Tool tests
There are thousands of AI video tools, all charging premium fees, each marketed like a specialist. Strip the wrapper and most are the same engine in different packaging. So I test them the same way every time: same product, same brief, head to head, and log exactly where each one breaks. The findings by use case are below. This is the standard I hold tooling to before it touches a deliverable. The named tool-by-tool breakdown stays with the client work it came from.
01 · Product → ad creatives
Fed one product through the "one prompt, 12 concepts" generators. Fully-automated mode is hit or miss: a few concepts land, most come out formulaic. The reliable path is the mode that pulls real product data and still lets you steer, which is where shippable A/B variants actually come from.
02 · UGC actor / spokesperson ads
Built product-in-hand actor ads end to end: generate the actor, composite the real product, animate, lip-sync. The best tools even infer their own context b-roll. Two catches worth knowing: branding garbles in motion on the cheap engine tiers, and "swap the actor in an existing clip" is still unreliable, cheaper to regenerate per actor.
03 · A/B testing & localization at scale
Ran one script against several actors in parallel to find the winner before spending on a full run, then spun up multilingual versions fast and cheap. That combo is where AI genuinely wins on volume.
04 · Long-form → short-form repurposing
Dropped a 16-minute talking head into a node canvas: it pulled clean, self-contained clips without cutting mid-sentence and synced pop-up graphics to the speaker's gestures. This class is a repurposing accelerator for hours of existing footage, not an ad-from-nothing generator.
05 · Relighting & look-dev on real footage
Tested relighting and compositing on real clips: dropping a subject into a new environment, rebuilding flat 8-bit into true HDR, lighting a flat clip as a rough 3D object. Great for whole-scene mood and fast product lighting on solid packaging. It breaks on glass, liquid, fine hair, and fast camera moves, and the reference image drives the look far more than the prompt.
06 · Trusting the "agent" builders
The conversational builders quietly pick the lazy default, an aspect ratio, an engine, and won't flag it. Ask the good ones to explain a choice and they genuinely reconsider; the best lays out a full spec and cost table before spending a credit. Either way, the output is only as good as the brief.
07 · When NOT to use AI
The one hero film that has to be perfect. AI video is built for scale, not for that. It's still limited, and I'll tell you plainly when it's the wrong call.
Slop or salvation. Both are wrong.
People treat AI video like it's either garbage or magic. Lean too hard either way and you ship something bad.
The market doesn't help. Thousands of AI tools, all charging premium fees, each marketed like a specialist: Tool A "best for UGC," Tool B "best for long-form." Strip the wrapper and most do the same thing. Most of the job is picking the right one for your use case, and knowing where it breaks before you've burned a month and a budget finding out.
So I don't start with a tool. I start with a question: what is this video actually for? Pushing a product with UGC is a different problem than scaling short-form, and each has a different right answer. Give me the use case and I'll test five tools that claim to do the same thing and tell you exactly where each one falls apart.
I'll also tell you when not to use AI. It's built for scale, not the one hero film that has to be perfect. It won't run your whole pipeline, and for most companies it doesn't need to. Knowing that line is the value.
AI gets you to 80% fast. Knowing when that 80% is the finish line, instead of chasing a perfection that quietly ruins the work, is the difference between shipping and spinning.
The rest is taste. I can usually tell what's wrong with a video in the first few seconds, and I know that past a point, fixing it makes it worse.
Most producers see the picture through one lens: AI or real production. I see both. That's the whole job.
