From Yapamatico to the cloud: the story, the certifications verified on Credly, and the technical territories I explore.

About me

My AI-DLC accreditations

AI-DLC (AI-Driven Development Life Cycle) organizes AI-assisted development into traceable phases—from intent through requirements, design, construction, and operation—with an approval gate before each step forward.

AI-DLC: AI executes, people decide

With Kiro the starting point is not a chat, it is a specification: requirements, design, and tasks before any code is generated. Steering captures the repository conventions once, and hooks take care of the repetitive parts.

Kiro: the spec as the unit of work

Agents write a lot of code very quickly, and that makes the decisions we cannot delegate more valuable, not less: the boundaries of the system, the trade-offs we accept, and what we are willing to maintain for years.

What AI does not decide

AI stopped being autocomplete and started doing the work. That does not remove judgement: it changes where judgement is needed. These are the three ideas I work with today.

AI stopped being autocomplete and started executing. I work with AI-DLC, which organizes AI-assisted development into phases with an approval gate before each step, and with Kiro, where the unit of work is the specification rather than the chat. What is not delegated: the system boundaries, the trade-offs, and what we are willing to maintain for years.

Building with AI

Good ideas improve when they are shared. Send me an email, or find me on LinkedIn and GitHub.

Continue the conversation

{exams} active certifications and {micro} micro-credentials. Every badge links to its verification on Credly.

{exams} active certifications. Every badge links to its verification on Credly.

Certifications

A story that starts in two small towns in Falcón, passes through a 286, and is still open.

From Yapamatico to the cloud

Technologies and disciplines that shape my work and the questions I develop on this site.

Areas I explore

The best architectures begin with an honest question.

Andrés Aguilar

The four ideas I think architecture through before choosing a technology, and how AI enters the development life cycle: AI-DLC, Kiro, and what is not delegated.

Principles

Technology changes quickly. Purpose and principles help us decide what deserves to endure.

A useful architecture begins by understanding whom it serves, what problem it changes, and which decision it must enable.

Design from purpose

Enduring systems are rarely born complete. They learn, adapt, and improve without turning every change into an all-or-nothing bet.

Evolve incrementally

Building also means caring for what happens next: security, resilience, observability, and operations people can understand.

Operate responsibly

Cost, complexity, and energy are not final details. They are boundaries that can lead to simpler and better solutions.

Efficiency as a creative constraint

How I think

These are not universal answers. They are ideas I use to think more clearly before choosing a technology.

I write to organize ideas, share what I learn, and leave better questions about architecture, cloud, and technology.

What I write

The voting protocol on Ethereum uses Blockchain technology to guarantee data integrity, transparency, and fault tolerance in electronic voting systems. Protocols such as the Open Vote Network (OVN) have been implemented that achieve ballot confidentiality, although they have limitations in terms of computational cost and the possibility of manipulation by the last voter. The use of blind signatures on Blockchain technology makes it possible to obtain voter authorization while preserving anonymity. Although security and privacy challenges remain, it is expected that more secure Blockchain-based solutions for voting systems can be developed in the future.

A Voting Protocol on Ethereum