Build a new AI agent on AWS and deploy it easily, OR wrap and deploy an agent you already have, using the Amazon Bedrock AgentCore harness. Explains what an "agent harness" is (the runtime scaffolding around a model - agent loop, tool execution, memory, identity, observability), then gives two fully-working, verified paths - (A) scaffold + ship a new agent with the AgentCore CLI (create/dev/deploy/invoke), and (B) deploy a prepared agent (Strands, LangGraph, or custom) via the SDK wrapper or a FastAPI + Docker + ECR container. Every import and command is verified against official AWS/Strands docs. Use when the goal is to create, wrap, or deploy an agent on AWS AgentCore. Triggers on agent harness, AWS harness, AgentCore, AgentCore CLI, agentcore create, agentcore deploy, deploy agent on AWS, bring your own agent, Bedrock AgentCore runtime, serverless agent.
Build AI agents with the Strands Agents SDK - the open-source framework (the agent "brain") for writing agent logic, tools, and multi-agent systems in Python. Model-agnostic, AWS Bedrock by default. Covers Agent, the @tool decorator, model providers (BedrockModel), multi-agent patterns (agents-as-tools, Swarm, Graph), conversation management, and streaming. Every import verified against official Strands docs. To DEPLOY a Strands agent on AWS, use the aws-harness skill. Triggers on Strands, Strands Agents, Strands SDK, agent framework, agents as tools, Swarm, Graph multi-agent, BedrockModel.
Master prompt-engineer for photoreal, artifact-free AI still images on ANY tool (Reve, Midjourney, Flux, GPT-image, Imagen, Nano Banana, Stable Diffusion). Builds prompts that hit National-Geographic-grade realism — true skin/fur texture (no plastic), correct anatomy/hands/faces, physically coherent light/shadows/reflections, clean legible text — while engineering deliberate visual IMPACT (color contrast, composition, awe/adrenaline, a striking point of view). Runs a gated process: lock the point-of-view and build the 8-block Capture Stack BEFORE generating, then run a forensic pre-submit inspection against the known artifact list. Use whenever the goal is a single still image that must look REAL and hold up under close inspection — contest entries, hero shots, product/character/wildlife/architecture/concept art, or any time AI images come out plastic, distorted, or fake. Composes with nano-banana-2 (execution) and director (motion). Hebrew triggers: תמונה, תמונות, פוטוריאליזם, ריאליזם, לייצר תמונה, פרומפט לת
Award-winning director's brain for making films/videos with AI. Runs a gated, interrogation-first process: lock the IDEA and the SCRIPT (the story) in words before generating a single pixel, then plan shots/camera/light/sound, then generate and edit. Use whenever creating a video, film, teaser, trailer, promo, ad, short, reel, documentary, or narrative piece AND the storytelling must actually work — or any time the user says the story/script keeps failing. Hebrew triggers: סרטון, טיזר, פרומו, פרסומת, ריל, סרט, תסריט, סטוריבורד. Handles development, story, and shot-planning; composes with cinematic-ai-video and yuv-fomo-teaser (style/manipulation), hyperframes (render), nano-banana-2/ElevenLabs (assets). Backed by a 28-chapter Director's Bible in references/.
Generate unified, on-brand Instagram Reel covers for Yuval (YUV.AI Neon Phoenix system) — the signature look is a giant Hebrew headline BEHIND the subject cutout + a punch line IN FRONT (depth effect), on rich black with a dim neural-net field, series-colored chip + phoenix mark. Use whenever Yuval asks for an Instagram/Reel/TikTok/YouTube cover, thumbnail, עטיפה, קאבר, תמבנייל, cover image for a video, or wants his Instagram grid to look consistent. One command per cover; background removal included in the pipeline.
Yuval's all-in-one AI video pipeline. Turns an idea/script into a finished, on-brand MP4 by orchestrating HyperFrames (HTML→deterministic video render), Lottie (branded motion graphics), ManimCE (math / neural-network / concept animations), and a transcribe→approve caption flow — all wrapped in the YUV.AI Neon Phoenix brand via a frame.md. Use whenever Yuval wants to make, edit, or explain something as a video: promo, explainer, launch, social reel, "make a video about X", "explain X as a video", "neural network animation", "turn this into a video", captioned tutorial, 16:9 or 9:16. Triggers: video, explainer, promo, reel, manim, lottie, hyperframes, animation, "make a video", "explain ... as a video", מצגת וידאו, סרטון, הסבר וידאו. Routes each beat to the right engine, wraps in brand, self-verifies, and renders.
Build a premium cinematic landing page with mouse-scrub video hero and brand-driven narrative-arc sections. Use whenever the user provides a hero video plus a product / subject / brand and wants a landing page, promo site, product showcase, marketing page, or storytelling site. Works for any language (RTL or LTR — Hebrew, English, Arabic, Spanish, French, Japanese, etc.) and any subject (food, tech, animals, fashion, services, SaaS, wildlife campaigns, music releases, books, real estate). The signature effect is mouse-driven video scrubbing — the hero video lives across the entire page as a fixed backdrop, and moving the mouse left-right scrubs the video timeline so the subject responds to the cursor. Below the hero, 4-5 fully-opaque sections each carry their own brand identity (color, typography emphasis, layout pattern) and walk the viewer through a narrative arc (e.g. longing → joy → nostalgia → contemplation → action). Triggers on phrases like "build a landing page from this video", "cinematic landing pag
Edit any video into a captioned showcase — transcribe (any language, defaults to large-v3), present a transcript_review.txt for the user to fix mishears BEFORE rendering, then build a HyperFrames composition with liquid-glass caption pills, liquid blob background, liquid morph wipes, optional behind-subject text via background removal, and render the final video. Use whenever the user provides a video file and asks to edit it, caption it, add subtitles, fix existing captions, make a reel/promo/captioned tutorial, or "do the same" pattern as a prior captioned video. Supports English, Hebrew, and any Whisper-supported language. **Renders both 16:9 (YouTube / horizontal) and 9:16 (TikTok / Instagram Reels / YouTube Shorts) from the SAME 16:9 source** — vertical mode uses a centered footage strip with a blurred backdrop + liquid blobs and a vertical-tuned caption pill, no need to re-shoot. THE PIPELINE PAUSES FOR USER APPROVAL on the transcript before final render — this is the support mechanism for getting capti