🪟 Context Windows - minezone · Scour

The Hidden Challenge of Multi-LLM Context Management 💸Affordable LLMs

dev.to·5d·DEV

Beever-AI/beever-atlas: Your First LLM-Wiki Conversation Knowledge Base 💬Prompt Engineering

github.com·2d·DEV

Your RAG Pipeline Retrieves the Right Docs. Your LLM Still Gives the Wrong Answer. Here’s Why. 🔍RAG

pub.towardsai.net

·1d

Chat History Storage Patterns in Microsoft Agent Framework 🗃Browser Storage APIs

devblogs.microsoft.com·5d

#sre #agenticai #rag #mcp #devops #aiarchitecture #platformengineering #aiops #cloudnative ⚡AI-Driven DevOps

linkedin.com·1d·DEV

I Reverse-Engineered ChatGPT's Retrieval Stack. The Bottleneck Isn't What You Think. 💬Prompt Engineering

dev.to·17h·DEV

Text Is the New Binary 💬Prompt Engineering

andreabaccega.com·3d·Hacker News

Prism-Reranker: Beyond Relevance Scoring -- Jointly Producing Contributions and Evidence for Agentic Retrieval 🔍RAG

How to Build a Self-Learning RAG System with Knowledge Reflection 🔍RAG

freecodecamp.org·5d

heymrun/heym: Self-hosted AI workflow automation visual canvas, agents, RAG, HITL, MCP, and observability in one runtime. 💬Prompt Engineering

github.com·2d·DEV

Document-to-Markdown for RAG: Preparing Documents for Your AI Knowledge Base 📝Markdown

dev.to·19h·DEV

RAG vs. Fine-Tuning vs. Prompting: 2026 Strategic Guide 💬Prompt Engineering

endevsols.com·4d·DEV

Qwen3.6-27B-INT4 clocking 100 tps with 256k context length on 1x RTX 5090 via vllm 0.19 📉Model Quantization

huggingface.co·4d·r/LocalLLaMA

DeepSeek-V4 Can Hold Your Entire Codebase in One Context Window and It's Open Source 💸Affordable LLMs

firethering.com·6d·Hacker News

From Static Data to Conversational AI: Building a RAG-Powered Customer Agent (Part 2) 💬AI Code Assistants

dev.to·2d·DEV

Adding a Trust Boundary to a LlamaIndex RAG Pipeline 🦙Ollama

dev.to·1d·DEV

Part 4: Improving Retrieval Quality with Token-Aware Chunking and HyDE 💸Affordable LLMs

github.com·4d·DEV

A Unified View of AI Evolution: From Machine Learning to LLMs, RAG, and Fine-Tuning 💬Prompt Engineering

dev.to·2d·DEV

My RAG Pipeline Was 84% Confident 💬Prompt Engineering

github.com·4d·DEV

Retrieval Augmented Localization Cuts LLM Terminology Errors 17-45% 💸Affordable LLMs

dev.to·1d·DEV

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