Blog
Writing.
On quality engineering, system design, AI/LLM governance, and the architectural decisions that determine whether systems survive at scale.
2026
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POLQA: Gobernanza de LLMs sin Depender del Vibes Testing
Evaluar modelos de lenguaje en producción no es solo correr benchmarks. Es construir pipelines reproducibles, auditables y agnósticos al proveedor — antes de que el sistema te falle en producción.
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Why the Best IT Architects Come from Quality Engineering
The skills that make you dangerous as a quality engineer are the exact same ones that define great IT architecture. Here's the case — and why that path produces better architects than most.
2025
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Beyond the Job Title: How Engineers Grow in Big Non-Tech Companies
Titles plateau fast in enterprise companies. Real growth comes from expanding your impact radius — from self, to team, to system, to organization. A practical framework for engineers in Tier-2 firms.
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From Engineer to Lead: Architecting Testing as an Organizational System
Becoming an automation lead is not a technical promotion — it's a systemic transformation. From individual contribution to quality orchestration, and what that actually looks like in practice.
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Robot Framework in Agile QA Teams
Robot Framework remains one of the most maintainable open-source automation tools for enterprise Agile teams. Here's why its keyword-driven architecture keeps it relevant — and where it falls short.
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Prompt Engineering: Insights and Misconceptions
Prompt engineering is not about magic incantations — it's interface design for probabilistic systems. Engineers who understand this will have a decisive advantage as LLMs integrate deeper into every technical workflow.
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Prompt Injection: The New SQL Injection
Prompt injection is the #1 vulnerability in LLM applications — and it's not a magic AI flaw. It's a classic input validation failure. Here's how to architect defense in depth for systems built on language models.
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The Testing of the Future: Cloud-Native, Blockchain, and Accessibility
Before, testing software meant making sure the buttons worked. Now it means validating smart contracts, surviving distributed production, and ensuring that a blind person can access your app. The QA of the future is already here.
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Bias, Hallucinations, and Dirty Data: The New QA Frontier
Errors are no longer always in the code. In AI systems, they live in the data, in the model, and in undetected biases — and that changes everything about how we test and govern them.
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Big O: The Language of Scalable Systems
Big O Notation is not just for whiteboard interviews — it's the tool architects use to reason about whether a system survives at scale. A practical guide for engineers who want to design, not just code.