linked resources.

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Open-Source RAG Ecosystem:

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Retrieval & Ranking

• FAISS — https://github.com/facebookresearch/faiss
• Weaviate — https://weaviate.io
• Haystack Retrievers — https://haystack.deepset.ai
• JinaAI Rerankers — https://jina.ai
• Elasticsearch KNN — https://www.elastic.co

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1. Project overview

• Goal: A small but realistic “Agent‑maintained service”: a REST API for a Task Manager (users, projects, tasks) where:

  • Agents build most features.
  • Repo is structured for agent-first work.
  • Background agents do “garbage collection” on code and docs. vercel

• Stack (boring, well-known tools):

  • Backend: Spring Boot 3.x → later upgrade path to 4.x.
  • DB: Postgres.

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microGPT Architecture — Complete Guide

A comprehensive walkthrough of Andrej Karpathy's microGPT: the "most atomic" GPT implementation using pure Python and math only — no PyTorch, no NumPy, no GPU.

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A huge traditional bank (State Street) and major market infrastructure players (DTCC, Galaxy, WisdomTree, etc.) are starting to use Stellar’s blockchain for “tokenization” – turning traditional financial products into digital tokens – and this could make Stellar (XLM) an important hidden player in future finance.[1][2]

Key news

• State Street and Galaxy are launching a new tokenized cash fund called the State Street Galaxy Onchain Liquidity Sweep Fund (SWEEP).[3][1]

• The fund aims to let big investors move cash into and out of a blockchain‑based fund 24/7 using PayPal’s PYUSD stablecoin.[4][1]

• It is expected to launch with about 200 million dollars in seed capital from Ondo Finance and will start on Solana, with Stellar and Ethereum planned as next chains, using Chainlink for cross‑chain connections.[5][1][4]

• Nadine Chakar, a senior executive who moved from State Street to Securrency (later acquired by DTCC) and is now **Managing Director and Global Head of D

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Complete Learning Guide: Building Enterprise Blockchain Applications with R3 Corda

A Comprehensive Path from Theory to Implementation

This unified learning guide combines structured video-based learning with hands-on implementation, providing a complete path to mastering R3 Corda—an open-source distributed ledger technology (DLT) designed for enterprise use cases like finance, supply chain, and healthcare.

Based on: Six-part YouTube video series by Telusko (Naveen Reddy), uploaded April-May 2021.

Prerequisites:

• Basic Java or Kotlin knowledge (Corda runs on JVM)
• Java 8 JDK (specifically Java 8 - Oracle, Amazon Corretto, or OpenJDK)

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The Dawn of the Post-LLM Era: Five Breakthroughs Poised to Revolutionize Artificial Intelligence Over the Next 18 Months

Abstract

Large Language Models (LLMs) have dominated the AI landscape, enabling unprecedented natural language processing capabilities. However, their autoregressive architectures, quadratic scaling limitations, and rigid reasoning paradigms are reaching inflection points. This whitepaper synthesizes emerging research and innovations that signal the retirement of traditional LLMs, forecasting a paradigm shift by 2026. We examine five key breakthroughs: Diffusion LLMs for efficient generation, Power Attention for scalable context handling, latent-space thinking with private chains of thought, Nested Learning for continual adaptation, and Continuous Thought Machines as a foundational departure from Transformers. Drawing from expert interviews, academic papers, and prototypes, we argue these advancements will yield 10x inference speeds, infinite-context reasoning, unsupervised internal

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Coins and tokens are both crypto assets, but coins run on their own blockchain while tokens live on top of someone else’s blockchain and usually represent a specific project or use case.[1]

What a coin is

• A coin is the native asset of its own blockchain and is used to pay transaction fees and secure the network (e.g., BTC on Bitcoin, ETH on Ethereum, BNB on BNB Chain).[1]
• Creating a coin means building and maintaining a full blockchain infrastructure, like buying and maintaining your own gym equipment or car instead of using someone else’s.[1]

Example:

• Bitcoin (BTC): Native coin of the Bitcoin blockchain, used mainly as digital money and store of value.
• Ether (ETH): Native coin of Ethereum, used to pay gas fees and secure the network.