Esneider Bravo Benitez

Esneider Bravo Benitez

Software Engineer @ Muno Labs

About

Software Engineer with more than 8 years of experience building scalable, high-impact technology platforms, especially in the fintech sector. I am passionate about creating efficient solutions, leading technical teams, and promoting an innovation culture focused on real results. I currently have an AI-First focus, integrating Artificial Intelligence into products and processes to optimize operations and accelerate companies' technological evolution. Throughout my career I have worked on software architecture, platform scalability, process automation, and technical leadership of multidisciplinary teams. I want people to know me for my ability to transform complex ideas into scalable, efficient, future-oriented technology solutions. I am passionate about combining engineering, innovation, and artificial intelligence to build products that generate real impact and help companies grow sustainably.

Workshop

Artificial IntelligenceCore Python

Beyond Vibe Coding: Spec Driven Development with Code Graphs

FORMAT: WorkshopLEVEL: IntermediateLANGUAGE: Spanish

Artificial intelligence is changing the way we build software, but writing prompts and accepting code suggestions is not enough to work on real systems. In applications with multiple layers, dependencies, and business rules, the real challenge is not just generating code, but understanding where to change it, how it impacts the system, and how to validate it correctly. In this workshop you will explore an evolution of Spec Driven Development using Code Graphs as a structured context source. Starting from a web application built with FastAPI, you will work on a specific feature following a guided flow: requirement, specification, graph context, planning, tasks, implementation, and validation. During the session you will learn the Spec Driven Development flow, from defining the requirement to creating the specification, planning, generating tasks, implementation, and validation. You will also see how a code graph can represent files, functions, classes, relationships, and dependencies, allowing AI not to depend solely on textual context or isolated prompts. This will help you reduce common errors such as duplicating logic, modifying incorrect layers, or ignoring affected tests. Upon completion, you will understand how to move from improvised use of AI in development to a more structured, traceable, and reliable process. You will learn to combine specifications, real code context, and AI assistance to build software with greater technical clarity, better impact validation, and logic applicable to real projects.

Esneider Bravo Benitez

Esneider Bravo Benitez

Software Engineer @ Muno Labs

Jonathan Vallejo Muñoz

Jonathan Vallejo Muñoz

Senior Director of Software Engineering @ Lendingfront

View talk

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