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Avoiding Docker-Based TP Setups in Development Workflows
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I tend to avoid docker-based tp setups tbh
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vLLM CUDA Graphs optimization: avoid OOM without eager mode
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PRO TIP vLLM telling you to use `–enforce-eager` to avoid OOM because CUDA Graphs “don’t have enough VRAM”? Don’t jump straight to eager mode Try this first: – lower `–max-model-len`, ex: 4k – let CUDA Graph compile (which will be cached by torch.compile) – restart, then
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Token Security in CLI Tools and MCP Best Practices
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Agree, but with CLI/API being the hype, it's quite common to have those tools save tokens to local files (esp. if they can't store into keychain). I wished more people understood the security implications and used MCPs instead which have a tighter boundary / keys managed well
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Agent Security: Protecting Production Credentials and Backups
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The conclusions here feel wrong to me. The two lessons I see are: 1. Don't run agents anywhere they might be able to access production environment credentials – it's on you to know which credentials those are 2. Keep tested backups that are independent from your production host
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AI Coding Agents and Backup Best Practices for Developers
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“Always keep a separate backup.” For sure, every experienced programmer should know this. 𝘉𝘶𝘵 𝘸𝘦 𝘫𝘶𝘴𝘵 𝘤𝘳𝘦𝘢𝘵𝘦𝘥 𝘢 𝘸𝘩𝘰𝘭𝘦 𝘨𝘦𝘯𝘦𝘳𝘢𝘵𝘪𝘰𝘯 𝘰𝘧 𝘷𝘪𝘣𝘦 𝘤𝘰𝘥𝘦𝘳𝘴 𝘸𝘩𝘰 𝘥𝘰𝘯’𝘵. And we now have a legion of synthetic coding agents (like Cursor) that
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Collaborative Tech Design Support With API Integration Available
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Fresh angles, let's work on it together—we provide tech/design/even API support
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Developer Commits to Open Source Initiative After On-Record Discussion
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I asked him about this on record and his response makes me believe he's committed to opensourcehttps://t.co/g5cP4A5rKw
— Ahmad (@TheAhmadOsman) 27 avril 2026I asked him about this on record and his response makes me believe he's committed to opensource
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Design Multi-Agent AI Systems Using MCP and A2A Framework
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New release from @PacktDataML available at: http://
amzn.to/40Sp4O9 "Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based Agentic AI Framework with tool use, memory, and multi-agent workflows" Table of Contents:
Introduction to Generative AI and AI -
Building 30 Production-Ready AI Agent Systems and Architectures
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30 Agents Every AI Engineer Must Build — Build production-ready agent systems using proven architectures and patterns: http://
amzn.to/41ckg6z v/ @PacktDataML —
What you will learn:
Deploy production-ready agent systems that scale securely and reliably
Use LangChain and