Discover the Talks at PyCon Colombia 2026 ✨
Browse every accepted session—titles, tracks, levels, and speakers—before you plan your days in Medellín.
From Voice to Action: Building an AI Assistant with Python and Google Workspace
Jumping between Gmail, Calendar, Drive, and Jira tabs for repetitive tasks is exhausting. That's why we built Attento, an assistant that lets you execute real actions in Google Workspace using natural language. In this talk we build Attento, an end-to-end voice assistant that turns natural language into real actions across Google Workspace. We'll cover architecture with FastAPI, OAuth 2.0 authentication with PKCE, function calling with Gemini, streaming with NDJSON, best practices with uv and Pydantic Settings, and the path from demo to production with Postgres and automated morning briefings.
Juan Manuel Marín Bedoya
Senior Data Engineer @ Huge
Juliana Suárez Ávila
Data Scientist @ Cuesta Partners
How to Find Pearls on the Bottom of the Sea – Autoencoders as Anomaly Detection Models
Like finding pearls on the ocean floor, detecting rare anomalies in large datasets requires sophisticated techniques. In this workshop, you'll learn the theory and practice of autoencoder architectures, how to train them for anomaly detection, how to set decision boundaries, and how to evaluate their performance. We'll work with real-world datasets and build complete anomaly detection pipelines in Python.
Feeding the Invisible: Food Security in Intermediate Cities with Python
In many countries, food insecurity is not only a social problem but also a data problem. In Colombia, key monitoring systems have lost continuity, leaving critical information gaps for public decision-making. This talk presents the development of a Python prototype to build a monitoring and prediction system for food insecurity risk in intermediate cities, using only open data. From a reproducible pipeline, multiple data science components are integrated: ingestion and processing of food price data (SIPSA), time series models for price forecasting (including classical approaches and machine learning like XGBoost), household segmentation through clustering from socioeconomic surveys, construction of a composite index relating income, prices, and vulnerability, and development of a decision support system (DSS) prototype. Attendees will take away a replicable approach for building complex indicators, strategies for working with imperfect open data, ideas for integrating models, socioeconomic data, and visualization in a single system, and a real example of applying Python in public policy and territorial development.
From ETL to Agentic Workflows: The Evolution of Data Engineering in the Generative AI Era
Traditional ETL pipelines are deterministic and rigid. Agentic workflows powered by generative AI can adapt, reason, and handle the unexpected. In this workshop, you'll learn how to evolve your data engineering practices from classic ETL to intelligent agentic workflows. We'll cover designing agents for data extraction, transformation decisions, and loading strategies—as well as how to combine traditional orchestration tools with AI agents for hybrid architectures.
How We Stopped Answering Data Questions and Built the Stack That Answers Them
If you've worked at a growing startup, you probably know the feeling: multiple teams pulling different numbers for the same metric, ops constantly asking engineering for basic answers, and creating or organizing metrics that's a real pain. Every new question feels like starting from scratch. This talk is the story of how a small team fixed that. First, by building a proper dbt architecture from scratch with Sources, Staging, Intermediate, and Marts so that things like bookings, revenue, and providers were defined in one place and everyone was looking at the same number. Once the data was reliable, we connected an LLM so non-technical teammates could ask questions in plain English and get real answers directly from Snowflake. No SQL, no ticket, no waiting on engineering. You'll walk away with a clear mental model for building a dbt layer people actually trust, a practical architecture for connecting an LLM to your warehouse, and the one thing that made it all click: your dbt docs are your LLM prompt.
Multi-Agent Teams in AI-Assisted Development: A Glimpse Into the Future of Programming
Get a glimpse into the future of programming, where teams of AI agents collaborate with human developers. In this workshop, you'll explore cutting-edge patterns for multi-agent collaboration in AI-assisted development: code generation agents, review agents, testing agents, and orchestration strategies. We'll build a mini multi-agent development team using Python and the Claude SDK, and discuss where this technology is heading and how developers can prepare.
Daniel Sabogal
Data & ML Intern @ Loka
Isabel Mora
Junior ML Engineer @ Loka
José Hernán Ortiz Ocampo
Senior ML Engineer @ Loka
NORTH: Claude as a Real Copilot
Learn how NORTH uses Claude as a genuine coding copilot—not just a code completer, but a true engineering partner. In this workshop, you'll explore the architecture of NORTH and learn how to build similar AI copilot integrations using Claude's API and Python. We'll cover prompt engineering for coding assistance, maintaining context across long sessions, integrating with development workflows, and building the feedback loops that make AI copilots genuinely useful.
Lessons Learned Reporting Vulnerabilities in the Python Ecosystem
You've surely received that notification telling you to update a dependency due to a security flaw. But have you wondered what happens from when someone discovers that vulnerability until the patch reaches your project? In this talk I'll share my experience reporting vulnerabilities in the Python ecosystem. We'll explore the behind the scenes: from the technical finding and reporting process to collaboration with maintainers and patch publication. We'll address not only technical aspects but also the human factor—both crucial for effective vulnerability resolution. The challenges maintainers and the community face, especially in this new era of open source software security where artificial intelligence plays an increasingly relevant role.
Camila Plejia, Virtual Assistant Applied to People with Tetraplegia
The combination of different tools and technologies in artificial intelligence—Computer Vision, OCR, NLP, RPA, Voice to text, text to voice—gives rise to a virtual assistant, Camila Plejia, that helps people with tetraplegia, facilitating their daily tasks such as reading news, checking the weather, reviewing, reading and writing email, reviewing, sending and reading WhatsApp messages, searching for and watching a specific video on YouTube, among others. It allows a person with tetraplegia to have a window of communication with the outside world, considering they spend much time isolated between four walls and depend on a third party's assistance to perform activities.
Dashboards That Think: Build Agentic Analytics with Sigma
Learn how to build dashboards that don't just display data—they think. In this workshop, you'll combine Sigma's business intelligence capabilities with Python-based AI agents to create agentic analytics dashboards. We'll cover integrating LLMs with Sigma, building agent-driven data narratives, automating insight discovery, and creating dashboards that can answer follow-up questions and adapt dynamically to user context.
