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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