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Desde el 14 de agosto de 2026 Claude Code cambia a modo auto por defecto en Pro Max y Team Esto aumenta en un 25% la cantidad de PRs creados en menos tiempo Para evitar errores hay un fallback automático tras 3 bloqueos seguidos o 20 bloqueos en una

Building trust in enterprise AI means more than flashy results. When AI decisions are explainable, consistent, and aligned with your business logic, it reduces risky surprises like hallucinations or missing audit trails

AI hallucinations are more than a quirky glitch—they pose a serious risk for agencies managing client deliverables. With errors costing businesses an estimated $67.4 billion annually, these inaccuracies eat up hours and damage trust

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Choosing the right business intelligence tool can feel overwhelming. In this post, I break down options like Looker Studio and Metabase, highlighting who they’re best for and what makes them different

Family offices exploring AI tools should be aware that hallucinations—where AI generates inaccurate or fabricated info—can occur in 22% to 94% of outputs. Studies show many AI responses have only about 50% accuracy, with 20% containing material errors

AI hallucinations can quietly drain your agency’s resources, costing businesses up to $67.4 billion annually in errors and rework. When client deliverables contain inaccuracies, teams waste hours tracking down fixes instead of focusing on strategy

Building trust in enterprise AI means more than flashy tech. Explainability and consistency help teams understand AI decisions and keep outputs reliable. Aligning AI with business logic ensures it supports real goals, not random tasks

Shipping AI features is getting more exciting—and challenging—in 2026. With tools like the MCP SDK hitting 97 million downloads a month, more teams are building smarter products that users actually want