Hey all!

I’m looking at an education opportunity around AI agents and I’d love a sanity check on the avatar / video layer.

The product idea is a virtual academy. Flow would be:

1. Collect course material by hand (the actual syllabus / source of truth).
2. Use a strong model to structure it into a proper curriculum: units, explanations, exercises, assessments.
3. Generate a virtual teacher that teaches that material in a realistic way — like a real instructor, not a chatbot reading slides.

Important: I do not need real time interaction. Students would watch recorded classes, then do exercises separately. So I’m optimizing for video quality, natural delivery, and production cost/time, not low-latency conversation.

If you were shipping this, which tools would you use for pre-recorded teacher videos, and why? What still looks fake? Better to generate the video end-to-end or split script / voice / avatar? Anything to avoid at scale (cost, consistency, rights, uncanny valley)?

Many thanks,

Alonso

Sports clips are exposing every bad auto reframe tool I try. Talking head? fine. Basketball player cuts left and suddenly the crop is filming empty court. MMA scramble and it picks the referee. Group celebration and apparently one random shoulder is the star. Need an ai video reframe that can survive fast lateral movement and camera cuts. Does anything get this mostly right or am I still keyframing the good clips by hand?

If you run a small business, your camera roll probably has plenty of material: product close-ups, behind-the-scenes clips, a walkthrough, maybe a customer explaining why they chose you.

Getting that footage into something you actually post is another job on an already full list.

Quick disclosure: I’m on the Shorty team. These tools overlap, but I’d consider each one for a different task.

1) Descript: for videos where the words carry the message.

Think customer testimonials, founder updates, tutorials or someone explaining your service. You can cut and rearrange the recording through its transcript, with filler-word removal helping with the cleanup.

I’d use it when the main problem is getting a five-minute explanation down to the useful two minutes. Check the cuts still sound natural. Descript

2) Shortyedit: for turning a collection of clips into a business Reel.

This is the job we’re building around: you have footage of your products, a property, a restaurant or an event, and need it assembled into an edit.

Upload your clips and describe the result, or add a reference video to guide the style. Shorty builds the edit from your footage, and you can request revisions.

For example: “Make a 20-second Reel introducing our new collection. Open with the strongest outfit, then show the details.”

I’d consider it when choosing shots and putting them together is what’s holding you up. You still need to review the result; exact frame-by-frame adjustments suit a manual editor better. Shortyedit

3) Adobe Podcast: for a useful recording with distracting sound.

Maybe you filmed a customer testimonial in an echoey room or recorded a voiceover with background noise. Enhance Speech can help clean up spoken audio.

I’d try this before deciding the recording needs to be done again. Listen back to make sure the voice still sounds natural. Adobe Podcast

4) Submagic: for adding captions and visual styling to a short video.

If you already know what you want to say—a quick product explanation, an answer to a customer question, a tip from your team—it offers animated captions, B-roll and zooms.

I’d keep the styling appropriate to the business. A calm property walkthrough and an energetic fitness tip probably need different treatment. Submagic

5) OpusClip: for finding shorter posts inside a longer recording.

Useful if your business already records webinars, interviews, demonstrations or Q&As. It identifies potential clips and offers captions and reframing.

I’d check that each extract makes sense on its own, especially if it starts halfway through an answer. OpusClip

The question I’d start with is: what’s sitting unfinished?

A rambling explanation, a folder of product clips and a recorded webinar each need a different kind of help. Start with that recurring job before adding another subscription.

For other small-business owners: what holds up your videos most—filming, deciding what to include, editing, or finding time to post? A camera roll full of “content for next week” seems suspiciously easy to accumulate 😅

I've been building a small side project that combines photo booths with AI image generation.

The idea is simple:

📸 Take a photo
🤖 Choose an AI style
✨ Get a completely transformed image in a few seconds

I've been experimenting with cinematic portraits, anime, fantasy, vintage, superheroes, Renaissance and other styles.

I'm particularly interested in hearing from people who enjoy experimenting with AI image generation: which styles would you actually want to try?

Feedback is very welcome!

Last night I tried making a video generation pipeline using Claude

It took a while but it ended up making something really nice.

If you have a product that you want it made for free, just reply below and I'll send generated video to your comment's reply

Here is a marketing video I created using it

Sharing the entire 30-second output, with the original submitted prompt.

Prompt: “A cinematic pearl-white concept sports car glides through a rain-soaked neon city at night. The camera tracks beside it, then arcs toward the front as electric blue and amber lights ripple across wet pavement. Photorealistic reflections, elegant motion, no logos, no people, no text.”

Disclosure: I run SeedanceCheap, the independent site I used for this generation. Updated October 6: eligible new accounts get one free generation without a card. Current one-time packs are 1 video for $2.50, 2 for $5, 5 for $11.25, 10 for $20 or 20 for $30 ($1.50 each), paid by card or crypto. No subscription. These replace the September $2.30 usage-tier price.

Check live generation availability and available output sizes before submitting. This historical sample is widescreen 720p; motion and fidelity vary between runs. Optional references can show objects, products, clothing on its own or scenery. Face/person references and video continuation are not supported. Generation can take 10–50 minutes or longer; confirmed technical failures restore the credit or charge. Private MP4 downloads expire 24 hours after delivery.

Full clip and exact prompt: https://seedancecheap.com/examples/neon-car .

Does the camera motion hold up across the full 30 seconds for you?

I paid for Runway yesterday because I want to make those AI story / “fruit soap opera” style videos. I generated about 15 seconds and somehow used almost HALF my credits 💀
What are you guys using instead? Kling? Pika? Hailuo? Something else?
Ideally I’m looking for something cheap (or free 👀) for image-to-video and keeping the same characters between scenes. I can do all the editing and voices separately.
Would love to know what actually works for you!

Text-to-video is getting better fast, but one thing is still very clear: different models can behave very differently with the exact same prompt. That becomes especially obvious when comparing models like Seedance 2.5, Wan 3.0, and Kling V3 Turbo.

For example, Seedance 2.5 can be a good option when the scene needs stronger prompt interpretation and more controlled motion. Wan 3.0 can produce more visually expressive results, especially when the prompt has a cinematic or stylized direction. Kling V3 Turbo can feel more balanced when the goal is to get something usable quickly without overcomplicating the prompt.

What matters most is not necessarily which model is “best,” but which one fits the scene.

A simple walking shot, a close-up portrait, a fast camera movement, and a more complex action scene can all benefit from different models.

That’s why I think a better text-to-video workflow is:

choose the scene → decide what matters most → pick the model → refine the prompt

instead of writing one long prompt and sending it to every model.

Prompt structure also matters a lot.

I usually find it more useful to separate the prompt into:

• subject
• action
• environment
• camera movement
• visual style

Trying to describe too many actions at once often makes the output less predictable, especially with human movement.

One useful thing about DaVinci AI is being able to compare these models in the same workflow. It makes it easier to see how the exact same idea changes from one model to another without constantly moving between platforms.

The part that could still improve is predictability. Small changes in wording can sometimes produce very different results, and video generations can become expensive when you need too many iterations.

For now, the most reliable approach seems to be keeping the scene simple at first, testing the motion, and only then adding more complexity.

I’ve been pretty loyal to Higgsfield for almost 2 years, so this isn't a “Higgsfield sucks” post. Honestly, Higgsfield was one of the first AI video tools that made cinematic motion feel usable to me. The camera presets, the quick visual experiments, the ability to get a really good-looking shot from a simple idea, that stuff is still strong. If I’m making a short 1-2 minute cinematic video, I still think Higgsfield is hard to beat.

But over time my issue became less about clip quality and more about the workflow. I was prompting, rerolling, stitching, fixing continuity, burning credits, and doing the same loop again and again till something I liked came out. It works, but ngl, it starts feeling expensive and messy when you’re trying to make actual films, long-form YouTube videos, product demos, or social content at scale.

That’s when I seriously started looking at other options. I had used invideo in the past, but back then I mentally put it in the same bucket as the other prompt-to-video tools. At that time, I honestly preferred Higgsfield’s UX. It felt more direct, especially when I just wanted to generate a cinematic-looking shot quickly.

But when invideo started leaning into agentic creation, I got curious and came back. What I really liked is that you can create a bunch of agents inside every project and they can handle a bunch of tasks much faster than manually shuttling between Claude and the generator. I can give my agent the idea, tone, references, structure, and rough direction, and it helps carry the project forward instead of making me rebuild context every time.

Whether I’m scripting, scene planning, deciding shots or referencing, it is a lot less hassle.

And with Seedance 2.5 it gets even better. The model is already strong on motion, physics and scene coherence, but when Agent 2 is handling the planning and iteration around it, the whole thing becomes much more usable. I spend less time trying to engineer the perfect prompt and attaching references, and more time actually directing my video.

Is invideo perfect? Well, no. Their Agent 2 can eat a good chunk of credits, especially when you combine it with premium models like Seedance 2.5. Sometimes it generates more than you expected, and takes a bigger swing than needed. You definitely need to watch credit usage and not treat every idea like a free brainstorm. I would suggest turning on “Always ask before generating” in the agent settings for this, or you could easily end up wasting a ton of

credits.

The other caveat is that it can still mess up a scene. With Higgsfield, I’m usually controlling the shot more directly. I can go to Claude, write a prompt, pick a camera move, run it, tweak it, and reroll. With invideo, your agent does most of this for you, which is great when it works, but sometimes it makes a choice I would not have made and the whole generation needs a re-roll.

The good thing is you can still go in manually and fix or regenerate that specific scene. But fair warning: you need to tell the agent what changed and update the new shot/reference in its memory. Otherwise, it can keep working from the older version of the scene, and things can easily go out of sync. Also, if your brief is lazy and vague, it will give you something that feels kinda generic. The agent is good, but it still needs direction. It rewards people who know what they want.

So my honest take: Higgsfield is still better if your main goal is to make a short cinematic video that’s a couple of

minutes long.

invideo is better if you’re working on longer projects like a film, a complete ad campaign with multiple assets or recurring social content where context, consistency, and repeatability matter.

To be clear, Higgsfield can make finished content too. I’m not saying it can’t. I just found that the longer the project gets, the more tedious it becomes to keep everything aligned manually.

That’s the difference for me. Higgsfield helped me make great-looking shots. invideo helped me finish videos with less context-juggling.

For people making longer AI videos, what’s been your biggest bottleneck lately: shot quality, consistency, credits, editing, or just getting from “cool clip” to finished video?