Articles for builders: architecture, code and integrations explained in detail.
Six essential artificial intelligence concepts explained with technical clarity: how text is tokenized, vectorized, retrieved, and connected to external tools.
What a large language model (LLM) is, how it processes tokens through transformers, its real hallucination and context limits, and how to integrate it in production systems with RAG.
Almeebar uses Django REST and PostgreSQL; BIT Project, BIT Talents and our CMMS use React and Supabase. The criteria we use to choose backends for each project.
Patterns we use to replace production systems that cannot go down: strangler fig, shadow traffic, continuous data synchronization, and rollback in minutes.
How we integrate billing record submission to the Spanish Tax Agency (AEAT) in a production ERP: architecture, chained hash, queues, and real-world errors.
