Articles tagged “llm”
16 articles
12 Ways Your LLM Judge Is Lying to You
Research identifies 12 systematic biases in LLM-as-a-judge systems. Learn to detect and mitigate each one before they corrupt your eval pipeline.
A 7B Domain Model Beat Everything We Tried
Domain-specific language models are beating trillion-parameter generalists on vertical tasks. Here's when a 7B model is the right call, how the training pipeline works, and what production teams are shipping today.
Fine-Tune a 7B Model for $1,500 (Not $50,000)
Full fine-tuning costs $50K in H100s. QLoRA on an RTX 4090 costs $1,500. Learn how LoRA and QLoRA let you train only 0.1-1% of parameters with nearly identical results, with working code for fine-tuning models that understand your agent's tool schemas.
A 1B Model Just Matched the 70B. Here's How.
How to distill frontier LLMs into small, cheap models that retain 98% accuracy on agent tasks. The teacher-student pattern, NVIDIA's data flywheel, and the Plan-and-Execute architecture that cuts agent costs by 90%.
Why Your AI Bill Is 30x Too High
Small language models match GPT-3.5 at 2% of the size and 95% less cost. Benchmarks, code, and a migration story from $13K/month to $400.
Your AI Agent Costs $13K/Month. Here's the Fix.
A production customer-service agent burned $13,247 in one month. Prompt caching, model routing, batch processing, and plan-and-execute architecture cut it to $1,100. Real pricing math for every technique.
Zero-Shot o sin oportunidad? Como los agentes de IA manejan llamadas que nunca han visto
Cuando un cliente llama con una solicitud que tu agente de IA nunca ha encontrado, que pasa realmente? Desglosamos la mecanica del manejo zero-shot y como probarlo antes de que falle en produccion.
Claude 4.6 broke our production agent in two hours — here's what's worth the migration
A practical developer guide to Claude 4.6 — adaptive thinking, 1M context, compaction API, tool search, and structured outputs. Real code examples in TypeScript and Python for building production AI agents.
IA Conversacional vs. IA Agentiva: Cual es la diferencia y por que importa para equipos de CX
La IA conversacional sigue scripts. La IA agentiva persigue objetivos. Aqui esta la diferencia exacta, con una comparacion lado a lado y una guia practica para elegir el enfoque correcto para experiencia del cliente.
Multimodal AI Agents: Voice, Vision, and Text in Production
How to architect multimodal AI agents that process voice, vision, and text simultaneously — from STT→LLM→TTS pipelines to vision integration, latency budgets, and production fusion strategies.
Fine-tuning vs RAG: why most teams pick wrong and how to decide
When to fine-tune, when to use RAG, and when you need both — with hands-on LoRA fine-tuning and RAG implementation on the same task to show the difference.
Como evaluar agentes de IA: construye un framework de evaluacion desde cero
Construye un framework funcional de evaluacion de agentes de IA en TypeScript y Python. Cubre LLM-as-judge, puntuacion por rubrica, pruebas de regresion e integracion con CI.
Prompt Engineering desde Primeros Principios: 12 Técnicas que Todo Desarrollador de IA Necesita
Domina 12 técnicas esenciales de prompt engineering con ejemplos reales en TypeScript. Desde zero-shot hasta ReAct, construye mejores agentes de IA desde primeros principios.
How Multimodal Voice AI Works: From Audio-Only to Vision-Aware Agents
How multimodal voice AI combines speech, vision, and text into a single agent — architecture patterns, latency tradeoffs, and TypeScript code you can run.
How LLMs Changed Agent Training Forever: From Writing Rules to Writing Prompts
LLMs didn't just improve agent training. They changed the entire discipline. Here's what actually shifted, what works in production, and what the industry still gets wrong.
Prompt engineering vs. context engineering: What's the next step for voice AI?
While prompt engineering focuses on perfecting inputs, context engineering optimizes the entire conversation environment. Discover why context engineering is becoming the key differentiator in voice AI.
Aprende IA Agéntica
Una lección por semana: técnicas prácticas para construir, probar y lanzar agentes IA. Desde ingeniería de prompts hasta monitoreo en producción. Aprende haciendo.
