Why I Chose Astro for This Site
A short rationale for picking Astro over Next.js for a technical blog and portfolio. Spoiler: it's the content layer.
p4blo.dev
Thoughts on AI, security, infrastructure, and building things that work.
A short rationale for picking Astro over Next.js for a technical blog and portfolio. Spoiler: it's the content layer.
Most LLM evaluation frameworks are over-engineered. Here's how I built a lightweight pipeline that caught real regressions in production.
What I've learned from testing LLM security. The attack patterns that work, the defences that don't, and how to think about LLM risk.
Practical lessons from running GPU-heavy ML training and inference workloads on Kubernetes in production.
How we monitor ML models in production. From data drift detection to latency percentiles. The tools and patterns that stuck.
Built an AI-powered contract reconciliation platform that compares deal summaries with legal contracts, identifies risks, and highlights mismatches automatically. Reduced manual review time by over 70%.
Built an internal AI platform for querying company knowledge across documents, SharePoint, and systems using retrieval-augmented generation. Significantly reduced information retrieval time.
Performed AI security research and vulnerability testing on large language models as part of an AI safety research programme. Developed attack scenarios, tested model behaviour, and reported vulnerabilities.
Led modernisation of business infrastructure supporting hundreds of users. Designed automation, security improvements, and cloud integrations.
I'm Pablo. I build AI systems for production environments, test LLM security boundaries, and review technical publications for Packt. I prefer building to planning and writing to presenting.
More about me