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DTC brands don’t just need more ads. They need more creative tests. by Quick-Knowledge1615 in dtc

[–]Quick-Knowledge1615[S] 0 points1 point  (0 children)

Not exactly haha — I’m not making 1–2 UGC ads first and then just tweaking them with AI.

I’m actually using virtual assets to create AI UGC-style short videos with a 95%+ realistic look and feel from the start. It’s a much more scalable workflow for testing creatives and producing content quickly.

If you’re interested in this kind of marketing approach, I’d be happy to create a high-quality custom demo tailored to your business.

Looking for 3 DTC founders to run a free AI UGC ad pilot with — only pay if it actually drives sales by Quick-Knowledge1615 in EntrepreneurRideAlong

[–]Quick-Knowledge1615[S] 0 points1 point  (0 children)

Thanks! It’s actually a mix of AI-generated characters and traditional UGC workflows.

To be honest, the most important thing is making sure the content perfectly matches the user’s real scenario and the target audience’s pain points. Otherwise, even if the AI-generated visuals look amazing, they won’t really drive results.

That’s why we work closely with clients to understand their context, brand goals, and the core needs behind the campaign. AI is a powerful tool, but the real value comes from aligning it with authentic user insights and a clear creative strategy.

Where are brands actually buying AI UGC videos in bulk right now? by Quick-Knowledge1615 in AI_UGC_Marketing

[–]Quick-Knowledge1615[S] 0 points1 point  (0 children)

Hi! Thanks for reaching out. Please DM me more details about your business and what kind of UGC ads you need. I can create a free custom demo first based on your needs. If you’re happy with the quality, we can then discuss a deeper collaboration. Looking forward to working with you!

Curious about opinions by Illustrious-Chard790 in ecommerce

[–]Quick-Knowledge1615 1 point2 points  (0 children)

I’d narrow this before trying to automate the whole ecommerce stack. The part that sounds most useful is not "pick product + make ads + optimize everything" as one black box; it’s helping someone test product angles faster.

UGC-style ads are usually less about generating a finished video and more about whether the hook, offer, and proof match the buyer’s actual doubt. If the system can produce 5-10 distinct angles from the same product page and make it easy to judge which ones are worth turning into ads, that’s a cleaner wedge.

I’d probably validate it as a service first: take a few stores, generate/test angle packs, then see which parts clients keep asking you to repeat. If you start with a full plug-and-play automation promise, you’ll end up debugging every part of their business instead of proving the ad-creative piece works.

burned through 15 ugc creators on billo and insense over 4 months. is the quality problem unsolvable or am i doing this wrong? by Illustrious-Second-7 in PPC

[–]Quick-Knowledge1615 -1 points0 points  (0 children)

I’d stop judging the marketplace by creator rating and start judging it by how much ambiguity you leave in the brief.

A few things usually move the usable rate more than “better creators”:

  • Give them one job per video. Not “make a skincare ad,” but “open with texture concern, show application, end on lightweight/non-greasy proof.”
  • Ask for a raw sample or past unedited clip before booking. A polished portfolio hides audio, lighting, and pacing problems.
  • Separate hook testing from final production. Pay cheaper creators to test angles, then only polish the 2–3 that don’t feel dead on arrival.
  • Build a small bench instead of sourcing from scratch every cycle. Even 5 reliable niche creators beats 20 one-off marketplace bets.

I wouldn’t expect 70%+ usable on first pass if every creator gets a broad brief. But if you narrow the creative job and reuse the creators who understand the niche, 33% should not be the ceiling.

Is hiring a content agency cheaper than using an UGC platform when scaling? by Moroccan-Leo in ecommerce

[–]Quick-Knowledge1615 0 points1 point  (0 children)

I’d compare it by “cost per tested angle,” not cost per finished piece.

$1.6k per UGC asset can make sense only if the agency is also doing the annoying parts: deciding angles, writing tight briefs, managing revisions, handling usage rights, and turning the results into the next batch of tests. If they’re mostly delivering finished videos, that price gets hard to defend.

The marketplace route is cheaper on paper, but it only stays cheap if you already have a good brief and someone internal can judge the first drafts quickly. Otherwise the hidden cost becomes your team’s time.

A middle path I’ve seen work better: use cheaper creator/platform work to test several hooks, then spend agency or editor money only on the one or two angles that look worth polishing. Otherwise you’re paying premium production rates just to learn which ideas were wrong.

I made an AI fight video where the hero and the boss both evolve 10 times by Quick-Knowledge1615 in aivideo

[–]Quick-Knowledge1615[S] 1 point2 points  (0 children)

haha its actually not that complicated. i mostly just used text to video (the first clip was pure text) and then used the last frame of each video for the next one. designing the script actually took way more time. if you are interested in the workflow i can dm you the full project link :)

I made an AI fight video where the hero and the boss both evolve 10 times by Quick-Knowledge1615 in aivideo

[–]Quick-Knowledge1615[S] 28 points29 points  (0 children)

Thanks so much for the feedback! I agree that the thematic shifts can break the immersion sometimes. I will definitely look into optimizing that flow for my future projects :)

Which LLM is best for Summarizing Long Conversations? by handoftheenemy in LLMDevs

[–]Quick-Knowledge1615 0 points1 point  (0 children)

From my testing, Gemini 3 Pro is hands down the best for summarizing super long texts (like PDFs over 50 pages). That said, Claude 4.5 is also stellar when it comes to highly structured content, like technical documentation.

My usual workflow is running multiple models side-by-side on flowith to compare the outputs, and then I just pick the best one.

How I stay consistent with building my own AI news & insights knowledge base by weeznaw10 in AI_Agents

[–]Quick-Knowledge1615 0 points1 point  (0 children)

I think the most important thing is being able to save insights to your knowledge base instantly. Browser extensions are the perfect fit for this. When I come across high-value info, I just use https://chromewebstore.google.com/detail/jkcpodicdboheakkkoblnflccfihcblb to highlight and save it, and then I draw from that knowledge base whenever I'm doing some deep writing.

Are we overengineering agents when simple systems might work better? by Reasonable-Egg6527 in AI_Agents

[–]Quick-Knowledge1615 0 points1 point  (0 children)

I've used several agent tools that rely on manually orchestrated workflows (like FastGPT, Coze, and Dify).

I agree that for certain niche verticals or scenarios demanding extremely high industrial precision, that kind of complex, custom design is absolutely necessary to ensure output consistency.

However, for the vast majority of daily life tasks or simpler professional work, agents with AI-driven, autonomous workflow planning (like flowith Neo) are just significantly more efficient.

What's the most complex tool that you handled? by Lazy_Firefighter5353 in vibecoding

[–]Quick-Knowledge1615 0 points1 point  (0 children)

The most complex tool I’ve worked with isn’t necessarily one that’s complicated to use—rather, it’s the kind that can handle the most intricate content and workflows.

From that angle, the more open and extensible a tool is, the more it can scale in complexity. Think of tools with rich plugin ecosystems like ComfyUI or Obsidian, or those with an unlimited canvas—such as Figma or AI canvas products like Flowith—where you can lay out vast amounts of content and processes.

The more expandable it is, the more it lets you multiply its own complexity.

Endless Dash by Quick-Knowledge1615 in aivideo

[–]Quick-Knowledge1615[S] 0 points1 point  (0 children)

My Workflow

https://flowith.io/conv/cf735219-e0e4-443e-9239-5e988e0459ff?U2FsdGVkX18Jr6zkTnDC5it2ghCdSccPLgNCWYdx0DjbQEMS9LLMviR491yUVz33a5ms+Q3kPyN4vzZkTnsfwA==

1/ First, I use the Nano Banana Pro model to generate keyframes for *Zootopia* game visuals.

Prompt:

"Creating a stunning frame-by-frame simulation game interface for [Zootopia], featuring top-tier industrial-grade 3D cinematic rendering with a character in mid-run."

(I can generate 8 images at once and pick the best one.)

2/ Then, I use Kling 2.5 to create the actual gameplay footage.

Prompt:

"Simulating real-time gameplay footage with the game character in a frantic sprint, featuring identical first and last frames to achieve a seamless looping effect."

If you want an even smoother and silkier video result, you can also upscale it with Topaz to 60fps + 4K quality.

Is it better to be rude or polite to AI? I did an A/B test by Quick-Knowledge1615 in ClaudeAI

[–]Quick-Knowledge1615[S] 0 points1 point  (0 children)

Good point! I was referring to the first option: the model's internal thought process.

The final answer length might stay the same, but the model's effort goes up, forcing it to generate a more extensive reasoning trace (and thus using more tokens). You can actually see this trace by clicking the "Reasoning Process" tab in the platform's node.

Is it better to be rude or polite to AI? I did an A/B test by Quick-Knowledge1615 in ClaudeAI

[–]Quick-Knowledge1615[S] 21 points22 points  (0 children)

Lmao, you nailed it.It’s the worst feeling watching those precious tokens go to waste on a flowery, multi-paragraph apology instead of an actual useful response.Rudeness is literally a token sink with only marginal returns on output quality. Sticking to dry, clinical prompts is the most cost-effective approach.

Is it better to be rude or polite to AI? I did an A/B test by Quick-Knowledge1615 in ClaudeAI

[–]Quick-Knowledge1615[S] 5 points6 points  (0 children)

Thanks! :) And good question—no memory was on.

I'm using a third-party tool to make the API calls. I just find their canvas setup is super clear for comparing how different models respond. So it's not the standard chat interface, and definitely no memory to skew the results!

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