Turn how your team works into playbooks and agents
The Hook
“Every company runs on knowledge. No system fully captures the work people do, how they do it, the decisions they make, the people they ask.”
Problem Agitation
“Then someone leaves, and that knowledge goes with them. Cue the handovers, SOPs, and weeks spent reconstructing how work gets done. AI agents face the same problem. They know the internet, but not your company.”
Product Reveal
“GodHands changes that. It learns how your team works by observing real tasks across desktop apps, capturing context, decisions, and edge cases.”
Feature Teaser
“It turns that experience into a living knowledge base, repeatable playbooks, and a self-learning harness that can do the work.”
Feature Teaser
“No integrations, no endless interviews. Knowledge stays when people leave. New hires get up to speed faster, agents work smarter, and businesses can reduce operational costs.”
Call to Action
“GodHands. The operational brain for your company.”
Synthesizable in Remotion · key components of the ai-knowledge-engine-manifesto template.
Multi-colored vector branching lines that connect desktop task inputs to state machine decision nodes.
Use SVG path elements with strokeDasharray and interpolate strokeDashoffset using frame progress to draw branches between coordinate nodes.
Point-cloud particle avatar that stands up from a desk and leaves while the desk remains populated.
Render Three.js PointCloud in a Remotion Canvas component, modulating alpha and particle translation along the X-axis across frames.
Card flow UI that ingests an incoming message, resolves company context, and auto-checks an action badge.
Sequence spring animations on child container scale and opacity, then transition status pill background color and checkmark icon opacity.
Purpose. Highlight how organizational knowledge is fragmented across apps and lost via turnover.
Execution. Rapid cuts between browser tabs, physical notebooks, and offboarding boxes.
Purpose. Demonstrate GodHands passively converting complex human decisions into executable workflows.
Execution. Chess move analogy mapped in real time to decision branches and playbooks.
Purpose. Illustrate concrete operational ROI: onboarding, smarter agents, and cost reduction.
Execution. Branching flowcharts consolidating multiple pending tasks into completed playbooks.
Objective
Launch video for an AI devops agent that captures senior engineer debugging habits.How the recipe adapts
Replace the office/chess metaphors with terminal logs, IDE captures, and production incident playbooks while preserving the living graph and wireframe transitions.Scene durations (6 scenes, 74s)
Key Remotion components
Introducing Griffin, the first AI to pass the video Turing test
The most emotive and controllable TTS model

Always-on agents built to handle everything