01 / AI case · Internal productInternal tool in use
PromptHub
Internal platform that combines editing, multi-LLM testing, and Git versioning to turn scattered prompts into traceable, comparable, governed assets.
AI Engineering specialist for products
I build products,
systems, and knowledge
with Artificial Intelligence.
AI Engineer, technical leader, and educator, combining architecture, experimentation, and product thinking to turn complex technologies into solutions for the real world.
01 / AIModels
Agents · RAG
Agents · RAG
02 / PRODUCTProblem
Planning · Solution
Planning · Solution
03 / LEADERSHIPDecisions
Collaboration · Method
04 / EDUCATIONTrainingCollaboration · Method
Workshops · Talks
Build / Learn / Share
EXPERIENCE AND REACH
Work connected to organizations in technology, education, and business.
Featured work
Projects that solve problems and create results.
02 / AI case · Applied architectureAnonymized solution in a real-world context
Multi-product RAG assistant
RAG-based assistant able to serve different products from specific knowledge bases, preserve context, and hand off the conversation when automation is not enough.
03 / Applied research · CESAR SchoolMaster's research · CESAR School
Engenharia de Prompt, Evals e Confiabilidade
Applied research comparing Prompt Engineering techniques to improve the quality, reliability, and efficiency of solutions based on language models.
04 / AI-first product · Product EngineeringMVP in progress
SpecFlow
AI product studio that turns raw discovery notes into structured specifications, a prioritized backlog, and a risk matrix with literal traceability.
05 / Own product · AI-firstOwn product
Spyke
AI-first product conceived as a lab for integrating Artificial Intelligence, product, architecture, and experience from problem definition through implementation.
06 / AI experiment · Applied RAGPublic demonstration
AskYou
Demonstration chatbot that combines embeddings, vector search with FAISS, and Google Gemini to answer questions from a synthetic knowledge base.
07 / Demonstration product · Applied AIPortfolio prototype
TalentScore AI
Product prototype that organizes resume analysis into scores, strengths, gaps, keywords, and actionable suggestions for people seeking opportunities.
08 / Experimental product · Machine LearningExperimental prototype
InnPricer
Experimental project about hotel pricing with Machine Learning and Artificial Intelligence, connecting data, product hypotheses, and an experience for investigating price.
Specialties
Capabilities that connect product, engineering, and people.
Technology is support. The center is the problem that can be understood and solved.
Active capability/01
01
AI Engineering for products
Turn opportunities, problems, and hypotheses into products and features people can use.
ApplicationFrom a product problem to the first flow a person can actually use.
Tap a specialty to see the details
Active capability/01
01
AI Engineering for products
Turn opportunities, problems, and hypotheses into products and features people can use.
ApplicationFrom a product problem to the first flow a person can actually use.
How I build solutions
A flow that turns intention into evolution.
It is not a rigid recipe. It is a sequence of questions that keeps technology, product, and learning in the same system.
FLOW / 06Click or tap to explore
STEP01
Problem
Understand the context, the person, and the value that needs to be created.
Click or tap to explore
Problem
Understand the context, the person, and the value that needs to be created.
01 / 6Teaching, training, and sharing
Turning knowledge into practical capability.
Corporate training, workshops, and talks on Artificial Intelligence, Prompt Engineering, agents, responsible use, and AI applications in products and processes — adapted to each organization’s context, maturity, and challenges.
Talk about training
IMMERSIVE FORMATS
01
Corporate training
Experiences tailored to the organization’s maturity and challenges.
02
Workshops
Guided practice that turns foundations into the ability to act.
03
Talks
Clarity, context, and real examples to open new conversations about AI.
Technical experience + teaching practice + real-world context.
Build / Lead / Sharean identity in motion
About Leo Teixeira
AI Engineering, product, and knowledge in one path.
Leonardo is an AI Engineer, technical leader, and university professor, working in AI Engineering for products with experience in solution architecture, AI governance, team coordination, and the integration of business, product, and technology.
He specializes in LLMs, Prompt Engineering, intelligent agents, LLMOps, and RAG. As a Master’s student in Software Engineering at CESAR School, he researches Prompt Engineering techniques that improve the quality, reliability, and efficiency of language-model-based solutions.
01Buildproducts, systems, and experiences
02Leaddecisions, people, and evolution
03Shareknowledge with clarity and method
Conversations about AI, products, and what comes next
Let’s talk about AI, products, and good
ideas.
The conversation can start with a professional opportunity, training, a partnership, or simply a good question.