Elixir Mentor
Elixir Mentor

George Guimarães on Forecasting

21 December 2025 1:34:29 Jacob Luetzow

Listen to episode

About this episode

In this episode of the Elixir Mentor Podcast, I chat with George Guimarães about Soothsayer, his time series forecasting library inspired by NeuralProphet and built on Axon and NX for business data analysis.

We explore how Soothsayer decomposes business data into seasonal components, handles holidays as special events, and uses neural networks to model nonlinear patterns. George explains why Elixir's ecosystem with NX, Axon, and Bumblebee provides unique advantages for machine learning workflows, allowing you to run models directly in your supervision tree without external infrastructure.

The conversation expands into why Elixir is particularly well-suited for AI agent development. George shares insights from his current work building agentic commerce solutions, where the BEAM's actor model, fault tolerance, and message passing provide battle-tested patterns that other ecosystems are now trying to replicate for LLM workflows. We also discuss AEO (Agent Engine Optimization) as the new SEO, and how websites will evolve to serve both human and agent visitors.

Whether you're interested in time series forecasting, building AI-powered applications in Elixir, or understanding why the BEAM's concurrency model is perfect for the agentic future, this conversation offers valuable perspective from an Elixir community OG.

Resources Mentioned:
- Soothsayer: https://github.com/georgeguimaraes/soothsayer

Connect with George:
- X: https://x.com/georgeguimaraes
- Website: https://georgeguimaraes.com

SUPPORT ELIXIR MENTOR
- Elixir Mentor: https://elixirmentor.com/?utm_source=elixir-mentor

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 Elixir Mentor. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.