I want to build a proof-of-concept pipeline that turns my training scripts into short, live-action videos automatically. The goal is to have an “agentic” workflow—one that chains together LLM prompts and generative-video APIs so I can feed in plain text and receive finished MP4s with captions and thumbnails. Scope for this first milestone is intentionally lean: • Select and connect appropriate live-action synthesis services such as Runway Gen-2, Synthesia, D-ID, Colossyan, or a comparable tool, using Python or Node plus LangChain/AutoGen (or a similar agent framework). • Script the agent logic to: – take a text lesson as input, – generate voice-over, on-screen presenter or b-roll, – compile everything into a 1080p video, – export SRT captions and a thumbnail. • Produce 2–3 sample training videos with the pipeline to prove repeatability. • Supply clean, commented code and a step-by-step README (or short screencast) so my non-technical team can rerun the workflow. Acceptance criteria – Runs locally or in Colab with minimal setup. – Live-action look; no animated or whiteboard styles. – Consistent audio quality and branded lower thirds. Deliverables: source code, config files, documentation, and the sample videos. Timeline: I’d like the prototype ready within a week; further refinement can follow once this baseline is solid.