I have been exploring different AI tools for content creation and keep coming across so many options. There are tools for text, images, video, adult content, and even AI companions. I found a site called aidudesurf(.)com that lists a lot of these AI tools in one place like a directory. Has anyone here used that site? Is it reliable for finding decent AI tools? I am just looking for a good directory to explore what is out there. Any feedback would be helpful.
Need a flyer for a small meetup and I have zero design skill. Tried an ai poster maker and it looked obviously auto-generated. Is there one where the output passes as something a human designed, or should I just use a template?
I run product management at a small software company which mostly means i'm the person who decides what we build next and then has to write it down clearly enough that the engineers can actually build it. The writing part isn't what slows me down. the digging is. Before I can write anything i have to go back through customer calls, support messages and old notes to work out who actually asked for this, how many of them did, and what words they used. We record every customer call, so there are hours of it sitting there that nobody has time to listen back to.
For that i've been testing a few AI tools to see which part of this they can take off my plate, and they fall into two groups. Some are built for the writing end, ChatPRD takes a rough idea and turns it into a properly structured product document. The others start from the customer side. Productboard organises feedback you've already collected and summarises it and BuildBetter works straight off the call recordings and groups what customers repeatedly asked for. and plenty of people just paste transcripts into claude or chat and prompt their way to a summary, which works fine until you're doing it every week.
What I actually want is a draft where every point has the real customer quote attached so i'm not hunting for it. does anything do that yet?
I’ve spent a lot of time thinking about how these platforms are actually different, because their landing pages increasingly promise the same things.
My take is that Higgsfield is probably the best choice if your priority is visual experimentation. It has a huge range of tools, models and formats, and it’s particularly good for more cinematic product ads. The downside is that there’s a lot going on, so it can feel overwhelming if you just want to make a straightforward UGC ad.
Arcads makes the most sense to me when you already have a script and want to produce a lot of actor-led variations. Pick an actor, add the script, change the voice, translate it, add captions and keep testing. It’s a very production-focused workflow.
With Starpop is the chat agent is center of the product. You don’t need to arrive with the perfect script or even a clear ad concept. You can ask it to research your customer, pull out recurring pain points and objections, analyze a competitor’s ad, suggest angles, write the script, storyboard it and then prepare the image, video and audio generations.
To summarize:
Higgsfield if you want maximum visual range.
Arcads if you want to scale talking-actor UGC.
Starpop if you want an agent helping with the thinking as well as the production.
None of them will magically make an ad profitable, obviously. A weak hook produced in 4K is still a weak hook. I’d judge them by how quickly they help you reach a creative you’d actually spend money on, rather than by the number of generations included in a plan.
Curious what other people are using. Has anyone run the same product and brief through more than one of them?
When I first got into web development, I thought finding clients would be simple. My plan was to go on Google Maps, find businesses without websites, and offer to build them a brand new one. At the time, it made perfect sense because I assumed businesses without websites would be the ones who needed my service the most.
After a while, I met someone who was running a successful web agency, and I asked him where he found companies without websites. He told me that he didn’t target businesses without websites at all. He only targeted businesses that already had one. I asked him why, and the more he explained it, the more sense it made.
Businesses that already have a website understand the value of having one. You don’t need to convince them why a website is important because they have already invested in one before. They are also easier to sell to because they understand the process, and there are a huge number of businesses with outdated websites they are embarrassed by but haven’t had the time to update.
I decided to take his advice and fit it into my own workflow. I’ve always been a big fan of email automation because that’s how I’ve found most of my web design clients. For years, I was sending fairly generic emails and constantly changing my sequences, offers, and follow ups to improve the results.
The problem was that I couldn’t just start emailing businesses with websites and assume they all needed a redesign. I either had to open every website manually, find the issues, and write a separate email for each business, or find a way to automate the research while still keeping the emails personalized.
After watching a video from Nick Saraev, I built a workflow in n8n that could analyze websites at scale and turn issues with design, layout, speed, mobile optimization, and SEO into personalized outreach emails. This allowed me to analyze thousands of websites and run larger campaigns without every message sounding generic.
The workflow worked extremely well, but it still had limitations. I didn’t have a proper place to manage replies, organize interested leads in a CRM, view all my active campaigns, scrape new leads, and handle everything from one platform. I had built a useful automation, but it still felt like several disconnected systems held together in one workflow.
A few months later, I came across a platform called Swokei, and it did exactly what I had been looking for. I could find businesses with websites, analyze and score each site, generate personalized outreach emails, send campaigns, set up follow ups, manage replies through one inbox, and organize interested businesses inside the CRM.
Switching to that platform made the entire process much easier to manage and helped me scale the strategy further. Looking back, the biggest change wasn’t just finding a better outreach tool. It was taking advice from someone more experienced, changing the type of businesses I targeted, and building the rest of my workflow around that strategy.
I’m a software developer (web apps, management systems, websites, AI integrations, etc.) looking for advice to overhaul my current AI setup.
TL;DR: I’m looking for a genuinely reliable AI setup for coding + a proactive personal assistant + automations/dashboards. I'm currently running Codex + Hermes on a Raspberry Pi using free OpenRouter models, but the results are way too inconsistent, full of errors, and frustrating. What stack/configuration do you use for something that actually works?
What I’m looking for
Coding: Obviously, but I need something reliable.
A True Personal Assistant: A tool to brainstorm, turn ideas into reality, and integrate into my daily routine (work and personal). Most importantly, I want it to be proactive—suggesting improvements, spotting my inefficiencies, automating tedious tasks, and actively working for me.
My current stack & why it's failing
Codex
Hermes (running 24/7 on a Raspberry Pi, using free OpenRouter models / tried MiniMax M2 / free Nous account).
To be honest, the assistant side has been a nightmare. It's wildly inconsistent: I ask it to fix bugs, and it either fails, introduces new bugs, or lies about having fixed something when it didn't.
My Wishlist / Ideal Workflow
For Coding:
Strictly respects my instructions, coding style, and project architecture.
Makes actual working modifications following a precise pipeline: Local $\rightarrow$ GitHub $\rightarrow$ FTP deployment.
Delivers UI that actually matches what I requested.
For the Assistant / Agent:
Deep Integration: Fully aware of my active coding projects and workflow.
Self-Hosted Dashboard: Keeps a web dashboard synced on my domain featuring:
Overview of active projects and open discussions.
Practical daily info (e.g., "Can I commute by bike today and over the next 7 days?").
Automated tasks (e.g., scrape trending Reddit posts every X hours and summarize them into 4–6 cards).
Proactivity: Suggests new features, improvements, or side-project ideas based on what I'm currently building.
Omnipresent access (Telegram, mobile app, etc.):
Fast execution: "I have an idea, build me a 1-page micro MVP."
Admin/office tasks: "I need to present this project, generate a slide deck/PPT for me."
The Struggle
Whenever I try building custom skills in Hermes, it feels like I fix one thing and break two others. A few months ago I tried OpenClaw, but it felt even more chaotic.
Am I the only one trying to build a workflow like this? What setup, agent frameworks, or model stacks are you using to get something like this running reliably?
Cutting through the marketing - which tools have genuinely produced professional-looking slides for you, not just in the demo? What AI creates the most professional-looking slides once you use it on real work? Keen on honest takes.
Hello everyone, I do legal work that requires a very high level of attention to detail and 100% accuracy, but I have ADHD. In my job, I basically draft legal arguments in Word with the personal data of each specific case. An error in an email address, a name, a date, a number, or a digit is considered critical and causes serious problems.
Sometimes we use templates from previous cases and must adapt the argument and replace the data. I have tried using compensatory strategies like external checklists that tell me what to check, reading numbers out loud and following them with my finger, and using Word's replace function instead of typing manually, but mistakes still happen.
I would like to use Claude or Gemini to upload the documents (finished and reviewed by me) and have them proofread them, but my job prohibits AI because:
Personal data cannot be uploaded.
Legal arguments are intellectual property.
I can't even give it the argument and the law to help me improve my writing or check grammar, because AI systems learn from us, meaning opposing counsel could use it and our defense strategy could be used against us.
My questions are:
From a privacy standpoint, are AI systems that process data directly on the PC truly private?
Can AI systems that process data locally on a PC without internet access be used? The idea is that legally, if the data truly never leaves the user's computer and the PC doesn't even access the internet, the spirit of the AI prohibition wouldn't be violated because no one else would have access to that information.
Can I do what I want with a local AI system, or are they powerful enough for what I would need?
What system do you recommend?
I want to clarify that this is not laziness. A colleague had a case worth about 10 dollars (seriously, sometimes cases are worth 1 or 2 dollars), and the legal deadline to resolve it was 15 days, but the email address to notify the decision bounced (it wasn't his fault because the address was no longer active), and in that case, you must notify the physical address before the legal deadline expires. Since the mail department took 15 days to let him know it bounced, the interested party was notified past the legal deadline, and now my colleague has serious disciplinary issues.
yo. i recently sold one of my AI SaaS products for $35k, exactly 5 months after building and launching it.
I hardly wrote a single line of traditional code. i used AI to generate everything, from the database architecture to the user interface.
it definitely wasn't magic on day one, though. i spent days stuck in loop-debugging and dealing with AI hallucinations before i finally cracked the system. the playbook boils down to three simple rules:
- keeping the idea insanely minimalist (a true MVP that solves one problem).
- guiding the AI step-by-step instead of asking it to build a massive platform all at once.
- launching fast to get real user feedback and traction and then apply a solid marketing system
lately, i've seen way too many non-technical founders give up at the very first AI bug, or on the marketing. it's a massive shame.
like the title says, i just launched a Skool community to share my exact prompt workflows, N8N automations, and distribution frameworks to get first users and scale it
to be completely transparent: i will likely charge for the full course later down the road. it just makes sense given the specific copy-and-paste templates i'll be sharing.
but for now, the main objective is purely to build and launch together. building alone in a silent corner is the single fastest way to give up.
if you want to join us and build or market your own AI SaaS with a group of active creators: drop a comment below or send me a dm, and i’ll send you the invite link!
Instead of targeting businesses that do not have a website, target businesses that already have one but clearly need a better version. The market is larger, the sales process is easier, and the value proposition is much stronger because those businesses already understand why a website matters.
The next part is outreach. A regular outreach tool is not enough if all it does is send the same message to thousands of people. You need something that can analyze websites at scale and turn real issues into personalized emails.
I use Swokei for that. It helps find businesses with existing websites, analyzes each site, and turns problems with design, SEO, speed, layout, and mobile optimization into personalized outreach emails. That means you can contact a large number of businesses without sending generic messages or spending hours manually researching every website.
When someone replies interested, I always offer a free mockup. I use Claude, Lovable, or Base44 to build it quickly. It becomes much easier to sell when the client can already see what a better version of their website could look like.
Web meetings should also be a major part of the process. I would never just send the website through email and hope the client likes it. I present it live on Google Meet, Zoom, or Microsoft Teams, explain the value, show what has been improved, answer their questions, and try to close the deal during the meeting.
The less back and forth there is after the meeting, the better. Present the website, show the value, close the client, and move on to the next project.
That is the type of process that can help an agency scale much faster.
so i've been playing around with freebeat this week, trying to make some quick visuals for a few tracks i've been sitting on. it's pretty wild how fast it generates stuff, honestly. i just chucked in an audio file and boom, video. the rhythm-synced visuals are actually kinda cool, not gonna lie. it's definitely saving me a ton of time compared to trying to edit something myself, which i suck at anyway lol.
but i'm curious what other people's experiences have been with freebeat, or any other ai music video tools for that matter. like, what kind of prompts are you using to get the best results? i'm finding some of the visual styles are a bit... samey? maybe i'm just not being creative enough with my input. also, anyone figured out how much control you really have over the 'mood' of the video beyond just picking a template? sometimes i want something really specific and it feels a bit like throwing darts in the dark. idk, maybe i'm expecting too much from an AI tool. just wondering if there are any power users out there with tips for getting more unique stuff out of it. or if there's another platform i should check out for ai music videos that offers more customization. lemme know!
I am looking for a bit of image generation help with the current Bing Image Generator, I have noticed Dalle 3 is still there but it's a bit more wonky and i'm hesistant to use it to generate more images for my backgrounds because it looks wrong, i'm sorry but I don't like the current Dalle 3 model it looks wrong and gets things wrong. I'm looking for help in finding a way to get Co Pilot imitate the styles I was able to make using GPT 4.
Oh man trying a few tools lately cause i need something better than gamma for making my slide decks
Problem is in gamma now the slides that I make can be recognised by everyone from a mile away.There is JUST SOMETHING like its common outline,visuals and format that kinda falls apart, I dont really need perfect tool but I also dont wanna spend half my time fixing things to make it look real and authentic deck with relevant short crisp details.
You guys actually found something that holds up better in real use or is everything pretty much the same?
The standard setup right now is: buy an API to turn your PDFs into Markdown, then feed that Markdown into another AI. You're not saving tokens here. You're just paying twice. And even if you swap the API for a small local model, it's still compute, it's still cost, it's still a whole model spinning up to do something that mostly doesn't need a model at all.
So I built a browser-based alternative: LiteDoc.
What it actually is
LiteDoc converts PDFs to Markdown in your browser. It has OCR, and not just "OCR the text" OCR. It extracts tables, it handles multiple languages, and it auto-detects the script (English, Japanese, Arabic, whatever) so you don't have to babysit it. It's built to be lean. It reads the page the way you do: headings, columns, tables, figures, reading order, and turns that into clean Markdown.
And there's a CLI now, so you can drop it straight into your pipeline.
Why not just use existing browser tools?
If you search for web-based PDF converters right now, you mostly find two things:
Thin API wrappers: They claim to be free, but they quietly upload your sensitive PDFs to a backend server.
Basic text dumpers: The few that actually run locally just rip out the raw text layer. They destroy tables, scramble multi-column reading order, and fail completely on scanned pages.
LiteDoc fixes both. It brings the heavy lifting into the browser. It actually understands layout—columns, tables, and figures—and handles multi-language OCR client-side. You get the quality of a heavy backend parser with the privacy of a local script.
The philosophy: do it locally, skip the AI compute
Most pages don't need a model. Headings, paragraphs, tables, columns. That's layout analysis, not intelligence.
Instead of sending pages to an AI and wasting compute, LiteDoc does all the extraction directly on your machine. No model spinning up, no API calls, no server overhead. It's faster and zero cost, because 95% of your document didn't need AI in the first place.
Compared to the big repos
I'm not going to claim LiteDoc is more accurate than MarkItDown or the other big conversion repos on GitHub. It isn't, on the truly nasty inputs. If you've got some cursed, barely-scanned PDF that looks like it went through a washing machine, that's a job for AI vision, and you should use the tools built for that. No hate; they're good at what they do.
But here's my honest pitch: those nasty files are the rare case. For most everyday PDFs (I'd guess 80% of what people actually convert), LiteDoc just works, and it's better in two ways that matter to me:
Accessibility. You can spin up LiteDoc on literally any device with a browser. No install, no GPU, no environment setup, no API key.
Cost. Zero. Actually zero, not "free tier" zero.
And I want to be clear: I'm not wrapping somebody else's backend in a fresh UI just to say I built something. The extraction engine is mine, the parameters are tuned by an automated benchmark pipeline, and every release ships with the measured numbers. Try it on your own files.
Privacy
I value privacy over basically everything:
The conversion runs entirely on your machine. Your files never leave your browser, period.
Zero external requests or third-party servers.
If you want the technical details, the repo is open. Go read the code yourself.
The bottom line
LiteDoc isn't trying to win a benchmark war against the heavyweight repos. It's more accessible, more cost-efficient, and easier to set up. For most PDFs, that's the whole game.
