Guide · 9 min
How to make a playable ad with AI
From a URL to four network-ready packages: brand analysis, brief review, build, deterministic QA and handoff. What the model does and what you must still decide.
The production path for a playable used to run: brief, storyboard, design, build, four network variants, QA, packaging. Roughly twelve hours per unit for someone who has done it before. Most of that is mechanical. Here is what the sequence looks like when the mechanical part is generated and the judgement stays with you.
1. Start from a link, not a blank prompt
Give the system your homepage or app store listing. It reads the page, the about copy, the manifest and the logo, and extracts a palette, a voice and a product summary. This matters because a prompt describes what you remember about the brand; a link describes what the brand actually is.
2. Correct the brief, not the build
Before anything is generated you get a brief: brand summary, palette, logo, proposed mechanic, end-card promise. Every bad AI advertisement we have seen was a bad brief nobody read. Fixing a mechanic here takes ten seconds; fixing it after the build costs a rebuild.
3. Pick the mechanic against the decision
Ask what the customer decides inside your product, then choose the mechanic that rehearses it in under fifteen seconds with one finger. Basket-building for retail, a slider for anything with an amount or a term, catch-the-offers for delivery and rewards, choose-and-match for travel and plans. If the mechanic needs a tutorial, it is the wrong mechanic.
4. Build, then read the QA rather than the preview
A preview in a desktop browser tells you almost nothing about an SDK WebView. Deterministic checks do: entry point present, assets inlined, ES5 where required, click handler matching the network, required disclaimer strings intact, package shape correct. Those either pass or they do not, and no amount of visual polish substitutes.
5. Export per network and ship
The same creative exports as self-contained HTML for Google UAC and AppLovin and as a rooted zip for Unity and Mintegral. Upload, tag, and then bring the numbers back: completion rate and choice distribution are the signals worth regenerating against, not impressions.
What the model should never decide
Claims, prices, ratings and offers — those come from your source material or they do not appear.
Network disclaimers — quoted verbatim, never rewritten for rhythm.
Whether the mechanic is honest about the product. That is a brand judgement and it has no proxy.