
Building AI agents: A 10-page ebook overview
Building AI agents: Discover a concise 10-page ebook that covers core concepts, step-by-step guidance, and sample LangChain/LangGraph code

Building AI agents: Discover a concise 10-page ebook that covers core concepts, step-by-step guidance, and sample LangChain/LangGraph code

Developed by a Gen Z team at TUT Brand, xBook uses AI and computer vision to transform ordinary smartphones, tablets and laptops into interactive learning tools — without requiring expensive dedicated hardware.

Claude prompt audit helps identify and remove legacy instruction patterns in CLAUDE.md and AGENTS.md, ensuring compatibility with Opus 5.5 and newer

Spotify token cost reduction cut spend by 90% by sending simple I/O jobs to cheaper models while keeping Claude for complex debugging.

The JEV Coding Agent harness design PDF offers a concise 12-page guide on building efficient coding agents, essential for developers.

RedAmon AI pentest automates vulnerability discovery, exploitation ranking, code remediation and creates a Pull Request, all in a single Docker

DeepSeek V4.1 Flash delivers near-top AI performance with low memory use, offering 552B parameters, 1M token context, and benchmark scores.

Anthropic engineer Lamis Mukta highlights the shift towards building self-prompting AI systems with persistent memory, moving beyond manual

self-prompting AI system enables Claude agents to manage their own prompts, reducing manual effort and improving scalability.

Discover how to run AI locally with 10 GitHub repositories that enable LLMs, image generation, and speech recognition on your own computer.
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