Fantasy Football Neuron – AI-powered debates for lineup building

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I built an app called Fantasy Football Neuron, a tool that turns fantasy football lineup research into live multi-agent debates. Instead of static articles or black-box optimizers, you pick a panel of up to six AI analysts (tuned on different strategies: GPP, data-heavy, contrarian, etc.). Ask a question like “Tua or Allen?” → they argue it out in real-time with ElevenLabs voices. The transcript shows why each pick wins, and you can export the chosen lineup directly to DraftKings/FanDuel. Tech stack: • Backend: Cloud Run + Cloud Functions (serverless-first) • Frontend: Next.js (hosted via Lovable) • Database: Firestore (real-time debate/live dashboard) • Caching: Redis + Cloudflare edge routing (infra <$0.05 per debate) • Models: six LoRA adapters trained on open-source LLMs (Vertex AI preemptible GPUs) • TTS: ElevenLabs for character voices Live here: https://fantasyfootballneuron.app Would love feedback from the HN community on the approach — especially around scaling real-time debates and caching optimizations.

Visit product View on Hacker NewsAug 22, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, model, lovable · Missing: mac, agents, macos

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

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TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

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nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

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BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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