If you're still paying for shoots, actors, or agency retainers to get cinematic-quality ad videos, there's a faster and far cheaper way to do it now.

SuperMaya.AI generates studio-quality cinematic ads from a single product brief. No camera, no crew, no weeks of back and forth with an editor.

Here's why it's hard to beat on both speed and price:

Cheapest in the game. Polished cinematic videos start around $7 each. Compare that to a traditional shoot, which can run into thousands of dollars per video before you've even tested if the ad works.

Insanely fast. Up to 100 videos generated per hour. What used to take a production house weeks now takes an afternoon.

Built for volume, not just one hero video. Run up to 1,000 to 1,200 ad variants in a single campaign, so you're not betting your entire budget on one creative direction.

Know what'll work before you spend. Every video gets a pre-launch performance score, so you can kill weak creative before it burns ad spend, not after.

Actually licensed. Training data is licensed and traceable, so you're not risking a copyright strike or a platform takedown down the line.

Built by people who know ads. The team is IIT and BITS alumni plus veterans from the ad-tech space, and brands like Belkin, Amazon Now, Liquid Death, Gameloft, and Corona are already using it.

Looking at a few AI tracking platforms right now including Brand Radar, Profound, Semrush and a few others.

Which one actually has the best reporting insights? Mostly interested in useful data rather than just another visibility score.

Hello all, I am building an AI agent swarm to manage ecom social media accounts, and phone verification took longer to figure out than the rest of the stack combined. Sharing my notes here so others can skip the headaches.

What failed

Temp non-VoIP OTP pools: Great for a single code, useless for ongoing account management. Numbers get recycled within days, so when Meta or Telegram demands a re-verify a week later, you're locked out. Also, the lack of an MCP server meant I’d have to build and maintain custom API's for their dashboards.

Virtual VoIP: Rejection on arrival. Carrier lookup flags them instantly as VoIP, and platforms like Telegram or Meta block them immediately.

What actually worked

Dedicated non-VoIP lines: One real carrier line assigned per agent on a monthly renewal. Because it registers as a legitimate mobile line, it passes carrier lookups, and the agent keeps long-term ownership of the number.

Direct MCP Integration: Wired the agent directly to non-VoIP provider with a native open source MCP server from Voidmob. Their documentation had a few endpoint quirks to figure out initially, but having the agent directly query SMS codes via tool calls saved me from building a custom API backend.

Costs a way more than cheap OTP pools, but it completely removes the headache of burned accounts and broken re-verifications. I have tried another dedicated lines but it turned out to be VoIP which was not suitable for my workflow. So I came up that paying more for real number is the case since my agents run important accounts.

Curious how others are giving access to AI agents and real phone numbers for them.

What's the thing you keep working around instead of fixing?

I've got a 22-hour build window this week and four themes to pick from. Rather than invent a problem, I'd rather build something an actual practitioner is annoyed by. The themes:

• UX in AI — how people interact with, trust, correct, or supervise AI systems
• Data for AI — pipelines, quality, lineage, labelling, retrieval
• Security & governance at scale — access, audit, policy enforcement across many systems or agents
• Physical AI — robotics, simulation, digital twins

What I'm asking: in whichever of those you actually work in, what's the recurring annoyance you've built a hacky workaround for and never properly solved? The thing that costs you 20 minutes a week, or that you've explained to three different new hires.

Not looking for startup ideas or moonshots. Looking for small, specific, real. Bonus if you've already tried something and it didn't work — I'd like to know why.

I'll post back with what I build and whether it worked, including if it didn't.

I’m a marketer with ADHD who works at a travel agency

while also handling development tasks on the side.

I’m also working on a side project to develop a healthcare app for seniors.

Since I work in a small team, we have a lot of meetings,

but during meetings, it’s impossible to organize my thoughts in my head,

and in my case, even when I wanted to take notes in real time, it was hard to concentrate.

However, using Miller or Granola has been great because I can review the meeting minutes

and check the action list right after the meeting.

I’m curious to know how others are getting help from AI.

It would be great if you could also share your job titles.

I just started working on a side project around how people actually use AI, and I realized I may have made a pretty big assumption without checking if it's actually true.

I assumed a lot of people still struggle to get tools like ChatGPT, Claude or Gemini to do what they actually want — like asking for something, getting a result that's not really what they had in mind, and then having to go back and forth trying to fix it.

But... is that actually a problem?

Does this happen to you? Or maybe to people around you? And if it does, what usually makes using AI difficult or annoying for you?

I hv bunch of notes/documents for a presentation already written,but the actual slide-making is taking longer than writing the content

I don't really need I to do research nd write topics from scratch. I basically want to give it my existing material and hv it turn into a coherent presentation with decent layouts and visuals

Has anyone found a tool that actually does it well?

I'm mainly looking for something where I can give it a Google Doc/PDF/text and get a solid first draft rather than starting with a blank PowerPoint.

my boss keeps sending mo voice memos and zoom recordings to transcribe and im literally losing my mind. tried a few free ones but they totally butcher the words especially whem people talk fast. what ai audio transcription tool do you guys use for messy audio. just need something simple that doesnt cost an arm and a leg tbh

I've tried a few of the AI app builders and I noted the same pattern.

The first 70% is ridiculously easy. Making a dashboard or landing page gets done in minutes but when i need a proper database record and make something that works, it consumes so much time and credits, that it becomes unreasonable.

For people who have shipped something, what are you using?

Emergent, Lovable, Replit, Bolt, something else?

I am looking for something that can build basic backend and make something I can demonstrate end to end.

Hey everyone,

I’ve been working on PixCraft, an AI-powered photo editor for Android, and I’d love to get some honest feedback from the AI community.

It currently includes tools like:

• AI Face Swap

• AI Headshot

• AI Avatar

• AI Background Removal

• AI Photo Enhancement

• AI Travel & Cosplay effects

• AI Time Travel

• 50+ photo editing and creative tools

I’m still actively improving it, so I’m especially interested in feedback on:

- AI result quality

- Which features are actually useful

- UI/UX

- Features you think are missing

If you try it, I’d really appreciate honest feedback — positive or negative.

Thanks!

I’m working on a startup idea called MyYearMovie.
The core idea is simple:
For 365 days, an AI Director follows your life, remembers the important people and events, and turns your year into a personal book and a short movie.
The user can speak or type.
The AI should remember:
people and relationships
important events
changes in your life
unfinished stories
recurring themes
personal turning points
So if you mention someone in January, something happens with them in May, and they appear again in October, the AI understands that this is one continuing storyline.
At the end of the year, the user gets:
📖 A personal book about their year
🎬 A cinematic short movie based on their real life
Users could upload photos of important people as visual references. If they don’t want to upload photos, they could describe the person and the AI would create a consistent visual character for the movie.
For the MVP, I want to start much smaller:
voice/text entries → AI memory → character tracking → monthly story recaps → short cinematic trailer
I don’t think the main innovation is AI video generation.
The main product is the combination of:
AI memory + personal storytelling + real life + generative media
I’m currently looking for:
a technical co-founder
AI / LLM / memory-system developers
mobile app developers
people experienced with generative video
early-stage angel investors interested in consumer AI
I’d also really appreciate honest feedback.
Would you use something like this for a full year?
And what would be the biggest reason you would stop using it?
If you’re interested in building, investing, or discussing the idea, feel free to DM me.

There are so many AI API options now like OpenAI, Anthropic, Google, Mistral, Cohere, Groq, and more, and it keeps expanding.

If you were building a real production app today and had to commit to just one provider, which one would you pick? Curious what matters most in your decision too, whether it’s cost, output quality, latency, reliability, or something else entirely.

i still have old software on my computer that i paid for once years ago.
it looks ancient, but it still opens. there's something weirdly nice about that.

AI tools have made me realize how much i miss that model.

I understand why generation is different. every time something gets rendered in the cloud, somebody is paying for the compute. when i'm using image-to-video in DomoAI, credits are part of that side of the workflow too.
that part makes sense to me.
what i miss is the feeling that the tool itself is mine even when i'm not actively generating anything.

I'd honestly be pretty happy with a setup where i buy the basic software once, keep using it for normal work, and then pay separately whenever i need cloud generation.
maybe that model just gets harder once so much of the useful stuff depends on servers.
still, i don't really want another monthly bill just because i occasionally want to generate a few clips.
would you rather pay once for the software and then pay for AI compute as you use it, or does a subscription actually make more sense for this kind of thing?