#self-hosted AI memory
178 related articles
·2 min
Production LLM Deployment Guide: Model Selection, GPU Configuration, and Inference Engine Breakdown
A comprehensive decision framework for production LLM deployment: model selection (open-source vs. API), GPU VRAM configuration, and inference engine comparison including vLLM and TensorRT-LLM.
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·2 min
Hombre: An Open-Source Visual Dashboard for Honcho AI Memory Server
Hombre is an open-source web GUI for self-hosted Honcho AI memory servers. Features workspace management, semantic search, real-time sync, and RBAC — built with FastAPI and native frontend, MIT licensed, Docker-ready.
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·4 min
TigrimOSR: An Open-Source Agent Framework in Rust with Configurable Agent Loops
TigrimOSR is an open-source multi-agent system written in Rust, supporting full agent loop definition via YAML config files with only 250MB memory usage. A deep dive into Loop Engineering, Rust advantages, and self-hosted Agentic AI.
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·6 min
The Eight-Step Method for Agent Development: A Practical Path from Pitfalls to Production
Many enterprises fail at AI Agents due to choosing the wrong tools and lacking methodology. This article outlines an eight-step Agent development method—from cognitive foundations, scenario selection, hand-writing ReAct, and structured output to Tool Use, RAG, evaluation sets, and production fallback.
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·3 min
The Complete AI Agent Development Workflow: A Seven-Step Guide from Requirements Analysis to Deployment
Want to build an AI Agent but don't know where to start? This guide covers the complete seven-step workflow—from requirements analysis, platform selection, prompt engineering, data storage, and UI building to testing and deployment.
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·6 min
Home Self-Hosting Server Setup Guide: Building a Private Cloud Ecosystem from Scratch
One 32GB server, 8 hours to build a complete home self-hosting ecosystem. This article details the selection logic behind core services like Jellyfin, Forgejo, Immich, and Ollama, plus infrastructure setup essentials for Nginx Proxy Manager and Podman Compose.
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·4 min
AI Agents Powering the Full Research Pipeline: A Practical Guide to Automation from Topic Selection to Publication
Learn how to use AI Agents to link the entire research pipeline—from literature management, data analysis, and paper writing to scientific illustration and dissemination—building a reusable research automation workflow with NotebookLM, N8N, and Ollama.
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·7 min
OpenClaw vs Hermes: An In-Depth Comparison and Selection Guide for AI Agent Tools
An in-depth comparison of OpenClaw and Hermes Agent, covering skill management, memory mechanisms, security, and gateway configuration to help you find the right AI agent solution.
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·4 min
AI Persistent Memory Three-Layer Architecture Explained: In-Depth Comparison of Mem0, Zep, and ContextNest
Deep dive into the three-layer architecture of AI persistent memory systems—storage, management, and retrieval—with an in-depth comparison of Mem0, Zep, and ContextNest to help developers choose the right memory solution for AI Agents.
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·5 min
GLM-5.2 Hands-On Review: A 753B-Parameter Open Model That Beats GPT and Claude on Value
In-depth hands-on review of Zhipu AI's flagship GLM-5.2: a 1M-token context window and API pricing just one-fifth of GPT/Claude. Covers website building, Chrome extensions, 3D game cloning, and agentic workflows.
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·7 min
Base44 in Practice: How Claude Code Powered Rapid Scaling from 1 to 80 People
How Base44's product team scaled from a single founding engineer to an 80-person team with Claude Code. Covers AI-assisted onboarding, code review, user evaluation, and QA automation.
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·6 min
GPT-5.6 Now Widely Available: The Era of Three-Tier Models and Multi-Agent Orchestration Arrives
OpenAI releases GPT-5.6 (SOUL/TERRA/LUNA), with Ultra mode running four agents in parallel; Meta launches Muse Spark 1.1 with million-token context; ChatGPT desktop unifies Chat, Work, and Codex.
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·6 min
Zuckerberg Says AI Will Run Your Entire Business — But Data Ownership Risks Can't Be Ignored
Meta launched an enterprise AI agent, with Zuckerberg claiming it can "run your entire business." This article explores the commercial value of AI agents, the hidden risks of data ownership, and how different businesses can balance efficiency with data sovereignty.
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·6 min
OpenAI Releases GPT-5.6: Cybersecurity Capabilities Take Center Stage
OpenAI launches the GPT-5.6 model family with cybersecurity as its biggest highlight. A deep analysis of GPT-5.6's differentiation, double-edged-sword effect, and enterprise strategy.
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·4 min
AI Agent Development Deep Dive: Opportunities, Real Entry Barriers, and Learning Paths
A deep dive into AI Agent development: real architecture, entry barriers, and learning paths. From ReAct to multi-agent systems and LangChain — cut through the hype.
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·4 min
Switching Careers to LLM Development: The Four Core Competency Layers Companies Actually Need
Want to break into LLM development but not sure where to start? This guide breaks the core skills into four progressive layers — from basic knowledge to RAG, fine-tuning, Agents, and multimodal — so you can align with real enterprise needs and land the job.
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·7 min
GLM-5.2 Released: Open-Source Coding Capability Approaches Closed-Source Flagships for the First Time
GLM-5.2 tops open-weight models in coding with a 74.4 Frontiers-WE score, beating GPT-5.5. Its MIT license enables local deployment, and the gap with closed-source flagships is closing fast.
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·3 min
Building an AI Auto-Editing Workflow with n8n: Parallel Processing, Date Filtering, and Scheduled Triggers — A Full Dev Log
A complete walkthrough of building an AI auto-editing workflow in n8n: Merge node sync, Luxon date filtering, scheduled triggers, real bugs, and debugging tips for solo creators.
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·6 min
Unsloth Major Update: DeepSeek-V4 Support and a Deep Dive into NVFP4 Quantized Export
Unsloth v0.1.481-beta adds full DeepSeek-V4-Flash support, NVFP4/FP8/imatrix GGUF quantized export, 1.3x faster GRPO, 3-5x faster MoE training, and an OpenAI-compatible API service in Studio.
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·7 min
The Agent Engineer Transition Roadmap: A Deep Dive into Three Core Skill Systems
Want to become an Agent engineer? This article systematically covers three core skill tracks—LLM fundamentals, LangChain architecture development, and enterprise deployment—to help you avoid detours.
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