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Explore the agent →Machine learning · AI · Data science
Notes from buildingwith data and AI.
I'm Oswaldo Orona. I write about the systems I build, from retrieval and AI agents to the data work underneath. Read the decisions, explore the results, and inspect the code.
Agents
Systems I built, with code and decisions you can inspect.
Agent
Star Wars embedding atlas
An interactive explorer for fifteen character descriptions, with similarity scores, projection views, and a way to test what changes when you remove their named relationships.
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Agent
ReActReel
A movie and music search agent that turns a remembered line into a playable video, with the tool calls visible beside the result.
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Agent
Masking before the agent handoff
A database transfer workflow that masks customer fields before rows reach an agent or its mailbox.
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Agent
Mexico City transit assistant
A conversational transit map that resolves places and asks a routing engine to calculate the journey.
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Agent
Memo Ocho Bits
An AI participant in a World Cup prediction pool, with saved forecasts and a leaderboard scored alongside human players.
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Agent
Investigating the Gulf oil spill
A geospatial investigation built to challenge the Mexican government’s account of the oil spill using vessel records, satellite layers, and dated statements.
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Agent
The blog as an MCP server
A public MCP endpoint that lets an assistant search the blog, browse its catalog, and retrieve complete articles.
Explore the agent →Library
Projects, analysis, and explanations of the systems I work with.
ReActReel: finding a movie scene or song from a remembered line
A Gemini agent searches for movie scenes and songs, shows its tool calls, and returns a YouTube result inside the app.
AI agentsReActGemini+1
Sep 22, 20266 min read
I Built a Transit Assistant That Has to Calculate the Route
A Gemini agent connects to MCP tools backed by PostGIS and pgRouting. The interesting part is resolving a place, choosing stations, and showing where the answer came from.
Sep 21, 20267 min read
Turning This Blog Into an MCP Server
I exposed the blog’s retrieval system as three read-only MCP tools. The implementation is small enough to inspect, and the same search tool appears in recorded agent sessions.
Jul 5, 20268 min read
I Put an AI in My World Cup Pool. Here Is What I Can Measure.
A grounded prediction agent competed under the same scoring rules as people. The published group-stage chart reports 47 correct outcomes from 72 picks; here is the implementation and what that result still needs to establish.
Jun 28, 20267 min read
Two Pi Agents and a Customer Table: Masking Before the Handoff
I put masking inside the producer’s data tool, then limited the tools that agent could call. Here is the code, the synthetic example, and the boundary this proof of concept actually provides.
Jun 8, 20266 min read
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About
I'm Oswaldo Orona, a Principal Database Administrator and AI practitioner based in Denver, CO. I hold an MCS-DS from UIUC (Tau Beta Pi, Phi Kappa Phi) and bring 25+ years of database experience alongside deep hands-on work in machine learning and AI engineering.
My focus areas include Retrieval-Augmented Generation (RAG), AI agents, Model Context Protocol (MCP), geospatial AI, and financial AI, all running in a self-hosted Proxmox home lab with Docker and LXC.
This blog is where I document explorations in latent space: the ideas, experiments, and systems that live between the data and the model.
ML & AI
- PyTorch
- TensorFlow
- RAG
- NLP
- Computer Vision
- LLMs
Databases
- PostgreSQL
- Oracle
- Redis
- pgvector
- DynamoDB
Infrastructure
- Docker
- Proxmox
- Ansible
- AWS
- Linux
Languages
- Python
- R
- SQL
- PL/SQL
- Java
- Bash
Ask about Oswaldo
Explore my experience through a conversation. Ask how I built a project, find out about my background, or discuss where my skills fit your team.
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