The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Working on DragSet involves coaching an AI coding assistant through features and bug fixes, then running QA. One failure mode I watch for is a growing pile of small patches without meaningful progress.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Trending
retrofuturism
Share your favorite designs from the past exploring the distant future. Or your own take on the aesthetic 🚀
halftone
Dots. Texture. Grain. Let's see your designs using the halftone technique.
Midjourney
Creatives are showing off what they're making with Midjourney.
colorgrade
Video editors sound off: How do you enhance the mood of your video in color grading?
Challenges
View all
Related posts
From a 40-Minute Client Call to a Working Interactive Prototype in Hours (5x Faster with AI Agents)
Going from an initial client briefing to an approved wireframe usually takes 3 to 7 days of manual note-taking, layout debates, and generic copy.
In this video, I walk through my exact 3-phase workflow to cut that timeline down to a single afternoon using raw call transcripts and custom AI agent
Descript MCP Workflow
Instead of scrubbing through the timeline manually, I used the Descript MCP with an AI agent to instantly generate accurate YouTube timestamps, description and video titles directly from the project context — killing post-production busywork in seconds.
YouTube Video Link: https://youtu.be/lI3sCyUabHQ
Descript Video: https://share.descript.com/view/7AlW3niOPfx
Descript MCP Session Workflow: https://www.loom.com/share/848564eb31074c43b8f0d2068460e1be (I used Google Antigravity, which doesn't have a shared chat option)
the blue prototype card looks cool
Just published a new case study👀
This project was a good reminder that a product video is not just about making things move. It’s about finding the right way to explain something complex, keeping the visuals clear, and making sure every animation has a purpose.
For this one, I worked on an AI coaching platform, turning its features and workflow into a structured 90-second explainer.
⬇️⬇️⬇️
The motion design is top tier 🔥 , love how the product features was communicated and the use of glassmorphism🙌
This project started with a very specific idea for how a static product visual should move.
The base artwork was created with ChatGPT and Nano Banana, but before generating the final animation, I spent time refining the prompt and defining the exact movement, camera behavior and energy we wanted.
I tested the direction with different models, including Kling 2.5, using those iterations to improve the prompt before producing the final sequence with Seedance 2.5.
The result was extremely close to what we had planned, including the animation and even the sound effect that completed the motion.
For me, this is where AI production gets interesting: the real work is not simply generating. It is art direction, prompt design, testing and refinement until the model delivers the intended result.
That line about the real work being art direction and refinement rather than generation is something I don't think most clients grasp yet, they still see 'AI made it' as the whole story. Did you end up walking the client through that process, or did they only care about the final result?
