Hey there, I’m Eric Aguayo!
Welcome to my corner of the web!
I’m a senior AI and full-stack engineer based in Quito, Ecuador, and a trail runner at heart. I’m Director of Applied AI at Nimblersoft. I build AI products and help engineering teams bring coding agents into their development workflows. I design and lead agentic development workflows with critical plan review, tests, explicit completion criteria, and traceability between requirements and changes.
I’m available for part-time or per-project contract work, and for mentoring teams and engineers on AI agents. Let’s talk about your project.
Selected projects:
- Vespera: an app to help plan your day and protect your focus, with a suggested agenda and research-informed micro-actions.
- Agent Fabric: open-source tool to install and sync shared agent definitions across OpenCode, Kilo, Codex, Claude Code and more, without overwriting your customizations.
- Artifacts Manager: view and manage agent-generated HTML and Markdown artifacts across projects.
Lately I’ve been writing about what really costs in an agent workflow: not the tokens, but the attention (in Spanish).
This blog is where I share my journey, from tech experiments to trail adventures and everything in between.
Professional AI Solutions
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Latest Posts
Stop Reading LLM Text Walls: Why I Built a Local Artifacts Manager for Agentic Workflows
Reviewing thousands of lines of LLM markdown is a massive cognitive bottleneck. Here is why I moved beyond disposable chatbot canvases and built a persistent, local-first Artifacts Manager for AI agent planning and architecture.
informa-t at MediaHack 2026: AI, Journalism, and the Art of Building in 36 Hours
Reflections, architectural challenges, and lessons learned after 36 hours of multidisciplinary collaboration at MediaHack 2026 building informa-t, an open-source tool combating electoral disinformation with auditable AI.
Beyond the Hype: Why Foundations Outperform "Vibe Coding."
Is your AI strategy built on solid engineering or just lucky prompts? Discover why understanding the math behind the models is the only way to build production-ready AI that scales without the "noise" of the latest trends.
Multi-Agent Systems: Architectural Lessons from the Great Tomb of Nazarick
Is your AI being too "loyal" to be useful? Explore why the "10,000-year plan" in Overlord is actually a masterclass in AI Sycophancy and how to manage the "Cold Logic" of autonomous Multi-Agent Systems.
Why Your "Perfect" Spec Files Are Making Your AI Agents Worse
Is your AI agent hallucinating despite your detailed specs? More context isn't always better. Learn why keeping your spec files lean and delegating to specialized agents is the only way to scale specs-driven development without the "context bloat" trap.
