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AI Developer Tools: The Complete Guide to AI-Powered Development

August 24, 2026

Explore the modern AI developer tools ecosystem: AI coding assistants, GitHub Copilot, Claude Code, OpenCode, DevOps automation, GitOps, VS Code workflows, GitHub Actions, and programming language trends. AI Developer Tools: The Complete Guide to AI-Powered Development

A case-study exploration of OpenClaw — a self-hosted AI assistant system that integrates local LLMs, retrieval, memory, routing, and observability into a cohesive local infrastructure. OpenClaw: Examining a Self-Hosted AI Assistant as a Real System

LLM Performance in 2026: Benchmarks, Bottlenecks & Optimization

February 21, 2026

LLM performance is not just about having a powerful GPU. Inference speed, latency, and cost efficiency depend on constraints across the entire stack: Model size and quantization VRAM capacity and memory bandwidth Context length and prompt size Runtime scheduling and batching CPU core utilization System topology (PCIe lanes, NUMA, etc.) This hub organizes deep dives into how large language models behave under real workloads — and how to optimize them. What LLM Performance Really Means Performance is multi-dimensional. Throughput vs Latency Throughput = tokens per second across many requests Latency = time to first token + total response time Most real systems must balance both. The Constraint Order In practice, bottlenecks usually appear in this order: VRAM capacity Memory bandwidth Runtime scheduling Context window size CPU overhead Understanding which constraint you’re hitting is more important than “upgrading hardware”.

Curated List of Articles about Coding in Python:

January 14, 2026

Architecture and Design Patterns, Modern Package Management, Building Production-Ready APIs, AI, RAG and LLM Integration, Data Science and Analysis, Document Processing and Web Scraping, Testing, DevOps Deployment: Curated List of Articles about Coding in Python #python, #coding #dev #devops #datascience #ai #rag #llm #architecture #web #testing

Open WebUI: Self-Hosted LLM Interface.

January 11, 2026

Complete guide to Open WebUI: a powerful self-hosted web interface for Ollama and OpenAI-compatible APIs with RAG, multi-user auth, and Docker deployment. https://www.glukhov.org/post/2026/01/open-webui-overview-quickstart-and-alternatives/ #AI #LLM #Ollama #Docker #SelfHosting #OpenSource #Python #K8S

How to rerank documents with Embedding models

September 30, 2024

How to rerank documents with Embedding models & similarity calculation in RAG: https://www.glukhov.org/post/2024/09/reranking-with-embedding-models #LLM #AI #Ollama #RAG #Embedding

Move Ollama Models to different location

September 29, 2024

After installing ollama better to reconfigure ollama to store them in new place right away. So after we pull a new model, it doesn’t get downloaded to the old location. Ollama is a text-based frontend to LLM AI Models and an API that can host those too. Install Ollama Goto https://ollama.com/download To install Ollama on linux: curl -fsSL https://ollama.com/install.sh | sh Ollama on Windows is on page: https://ollama.com/download/windows Ollama for Mac is there too: https://ollama.com/download/macOllamaSetup.exe Download, List and Remove Ollama models To download some Ollama models: Go to Ollama Library (https://ollama.com/library) and find the model you need, there you can also find model tags and sizes. Then run: ollama pull gemma2:latest # Or get slightly smarter one still nicely fitting into 16GB VRAM: ollama pull gemma2:27b-instruct-q3_K_S # Or: ollama pull llama3.1:latest ollama pull llama3.1:8b-instruct-q8_0 ollama pull mistral-nemo:12b-instruct-2407-q6_K ollama ...