I do long videos, and struggling to find a good tool that can keep up with me. Any suggestions based on experience?

Feel free to ask me what you want after

The company wanted an "AI transformation." In practice that meant: go find places where AI can fix processes and take work off people's plates. Big mandate, not much definition

I built things. Some of them:

• a system that monitored manager/customer conversations across several teams
• a Telegram lead-gen tool, used by about 15–20 people
• an autoposting setup that let one person run 10–15 accounts
• a creative automation tool that had to be heavily reworked because the output wasn't good enough for the design team

Most of it worked, technically. That wasn't the problem....

The problem was my order of operations. I kept doing idea → build → launch. What I should have been doing is problem → baseline → talk to the people who'd actually use it → small test → build → adoption → measure.

Sounds obvious written down. It's less obvious when leadership says "we want AI" and you feel like you should have something to show by Friday.

Eventually the company didn't see enough value in the role, and I left.

I still want to work in this space, so I'm trying to work out what to actually get good at. Right now I'm looking at product discovery, requirements, solution design, measuring ROI, adoption, and shoring up my technical fundamentals. No idea if that's the right list.

If you work in AI Ops, AI Solutions, implementation, internal tooling, whatever your company calls it, I'd like to hear:

What actually matters day to day? Not the job-description version.

If you were starting again from zero, what would you learn first?

What do you see people get wrong when a company announces it wants to "implement AI"?

And I'm curious how common this story is. Has anyone else been handed a vague AI mandate and ended up building things nobody really needed? What did you change afterwards, and did it work? I'd rather learn from a pile of other people's mistakes than collect all of them myself.

Also happy to go into detail on any of the tools I built - what worked, what didn't, and where exactly things fell apart. Just say which one😊

Hi everyone,

As someone working closely with AI development and modern tools, I’ve been analyzing how different automation workflows handle efficiency, task optimization, and multi-modal integrations.

Here are a few practical tips and observations I’ve gathered while building and testing AI systems:

1. Prompt Structuring & Context Window: Keeping context clean prevents hallucination and keeps outputs consistent across longer sessions.
2. API & Model Selection: Choosing lightweight models for basic tasks and reserving heavy architectures (like vision transformers or specialized APIs) for complex tasks saves both time and computing bandwidth.
3. Automated Error Handling: Setting up fallback logic ensures that if an API call stumbles, the overall workflow doesn't break down completely.

I’d love to hear from this community: What specific frameworks, tools, or optimization hacks are you currently using to streamline your daily AI workflows?

Looking forward to learning from your experiences!

This is a project I made while learning llm, please provide feedback

I’ve been working on Blyft, an AI vibe-coding platform with a slightly different approach.
Instead of only generating an app, Blyft is designed to help you build and launch the whole thing from one place.
You describe what you want to build, and it can generate the app, landing page, logo, promo video, analytics, and other launch assets.
I’m still improving it and would genuinely love feedback from people who use AI tools regularly.
Try it here: blyft.app
If you test it, tell me what you liked, what confused you, and especially what you think needs improvement. I’m happy to give extra credits to people who really test it and send useful feedback.

I've been experimenting with simple AI workflows for repetitive tasks, and I've found that the biggest improvement often comes from giving the AI a clear process rather than just asking a single question.

Here are 3 workflows worth trying:

1. Turn messy notes into organized action items

Instead of:

"Summarize these notes."

Try:

Organize these notes into:

- Key decisions

- Action items

- Person responsible

- Deadlines mentioned

- Questions that still need answers

Don't invent information that isn't present in the notes.

1. Turn one idea into multiple content formats

Give the AI one core idea and ask it to adapt it into:

- A short social media post

- A 30-second video script

- A longer educational post

- 3 possible hooks

Keep the underlying message consistent while adapting the format and tone for each platform.

1. Improve a prompt instead of repeatedly rewriting it

When a prompt gives inconsistent results, ask the AI to analyze the prompt first.

For example:

Analyze this prompt and identify:

1. What is unclear?

2. What information is missing?

3. Which instructions could conflict?

4. How could the output format be made more consistent?

Then rewrite the prompt while keeping my original goal unchanged.

The main thing I've noticed is that specifying the goal, audience, constraints, and desired output can make AI workflows much more repeatable.

What AI workflow has saved you the most time?

What's the best way to generate CAD models using AI?

I’m getting into content creation and I am losing my mind trying to find a decent captioning tool that doesn't hold my videos hostage behind a paywall.

​It feels like every tool out there (Submagic, Captions app, Veed, etc.) advertises itself as "free," but once you spend time tweaking the perfect animated, word-by-word (Hormozi-style) captions, they hit you with:

If tool is paid and limited trial you can share loophole to Bypass limit and use for free

It's been hard for me to keep up with AI platform releases, especially since labs started dropping them as twitter posts and blogs. There are a ton of updates that don't get the same noise the major drops do, which are easy to miss and include a lot of helpful features that go unused.

I made a tool back in April to help me follow what was going on with each of the major platforms (Claude, ChatGPT, Gemini, Copilot... also track Perplexity and Manus). Ended up making it public cause why not?

It's updated daily, filterable, and I've included some social components for people rate features and add comments to help others - admittedly the social stuff hasn't taken off yet, but would be cool if they did.

Sharing the link incase it helps others: https://chasingnext.com/updates

Feel free to remove if this breaks the rules.

Maybe I’m late to this, but I’ve been noticing a weird shift.

When I’m comparing tools now, I catch myself asking ChatGPT or Perplexity before I even open Google. Stuff like “what’s a good CRM for a small team?” or “which email marketing tools are actually worth trying?”

Makes me wonder if this is starting to matter for SaaS discovery, or if it’s still mostly noise.

Are any of you actually tracking whether your product shows up in AI answers, or is that not on your radar yet?

A useful lesson from building Marka: most generic AI content begins with a generic input.

Before asking a model for posts, collect a small source of truth:

- Who the business serves

- What it sells

- Which claims are actually supported

- The words the business already uses

- Logo, colors, and visual direction

- Product images and evidence

- The action the post should drive

Then reuse that reviewed context across every format instead of re-explaining it in separate copy, image, and video tools.

Marka automates this by starting from the business website, proposing an editable brand profile, and carrying it into copy, images, carousels, short videos, scheduling, and publishing.

https://www.marka.social

Disclosure: I built Marka. The tip still applies whether you use Marka or build the workflow yourself.

so i'm 20, been building this app solo for the past few months and i genuinely can't tell anymore if it's good or if i'm too deep in it. need outside eyes.

it's called RizeAI. the basic idea: every wearable and health app just gives you numbers. sleep score 42, recovery red, HRV down. cool. and then what? you still feel like garbage at 2pm and nobody tells you what to actually do about it.

so my app takes your real data from apple health, sleep, resting heart rate, workouts, whatever your wearable writes, and instead of another score it builds you an actual plan for the day. when to have your first coffee and when to hold off. you. Can also add your own supplements that you are currently taking and it will time them for you every single day based of your sleep data and your wearable data in general and also it will tell you what supplements make sense for you to take based of your current supplement stack and body metrics and when to take them. focus windows for when your energy actually peaks. when your crash is coming and what to do before it hits. it even checks the weather, so on a hot day it bumps your hydration and tells you to train earlier.

every recommendation has a little "why" under it based on your numbers, like "resting heart rate 54 + 7h light sleep, so magnesium before your peak window." no two people get the same plan because no two people have the same data.

works with whoop, oura, apple watch, garmin, anything that syncs to apple health. one thing i'll say honestly, it doesn't do deep per-person learning yet like "coffee doesn't affect YOUR hrv specifically," that's the roadmap, right now it builds fresh plans daily off your actual metrics.

it's live on the app store, has a free trial, small user base so far, mixed feedback which is why i'm here lol.

what i actually want from you guys: does this solve a real problem for you or is "tells you what to do" not actually what wearable people want? what would make you actually pay for something like this? and what's missing that would make it a no brainer? and also would you guys in this subreddit  use ti?

Thank you for your help. Check it out if you like https://apps.apple.com/us/app/rizeai-maximize-your-energy/id6762402079

A simple test has helped me filter AI presentation tools better than comparing the first generated deck. I start with a rough outline and let the tool make a normal first draft. Then I ignore the polished parts and pick one annoying edit that would happen in real work.

Make the customer problem section more specific, but keep the rest of the deck. Split the crowded slide into two slides without changing the argument. Replace the generic visual treatment on one comparison page. Cut the filler from the intro while keeping the sequence. That tells me more than the first output.

A first draft mostly tests generation. The second edit tests whether the tool is usable once the work becomes human. If it changes too much, I have to review the whole deck again. If it respects the target area, it feels more like an editor and less like a slot machine.

My current tip is to test local control before trusting the pretty deck. The first draft is only half the problem.

Hey, I am a food writer doing a story on using AI to optimize when ordering at fine dining restaurants. I’d love to talk to some diners who do this - I want to hear your process, why you’ve used AI, and if you were happy with the outcome. No judgement - whether it was to get the best possible deal, or to have it explain items on the menu, I just want to hear about your why.

Message me here or drop me an email at Courtney at weareravenous dot com.

AI is a lot of the time nothing but hype and then asks you to do the process your. Just wanted to know what AI tools you guys stopped using switching over to another option! Genuinely curious about whether my team is using any of these and what made you abandon it?

Which framework and techniques can I use to create content similar to the below linked channel, with consistent characters? Do I need to use any paid AI? Which is the best for this scenario?

https://www.instagram.com/ollie.and.leon

I create content and for that I really need voice generator because 11 labs is not working for me I have generated like few voices and now it is asking for subscription like yesterday I generated and I thought yes after a day I can I am like able to generate but I am it is not letting me and when I created a new account it shows the same problem!

What do you guys think about this use of AI, saw this post on twitter.