End-of-Season Update: Our Amazon Bedrock Fantasy Football Agent
When we left off in “Can You Beat the Bot? Inside Red Oak’s Fantasy Football AI Showdown,” the Red Oak Fantasy Football AI was doing something no one wanted to admit was possible: consistently beating most of the humans in our league.
After five weeks, it led the league in both record and points scored. By Week 11, it had ridden a six-game win streak into a first-round playoff bye and was widely regarded as the most disciplined manager in the league. At that point, we briefly considered updating the headline to “Yes, You Can Beat the Bot (But Probably Not This Year).”
Now that the season is officially complete, we’re proud to report that humanity prevailed, at least for one more year. After earning that first-round bye, the AI ran head-first into the most powerful force in fantasy football: player variance. My team, the McCaffrey Load Balancers, managed to lift the inaugural Red Oak Fantasy Football trophy on behalf of humankind, proving my superior ball knowledge (and my genius approach of drafting Christian McCaffrey at #9 and picking up Joe Burrow, RJ Harvey, and Rico Dowdle off of waivers).
As a data scientist and lifelong sports fan (please don’t ask me about the Raiders), this outcome felt oddly fitting. Fantasy football is one of the most statistically rich games we play, and also one of the most chaotic. Injuries, game script, weather, coaching decisions, and sheer randomness all collide in a way that no model can fully tame.
And yet, that’s also what made this AI transformation experiment so valuable.
What This Taught Us About Agentic AI (Beyond Fantasy Football)
While this project started as a water-cooler experiment, it quickly became something more meaningful. Designing the Fantasy Football AI forced us to think deeply about agentic behavior, breaking a complex role into discrete, goal-oriented actions that could reason, act, and adapt over time.
Drafting. Lineup optimization. Waiver prioritization. Risk management. Even (light) trash talk.
Each of these was implemented as a focused agentic workflow on Amazon Bedrock, supported by live data via web search and contextual reasoning. That same design pattern, clear responsibilities, bounded decision-making, human-readable reasoning, and optional human oversight, is the exact pattern we now help clients apply in their own AI transformations.
The lesson wasn’t “AI can do well in fantasy football.” The lesson was how AI behaves when it’s trusted with decisions instead of prompts. The Fantasy AI didn’t chase hype. It didn’t panic after a bad week. It didn’t overfit to narratives. It played percentages, documented its reasoning, and executed consistently. That’s the same behavior enterprises want when deploying agentic AI into real workflows: forecasting, operations, recommendations, triage, and decision support. Systems that don’t just respond, but act with intent.
Humans Still Matter (And That’s the Point)
The most interesting part of the season was how the AI lost. Managers who combined data awareness with real football context: usage trends, coaching tendencies, playoff strategy, and gut-level risk tolerance, found ways to outmaneuver it when it mattered most by knowing when to pull the right lever. That’s exactly how we think about AI transformation with our clients. The goal isn’t full automation for its own sake. It’s human-AI collaboration, where agentic systems handle consistency, scale, and reasoning, while people provide context, judgment, and accountability. Fantasy football just happened to be a very public, very humbling proving ground.
Looking Ahead to 2026
We’ll be back next season with more human managers, a smarter AI, and another year of rapid advances in agentic reasoning and tooling. And just like with our clients, we’ll keep refining how these systems think, act, and integrate with human decision-makers. Because whether it’s fantasy football or enterprise AI transformation, the real question isn’t “Can you beat the bot?”
It’s: “What happens when we design agents that actually know how to play the game?”
