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Pivot Note (March 2026): Ryu has evolved from "rebuild the agent from scratch" to an orchestration layer. Users pick their own agent engine (ZeroClaw, OpenClaw, IronClaw, etc.), and Ryu provides the UI (Ryu App) + middleware (Ryu Gateway). Content ideas below should be adapted to reflect this: the story is no longer "we built a better agent" but "pick your agent, we handle the rest." Two content tracks: Ryu App (consumer demos, "look what my AI did") and Ryu Gateway (developer/enterprise, "secure your AI stack through one layer").
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A running list of content ideas to demonstrate Ryu's capabilities in the wild, YouTube videos, UGC-style posts, threads, and shorts that prove the product works by showing real results.
🎯 Content Strategy
Every piece should follow one principle:
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Show, don't tell. Run real tasks with Ryu using local and open-source models, record the results, and let the output speak for itself. Authenticity > polish.
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🎥 YouTube Video Ideas
"I Tried Local Models for AI Agents — Here's What Happened"
- Run a complex multi-step agent task (research → summarise → draft) using a local model via llama.cpp
- Show the full process — setup, execution, output quality
- Compare against a cloud model doing the same task
- Hook: "You don't need GPT-4 for this."
"I Run AI Agents for Free — No API Keys, No Subscriptions"
- Full walkthrough of installing Ryu, downloading a local model, and running an agent with zero cost
- Emphasise the zero-dollar angle — no cloud, no keys, no billing
- Show multiple use cases: file organiser, email drafter, code reviewer
- Hook: "Everyone's paying $20/month for AI. I pay nothing."
"How Well Do Open-Source Models Actually Perform with Agents?"
- Benchmark-style video: run the same agent tasks across Llama, Mistral, Qwen, Gemma, etc.
- Score on task completion, speed, coherence, tool-calling accuracy
- Honest results — show where they fail too