MirahLabs Engineering Blog
Technical insights, architectural deep-dives, and system designs authored by our product engineers and AI research leads.
Quantization Techniques for LLMs: FP16 to INT4 and GPTQ
Deploying LLMs on local hardware requires massive memory footprint reductions. Learn how post-training quantization techniques like GPTQ and GGUF compress models from FP16 to INT4.
Understanding LLM Hallucinations: Causes, Detection, and Prevention
LLM hallucinations—confidently wrong answers—are the most critical reliability challenge in production AI. Learn why they happen, how to detect them, and architectural strategies to minimize them.
Prompt Engineering: Advanced Techniques for Production LLM Applications
Prompt engineering is the art of communicating with LLMs effectively. Learn chain-of-thought prompting, few-shot examples, structured output, and prompt injection prevention for production systems.
Prompt Injection Vulnerabilities in LLM Applications and How to Prevent Them
Prompt injection allows malicious actors to hijack LLM behavior. Learn how to protect your applications from direct and indirect prompt injection attacks.