[ featured · 2026-05-30 ]

>_ Opencode Go vs Claude Code: A real 11-day analysis

$60 in API consumption for a $10 subscription. A real 11-day analysis comparing Opencode Go vs Claude Code: costs, limits, and when it makes sense to switch.

read: ~9min wc: 1945
Opencode Go vs Claude Code: A real 11-day analysis

// recent_posts — latest published

ls -la archive →
[01] 21·May·2026
Demystifying AI First: The Strategic Priority

Demystifying AI First: The Strategic Priority

AI First isn't about putting AI in everything nor an isolated strategy. It's a strategic priority that coexists with Data First, Security First, and Cloud First. The architect's role: ensuring priorities outside the top 5 don't get lost.

~7min
[02] 18·May·2026
Multi-Agent: beyond speed, a strategy to isolate context and optimize costs

Multi-Agent: beyond speed, a strategy to isolate context and optimize costs

When someone starts working with agents, the first instinct is usually to load the main agent with all available skills, all connected tools, and a giant system prompt where you...

~14min
[03] 16·May·2026
HITL in Vibe Coding and IaC: Avoid the Long Bill

HITL in Vibe Coding and IaC: Avoid the Long Bill

In 2026, corporate discourse goes almost entirely in one direction: autonomous agents, full automation, self-healing pipelines. The promise is seductive because it sells. The operational reality is that almost...

~7min
[04] 15·May·2026
Fine-tuning vs. RAG: When Each One Has Real ROI in Production

Fine-tuning vs. RAG: When Each One Has Real ROI in Production

We already saw how to lower inference costs using open-weight models like Qwen 3.5 in the article Reducing Production Costs: Qwen 3.5 on AWS vs Commercial APIs. But once you have the base cost under control, you face another problem: how to give the model specific knowledge about your business.

~4min
[05] 13·May·2026
LLM-as-a-Judge: how to build scalable AI evaluation pipelines

LLM-as-a-Judge: how to build scalable AI evaluation pipelines

Prompts in systems with Large Language Models (LLMs) don't behave like deterministic code. In traditional software development, if you modify a function and all tests pass, you can...

~9min
[06] 12·May·2026
Skills Audit: Protecting Your Infrastructure from Sleeping Payloads

Skills Audit: Protecting Your Infrastructure from Sleeping Payloads

Skills and agents are arguably the best thing that has happened to the AI ecosystem in recent years. A skill is, in essence, a powerful abstraction: it encapsulates knowledge and scripts...

~4min
[07] 16·Apr·2026
Reducing Production Costs: Qwen 3.5 on AWS vs OpenAI

Reducing Production Costs: Qwen 3.5 on AWS vs OpenAI

Technical analysis: AWS SageMaker vs OpenAI. Discover why hosting open-weight models is critical for profitability and latency.

~14min
Antonio Barbosa
// whoami

Antonio Barbosa

Software Engineer

Software Engineer with 19+ years of experience leading the design, development, and scaling of systems at companies like Buk, Walmart Chile, Cencosud, and Globant. My work covers the full cycle: backend architecture, cloud, DevOps, frontend, and recently integrating Large Language Models (LLMs) and agentic AI capabilities in production.

location
Santiago, CL
writes_about
software · architecture · infrastructure · ai · leadership
links
→ linkedin
→ github
→ blog en medium
→ rss
→ buk tech blog