📰 Dev.to · Alan West

Quantizing a model with multi-token prediction heads? Here's why standard conversion pipelines drop them silently, and how to preserve and calibrate them.

LLMs produce confident-looking but geometrically broken OpenSCAD code. Here's why spatial reasoning fails and how to fix it with structured intermediates.

Why local LLM inference hits OOM errors even when the model 'fits' in VRAM — and how to fix it with quantization, KV cache tuning, and allocator config.

Notes from migrating production workloads between closed LLM APIs and open-weight models like Qwen, with code, gotchas, and honest tradeoffs.

Stop runaway LLM agent loops with hard iteration caps, tool-call deduplication, embedding-based loop detection, and forced-decision prompts.

Comparing Gemini 3.5 Flash, Claude Haiku 4.5, and GPT-4o mini with migration code and honest tradeoffs from production use.

Public LLM safety benchmarks lie about your real risk. Here's how to build a reproducible eval harness, write domain probes, and gate it in CI.

Why MTP often fails to speed up llama.cpp inference, and how to debug acceptance rate, VRAM pressure, and CUDA graph capture issues.

Why prompt engineering hits a wall for tone and behavior control, and how to extract and apply activation steering vectors with PyTorch hooks.

Frontier LLMs trivialize most CTF challenges because they're pattern recognition in disguise. Here's how to design challenges that actually hold up.

Local LLM knowledge base giving bad answers? The fix is almost always the retrieval layer. How to debug chunking, embeddings, and reranking.

A hands-on comparison of TextGen and LM Studio for running local LLMs, with migration steps and honest tradeoffs from real usage.

A grounded look at TokenSpeed, the new LLM inference engine trending on GitHub, plus a practical benchmark you can actually run yourself.

A practical, layered approach to catching hallucinations and confidently-wrong outputs from LLM features in production — with code.

Step-by-step guide to solving GPU memory issues when self-hosting Mistral Medium 3.5 128B with vLLM, tensor parallelism, and smart configuration.

Learn how to debug LLM applications in production with tracing, evaluation pipelines, and output guardrails to catch hallucinations and failures.

Local LLMs for coding keep producing broken code? Here's why quantization, context limits, and prompting cause failures — and a step-by-step fix.

Comparing open-source LLMs you can run locally today — Llama, DeepSeek, Qwen, Mistral — instead of waiting for Grok 3 to maybe go open-source.

AI image models have always mangled non-Latin text. OpenAI's gpt-image-2 uses reasoning to fix that. Here's how to build with it.

Stop evaluating LLMs with vibes. Here's a practical framework for benchmarking open-source models against your API provider using real production data.

Comparing Qwen 3 and Llama 3 for local inference — configuration tips, migration steps, and honest benchmarks from real-world testing.

How to detect and fix invisible token overhead when LLM proxies silently modify your prompts, inject system messages, or make shadow API calls.

Fix the robotic, corporate tone in LLM-powered features using system prompt engineering. A practical guide to eliminating AI slop.

Learn how CPU offloading, activation checkpointing, and smart memory management enable training 100B+ parameter LLMs on a single GPU.