Edit by Feel

What the company appears to be: Edit by Feel is a self-reported tool that claims to use AI to assist in video editing within DaVinci Resolve. It positions itself as an assistant that interprets a user's emotional intent ("describe how the film should feel") and applies precise edits, while keeping the user as the director.

What changed: The project was submitted to the OpenAI 2026 hackathon, suggesting it is in early development or prototype stage. No evidence of prior traction, revenue, or customer adoption exists.

Single most important open question: Is there any evidence of actual functionality beyond a concept or demo? The description does not confirm whether the tool works as described or if it's a proof-of-concept.

Analysis basis: This report is based solely on the self-reported project description provided by the caller. All claims are unverified and should be treated as stated by the author, not proven facts.

The description states: “Describe how the film should feel. Codex understands the footage, makes bounded, precise edits inside DaVinci Resolve, and verifies every change while you remain the director.”

• Product claim: A tool that interprets emotional intent from a user and applies edits to video within DaVinci Resolve.
• Technology stack: The author lists tools including Codex, DaVinci Resolve Studio, DJI, ffmpeg, Fusion, GPT-5.6, macOS, MCP, NumPy, OpenCV, Python, PyTorch, SciPy.
• Not evidenced: Whether the tool actually integrates with DaVinci Resolve or executes edits in real-time; whether “Codex” refers to a specific model or is a placeholder.

Inference: The product appears to be an AI-assisted editing assistant for video editors using DaVinci Resolve, but actual functionality remains unproven.

The tagline and description state:

"Describe how the film should feel. Codex understands the footage, makes bounded, precise edits inside DaVinci Resolve, and verifies every change while you remain the director."

• Positioning claim: A tool that allows users to express emotional intent and have AI apply edits within a professional editing environment.
• Key differentiator: The user remains the director; the system provides “bounded, precise” edits.
• Not evidenced: Whether this is a new or existing concept in video editing; no prior positioning or evolution history is provided.

Inference: The product positions itself as an AI-powered editor that respects creative control while automating parts of the process. This is a self-reported claim without evidence of prior market presence or differentiation.

The description states:

"Codex understands the footage, makes bounded, precise edits inside DaVinci Resolve"

• Target customer: Video editors using DaVinci Resolve.
• ICP (Ideal Customer Profile): Likely professionals or semi-professionals in filmmaking, content creation, or post-production who use DaVinci Resolve and seek AI assistance.

Not evidenced: No specific customer segments, personas, or use cases are described. The description does not indicate whether the tool targets indie filmmakers, studios, or hobbyists.

The description states:

“Codex understands the footage, makes bounded, precise edits inside DaVinci Resolve, and verifies every change while you remain the director.”

• Business model claim: Not stated.
• Pricing evidence: None provided.
• Not evidenced: Whether this is a SaaS tool, a one-time purchase, or a freemium offering.

Inference: The business model is not described. It may be a software-as-a-service (SaaS) product, but no pricing or monetization strategy is evident.

The author lists the following tools used:

• Codex
• DaVinci Resolve Studio
• DJI
• ffmpeg
• Fusion
• GPT-5.6
• macOS
• MCP
• NumPy
• OpenCV
• Python
• PyTorch
• SciPy

• Technical stack: Indicates use of AI (GPT, Codex, PyTorch), video processing (ffmpeg, OpenCV), and editing (DaVinci Resolve, Fusion).
• Not evidenced: Whether the tool is a plugin, standalone app, or integrated into DaVinci Resolve; whether it's a desktop or cloud-based solution.

Inference: The project uses a mix of AI and video-processing tools, suggesting technical sophistication. However, no evidence of delivery mechanism or integration is provided.

The description states:

• “This project was submitted to the OpenAI 2026 hackathon on Devpost.”

• Traction: Not evidenced.
• Maturity: The submission to a hackathon suggests early-stage development or prototype status.
• Not evidenced: Any user base, revenue, or product adoption.

Inference: The project is likely in an early stage of development. No signs of traction or product maturity are evident.

The description does not mention any competitors or market context.

• Competitive landscape: Not described.
• Not evidenced: Whether similar tools exist; whether this addresses a gap or overlaps with existing solutions.

Inference: No competitive positioning or market analysis is provided. The tool may be novel, but there is no evidence to support or refute its uniqueness.

• Risk 1: The project is described as a hackathon submission, suggesting it is not yet a mature product.
• Risk 2: No evidence of integration with DaVinci Resolve or actual functionality.
• Risk 3: The use of “GPT-5.6” (not a known model) raises questions about technical accuracy or marketing hyperbole.
• Risk 4: No pricing, business model, or customer data is provided — all assumptions are speculative.

Inference: The lack of product functionality, traction, and business clarity raises significant risk for investment or partnership.

1. What does “Codex” refer to in this context? Is it a specific model or placeholder?
2. Has the tool been tested with real users or footage?
3. How does it integrate with DaVinci Resolve? Is it a plugin, API, or standalone app?
4. What is the exact workflow from user input (e.g., “how the film should feel”) to edit execution?
5. Are there any existing customers or early adopters?
6. What is the monetization strategy and pricing model?

Inference: These questions are necessary to validate the claims and assess product viability.