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AI

Hands-on guides to LLMs, agents, prompt engineering, and the AI tools Botmonster runs every day for real work, not demos.

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Building multi-step AI agents with LangGraph

Building multi-step AI agents with LangGraph

Build production-grade AI agents with LangGraph's graph architecture. Add self-correction, memory management, and multi-agent patterns to Python apps.

High-end gaming desktop with illuminated NVIDIA GPU visible through a glass side panel, surrounded by floating holographic neural network diagrams and data streams

Run Llama 4 Scout locally: 24GB VRAM, GGUF, real speeds

Run Llama 4 Scout locally with Unsloth dynamic GGUF. Real VRAM by GPU, which quant fits 24GB, Ollama vs llama.cpp, and honest tokens per second.

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Popular

Three roped climbers ascend a cliff whose contour lines form a topographic curve over stacked memory chips at the base.

Local image models in 2026: Qwen vs FLUX vs SDXL on VRAM

Compare the best local image generation models on text-in-image accuracy, prompt adherence, VRAM, speed, and license to find your sweet spot.

A glowing desktop graphics card streams data into a landscape painting on an easel beside VRAM and wattage gauges

Run FLUX 2 locally in 2026: VRAM by GPU + ComfyUI setup

Run FLUX 2 locally in ComfyUI. VRAM by GPU from 8GB to 24GB, GGUF builds, the variant that fits your card, cost versus cloud, and the files to grab.

RTX 5080 vs. RTX 5090: the best GPU for local AI workloads in 2026

RTX 5080 vs. RTX 5090: the best GPU for local AI workloads in 2026

Compare the RTX 5080 and 5090 for local AI in 2026: LLM inference benchmarks, image generation speed, power draw, and a clear value verdict.

Brass lighthouse on a rocky coast shining an orange beam at dusk as small sailboats turn back toward it

Opus 5.5 is the Claude comeback Reddit was waiting for

Opus 5.5 Reddit threads call it the Claude comeback. It finally talks like a person, limits stretch further, and Fable 5.1 still wins some coding tests.

Running Gemma 4 26B MoE on 8GB VRAM: three strategies that work

Running Gemma 4 26B MoE on 8GB VRAM: three strategies that work

Run Google Gemma 4 26B MoE on a budget 8GB VRAM GPU using aggressive quantization, GPU-CPU layer offloading, and tensor parallelism. Full setup guide.

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Make Opus 5 less verbose with an output style and a hook

Make Opus 5 less verbose with a custom output style, a UserPromptSubmit hook, and fewer CLAUDE.md rules. The env var everyone shares backfires.

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