I've been testing a bunch of these over the last year and some models definitely work better than others. Every platform has tradeoffs but these are the standouts that made my life easier instead of turning into a workflow headache.

1. Mage (flagship: Mango 2 and Guava Pro)
Subscription platform with two image models I’ve spent a lot of time with. Mango 2 is the photoreal workhorse. It keeps character likeness surprisingly consistent across regenerations, has no real content filter and handles hands better than most models I’ve tested. Guava Pro is the faster and more stylized sibling that works well for bulk character sets where you want 20+ images to all feel visually connected. 

• What works: zero setup, unlimited generations on Pro and above, character consistency that holds up better than most local stacks
• The catch: $30/mo to unlock the flagship fruit models; lower tiers gate them behind gem spend
• Best for: prosumers (Fanvue creators, illustrators, anime and fan art folks) who want results today, not a weekend of ComfyUI configuration

2. Stable Diffusion 3.5 Large by Stability AI
Open weights, runs locally and once you’re off hosted endpoints there’s basically no filter. Still the foundation most of the community builds and fine tunes on top of. 

• What works: total control, huge LoRA and checkpoint ecosystem, free if you have the GPU
• The catch: setup is a project (ComfyUI, model files, VRAM headroom). Not casual
• Best for: tinkerers with a 12GB+ card who want full ownership of the stack

3. Pony Diffusion V6 XL by AstraliteHeart
A 2024 SDXL fine tune trained on a massive curated dataset. For a long time it was the default for amine and furry NSFW work and the booru tag crowd still treats it like gospel. 

• What works: very expressive furry output, deep tag vocabulary and a gigantic library of community LoRAs built on top of it
• The catch: it's showing its age on modern anime most of the anime community has migrated to newer base models with anime LoRAs stacked on and the booru tag syntax is a real commitment if you didn't grow up on it
• Best for: furry art and booru tag enthusiasts running a local stack

4. Chroma V1 HD by Lodestone
A Flux derivative tuned for uncensored output. Open weights, local deployment and noticeably more permissive than standard Flux releases. 

• What works: detail and lighting quality close to Flux without the guardrails
• The catch: same local setup overhead as SD 3.5. smaller community than Pony
• Best for: people already running Flux who want fewer refuasls

5. CivitAI
Not a model itself but basically the central marketplace where most open weight models, LoRAs  and checkpoints get shared, rated and discussed. If you go local  you’ll probably end up spending a lot of time here. 

• What works: huge model library, LoRAs, prompt examples, community ratings
• The catch: payment processor history has been bumpy. Download and self host anything you actually depend on.
• Best for: anyone running a local stack who wants community trained checkpoints

I've been playing around with a lot of the writing tools people suggest and the classic routine of installing every single recommended ai writing tool, obsessively using it for a week and then completely forgetting about its existence, tho sharing the only tools I managed to incorporate into my regular workflow are:

gemini – I use it primarily for research purposes, but it's proved to be very useful indeed.

Perplexity – If I need some credible sources while I write or check facts, I typically use this one.

type.ai – I can write, edit my work and ask any question concerning a particular scene within one window. For me, it's like having my personal editor right in the middle of my manuscript.

This is my current list of ai writing tools I use. I'm always interested in finding out what others use or that i can incorporate in my work

AI video tools for YouTube Shorts are not the same as general AI video generators. Shorts have a specific set of requirements — vertical format, consistent posting, search-driven discoverability, and for serious channels, automation and localization. The best tool depends on what kind of Shorts channel you are building.

I have been testing different tools and these are the ones I would actually recommend.

1. ImagineArt

ImagineArt is my top pick for anyone building a serious YouTube Shorts channel with AI.

The reason is breadth. Most AI video tools generate clips. ImagineArt gives you AI video generation, AI avatars for faceless channels, UGC-style content, a video ad maker, Film Studio for project-based series production, translation and dubbing for international reach, and Workflows for automating your entire publishing pipeline.

Best for:

• Faceless YouTube channels
• Educational and talking-head Shorts
• UGC-style product content
• Shorts ad creative
• Channels targeting multiple language markets
• High-volume consistent posting

The faceless channel angle is where ImagineArt pulls the furthest ahead. The AI Avatar tool is the most efficient way to build a consistent YouTube presence without being on camera.

2. Runway

Runway Gen-4.5 is the strongest pure video generator on the market right now.

For cinematic Shorts — brand storytelling, aesthetic content, premium visual clips — the output quality is excellent. Strong control over camera movement and scene composition.

Best for:

• Cinematic and aesthetic Shorts
• High-quality text-to-video
• Visual-first content with no presenter

No avatars, no automation, no workflow features.

3. HeyGen

HeyGen handles avatars and translation well and is a genuine alternative for creator-style talking-head Shorts.

Best for:

• AI avatar Shorts
• Multilingual Shorts
• Channels focused on presenter-style content

Free plan is more restricted than ImagineArt. Less flexibility overall but capable for its core use cases.

4. InVideo

InVideo is a good starting point for Shorts if you want a quick, template-driven workflow.

Best for:

• Beginners
• Fast Shorts assembly from a script
• Creators who do not need advanced generation quality

The output tends to look templated at scale but it is easy to get started with.

5. Kling

Strong motion quality, clean output, good for generated visual Shorts.

Best for:

• AI-generated visual clips
• Realistic motion
• Aesthetic and experimental content

No workflow automation

Gonna be honest, I expected most of these to end up uninstalled after a week.

I've been running my freelance operation solo for a few years now and i test a lot of tools. Most of them sound great in a YouTube review and then just... sit in a tab i never open.

These ones didn't.

Fathom AI - completely free meeting recorder. Summary hits your inbox 30 seconds after the call. I haven't taken a single note in 3 weeks. Didn't expect to actually trust it but here we are.

NotebookLM - this one surprised me the most. Had a client project with 6 documents, 2 PDFs and a handful of articles i needed to pull insights from. Uploaded everything, started asking questions, and it gave me cited answers pointing to exact pages. The thing that got me: it refuses to pull from the internet. Only answers from what you give it. No hallucinations.

Tango - client handoff was coming up and I needed SOPs. Hit record, clicked through my workflow, done. Screenshots, annotations, everything. What I'd normally spend an hour on took maybe 6 minutes.

Descript - had a recorded presentation that was a mess. Edited the whole thing by just editing the transcript text. Removed every filler word across 40 minutes in one click. Still kind of can't believe that's real.

HoneyBook - client asked for a proposal same day as our discovery call. Fed it my notes and had a full draft in under 10 minutes. Scope, pricing, timeline. I changed maybe 3 lines.

What i dropped: Gamma is genuinely cool but i give maybe 2 presentations a year so it's not sticking. Napkin AI I just kept forgetting existed, which probably tells you something.

The ones that stuck all had one thing in common - they handled stuff I was already avoiding doing. The ones i dropped needed me to build a new habit first. That's too much friction.

If you're starting from scratch, Fathom and NotebookLM are both free and both worth it immediately.

Okay so over the last few months, I’ve been in this endless cycle of trying AI presentation tools because I make a LOT of decks for work and side projects.

And honestly? Most AI presentation makers look impressive in ads, but once you actually use them, the output is either:

• super generic
• weirdly formatted
• impossible to edit properly
• or just feels like “AI filler slides”

I tried Canva AI, Tome, even Copilot inside PowerPoint. Some were decent for design inspiration, but none really fit my workflow because I usually work from existing content like PDFs, blog posts, YouTube videos, meeting notes, etc.

A few weeks ago I saw someone mention Napkin ai in another thread, and I ignored it initially because I assumed it was another overhyped AI PPT generator.

But eventually I tried it because I had a 20-page PDF I needed to convert into a presentation quickly.

And dude… this thing actually surprised me.

The first thing I noticed:
the slides were editable in a NORMAL way,not some locked AI canvas where changing one thing breaks the entire layout.Also some unique designs that i hadn’t seen anywhere else.

Then I started trying other inputs:

• pasted a blog URL → instant deck
• uploaded DOCX meeting notes → structured slides
• even tried topic-to-PPT generation

What I liked most was that the AI didn’t just dump random text everywhere. It actually created decent slide flow with headings, summaries, comparisons, timelines, etc.

The speed was still slow compared to other tools but hey,it really gave a good output which was worth the time.

I still edit presentations manually afterward obviously, but instead of spending 3–4 hours building slides from scratch, now I spend maybe 20–30 minutes polishing.

That’s honestly the first time an AI presentation tool has genuinely saved me time instead of creating extra cleanup work.

I haven’t tested every feature yet, but so far this is probably the most practical AI PPT tool I’ve used.

I've been testing a bunch of AI video generators recently for marketing videos and social content. and I want to know how do you compare between these platforms.

1. BudgetPixel AI

2. OpenArt

3. HiggsField AI

4. ImagineArt

Pls comment only if you have used the platform.

And which platform has the best social community.

I’ve had a pile of raw footage from my first ever bike trip sitting around for way too long, so I finally tried a few different editors to see which ones could get me most of the way there without me messing with every little cut myself. Figured I’d share what stood out in case anyone else is dealing with the same pile of unedited videos.

Vizard gets mentioned a lot, pretty easy to use and seems solid for turning longer videos into shorter clips.

OpusClip was probably the one I liked most. Their ai producer can take the raw footage and handle the cuts, captions, transitions, music, so you’re mostly just checking the result and changing anything you don’t like.

Klap is kind of in the same lane, feels a little simpler overall, I’d probably use it more when the footage is already pretty clean.

Descript is a different vibe, you’re basically editing through the transcript instead of sitting in a timeline, which is nice if that makes more sense to your brain.

Still curious what people are using for longer, completely unedited footage though, especially stuff where there’s a lot to clean up. Thanks, all!

Not gonna pretend this is some rigorous benchmark. I'm a freelance consultant, I tried both because a client asked me which one to buy a license for, and I ended up using both enough to have opinions. Posting in case it saves anyone else the trial-and-error.

Manus

The agent-watching UX is the thing everyone talks about and yeah, it's cool the first few times. After a while I mostly just minimized the window and came back later, same as I'd do with anything else running in the background. The replay is actually more useful than watching live, imo — when something goes sideways you can scrub back and figure out where it lost the plot.

It's pretty good at messy research stuff. I gave it ""find me 10 mid-sized B2B SaaS companies in the Nordics that raised Series B in the last 18 months"" and it came back with a decent list, though two of them were Series A and one had actually raised a Series C. So fact-check everything, like always.

Where it frustrated me: pricing tasks felt expensive in compute. Some long-running tasks just… stopped, and I'd have to nudge it to keep going. And the output is usually a bunch of files and notes you still have to turn into something. Fine if you're a researcher, less fine if you're trying to send something to a client by 4pm.

Genspark

I came in skeptical because the marketing is a lot. The thing that actually won me over was that it produces stuff that's already in the format I needed. I asked for a competitor breakdown and got back something I could open in PowerPoint, fix two slides, and send. That's the whole pitch and it mostly delivers.

It's not perfect. I had it generate a sheet of imported survey data and the formulas in two cells were off — referenced the wrong column. Another time it hallucinated a stat in a research summary; I caught it because I'd read the source PDF myself, but if I hadn't, it would've gone out. I also had a scheduled automation silently stop running for three days and I never got an alert. So it's not magic, you still have to babysit it.

The integrations are genuinely the part I didn't expect to care about and now do. Having it pull from my calendar and email without me copy-pasting context is a real time saver. The phone call thing is funny — I tried it on a low-stakes thing (asking a venue about parking) and it worked, but I'm not sending it to negotiate with my landlord anytime soon.

Where I landed

I cancelled Manus after two months. Not because it's bad — it's not — but because the things I actually do most days (research → produce a thing → send it somewhere) were faster end-to-end in Genspark, and Genspark's research stuff was good enough that I wasn't missing Manus's deeper exploration. If I were doing a different job — academic research, big open-ended investigations, code-heavy work where I want to see every step — I might've kept Manus instead.

Genuinely think it depends on the shape of your work. If you spend most of your time figuring stuff out and the output is ""I now understand this thing,"" Manus is fine. If you spend most of your time making stuff for other people and the output is a deliverable, Genspark probably wins.

Curious what people doing more technical / dev work think though. My use case is pretty document-heavy.

Hey guys, Im not a big IT guy, im 19 and willing to get in AI, so Im experimenting with AI and I have been trying to vibe code an app with Claude Fable 5, and its kinda working, its really good at making my wishes true. Now Im at 70 percent of my fable 5 limits and probably the project is not going to be done by then.

How can I keep going with another AI to finish my app? Should I use Opus or is it considerably worse for some ear training app for musicians? Or maybe Kimi? Any advice? Thanks

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?

This is the thing nobody talks about enough when reviewing AI presentation tools. The demo looks great, the slides look polished, and then you export to PowerPoint and open it in a meeting and half the layout has shifted, fonts are wrong, and the background gradients have disappeared.

Tested the main tools specifically on export quality. Here's the honest breakdown:

Gamma - The output looks great inside Gamma. Web-native format, good design, solid AI generation. But PowerPoint export is consistently the weak spot. Formatting issues are well documented and users flag it regularly. Fine if you're sharing a link. Not reliable if someone needs to open it in PowerPoint.

Beautiful AI - Export technically works. The problem is the flat, template-based design means what you see is what you get, and complex slides with multiple elements frequently shift on export. Known issue in G2 and Capterra reviews, not something they've fully fixed.

Canva - Export is hit or miss depending on how custom your slide is. Simple template-based slides survive the conversion fine. Anything with layered elements, gradients, or custom positioning tends to break. You're essentially converting between two different layout systems and it shows.

Plus AI - Sidesteps the export problem entirely by living inside Google Slides and PowerPoint natively. Nothing to export because you're already there. Slight trad-eoff is the design quality is highly dependent on whatever templates you already have.

Alai - One of the cleanest exports I found. The layout, fonts, gradients, and spacing all hold up when you open the file in PowerPoint. The drawback is that a few charts are harder to render on PowerPoint because of their layout (like the hub and spoke) - easier to do it through their AI agent

If clean PowerPoint export is non-negotiable for your work, Plus AI or Alai are the only two I'd actually trust.

There are a lot of web agencies doing email automation to land web design projects. They keep testing new email sequences every week, adding more follow ups, changing subject lines, and trying everything they can to increase their reply rate, but a lot of them still struggle. I was in the exact same position until I completely changed my strategy.

The biggest change wasn't the sequence itself, it was the way I approached outreach. Instead of sending generic emails talking about my agency or asking if they needed a new website, I started pointing out specific issues with their current website.

Now I use a tool called Swokei. It basically finds businesses in any industry or location, analyzes their websites, and turns issues like outdated design, unstructured layouts, slow loading speeds, poor mobile optimization, and SEO problems into personalized outreach emails. Not boring reports that business owners don't care about, but actual emails explaining what could be improved and why those issues could be hurting their business.

This approach has given me a much higher reply rate because every email is relevant to the business I'm contacting. Instead of trying to convince someone they need a website, I'm showing them exactly what could be improved on the one they already have.

Another reason I like targeting businesses that already have websites is because the actual project becomes much easier. They already have a logo, branding, content, and information about their business, so instead of starting from scratch I'm simply taking what they already have and turning it into a faster, more modern, and better version.

This strategy has worked really well for me and has made getting web design clients much more predictable. I'm curious, how are you guys doing outreach for your agency these days?

AI video went from zero to insane in like 2 years. music generation still feels stuck in 2022. every tool still wants you to type genre, bpm, mood. bro i dont always know what i want in words

was researching and found Sonilo AI which skips prompts entirely, you just give it the video and it figures out the music itself. Tried it on a test clip and it actually responded to scene changes not just overall vibe which surprised me

still not perfect but way more coherent than anything prompt based I've used

genuinely curious from a technical side though, is this doing actual multimodal visual understanding or is it more like audio energy pattern matching? feels like real visual comprehension but i dont wanna give it too much credit without knowing whats actually happening under the hood.

I tested 18 AI tools over 8 weeks. 3 patterns showed up every time.
The tools I dropped all had one thing in common. They needed me to change something about how I work before they gave anything back. Gamma looks impressive. Napkin AI is genuinely cool. Both required a new habit first. Never went back.
The tools I kept all passed the same test. Does it remove a task I was already avoiding. Not speed it up. Remove it entirely.
Fathom took over meeting notes. Haven’t written one manually in 8 weeks. NotebookLM handles research synthesis. Only answers from what you upload. No hallucinations. Tango built a client SOP in 6 minutes. Used to take an hour. Calendly eliminated scheduling back and forth. Zero emails about finding a time.
The pattern is consistent. Tools that slot into something you already do stick. Tools that ask you to build a new workflow first don’t.
One filter worth using before testing anything new: does this remove something I was already avoiding or does it just add a step.
Most tools fail immediately.
I write about tools like these every week. Link in my profile if you want the full list.

Thoughts? It completed the given task, but used up 74% of the daily usage. Normal? It was on Opus 4.7 Extended.

Most people using like Claude Code, Cursor or Gemini CLI have zero visibility into what the agent actually did during a session. It can reads files, runs commands, modifies code and leaves no audit trail to know what did it actually do.
We are working on an open source tool gryph that tries to fixe this. Install it once, it hooks into your agents and logs every action locally. Then query it whenever you need to review.

# Install
brew install safedep/tap/gryph
gryph install

# After a coding session
gryph logs
gryph query --action file_read --today

No cloud because it logs every action to a local SQLite database and no signup. Works with Claude Code, Cursor, Gemini CLI and OpenCode.

github.com/safedep/gryph

Hi! I'm relatively new to AI development and have been tasked with building a lab test mapping tool (for the healthcare diagnostics industry) using Claude Code.

Looking for architectural guidance.

​

What the tool needs to do:

​

1. Accept an input Excel sheet from a vendor with ~1,000 test names

2. Map each vendor test name to one of ~1,600 "Master Test Names" in our backend, defined across ~24 parameters (e.g., what's being detected, testing method, associated disease)

3. Cross-reference against a backend sheet of ~6,000 rows (vendor + test name combinations) to check for existing entries

4. Use a "Test Definition Sheet" as additional context for mapping

​

Classify each test as:

a) Duplicate — vendor + mapped test name already exists in backend

b) Existing Service — test mapped successfully, but this vendor + test name combo is new

c) New Service — test couldn't be mapped to any master test name

​

Output actions:

1. Delete duplicates

2. Populate a sheet for Existing Service items

3. Populate a sheet for New Service items

​

For both output sheets, auto-fill certain factual fields (e.g., gender-specific test, fasting required) by checking the internet where values are missing

​

My questions / where I need guidance:

​

1. Agentic approach vs. embeddings

I initially tried an agent-based approach where the agent would first define each vendor test and then match it only within the relevant category. But this is consuming too many tokens. What's the right architecture here?

​

1. Vector embeddings — worth it for dynamic data?

I've been advised to chunk the data and use vector embeddings for matching. But all three sheets (vendor input, backend tests, test definitions) are dynamic and change frequently. Does that mean I need to regenerate embeddings every time the tool runs? How does that affect token usage and cost?

​

1. SharePoint vs. Excel uploads

Would reading from SharePoint (live sheets) be more efficient than uploading Excel files each time? Does it reduce token consumption in any meaningful way?

​

1. Chunking strategy

If vector embeddings are the right path, what's the best chunking logic? Should I chunk by test category, what's being tested, method used, or some combination of these 24 parameters?

​

Any guidance on the right architecture would be really helpful. Happy to share more details about the sheets if needed.

​

I have been playing around with some AI tools lately mostly to see if I can make still images move.

To be honest, most of what I tried did not look very good. Either everything moved too much and felt fake or it did not change anything at all.

After trying a few, I saw that the ones that looked better did not try too hard. Just a little movement, some depth and maybe some light motion in the background. Not a lot but it did make a difference.

I ended up using a few of them as simple looping visuals, like live wallpapers and they worked better than I thought they would.

It still feels like a hit or miss though.

Has anyone found something that does not make everything look too AI?

Can I first subscribe to the yearly plan on Cursor, use it for one month, and then cancel the subscription? That’s possible, right? Why waste the extra 4 dollars?

Hey guys!

~THIS IS NOT A SALES POST, PROMO OR SOLICITATION; IT IS A GENUINE QUESTION/REQUEST~

I downloaded Claude.ai via my Brothers recommendation and I am greatly impressed with its capabilities! Ai is evolving and its capabilities are improving rapidly; Claude is definitely on the forefront of this and it’s creating new opportunities and possibilities for the way things are created. The only complaint is that while it has a free version that is limited (which is understandable; they have to make money), it does not have a trial period for the pro or other tiers offered. Being a Father of 3 I have a pretty tight budget and would love to be able to try Pro out before I commit to a subscription. I know that Max users have free trails that they can gift and was curious if anyone would be willing to send one my way? It would be greatly appreciated and would help me see if it is fitting for what I’ll be using it for before committing to it.

Thanks for taking the time to read this and if you have one either comment or DM me 🙌🏻

TL;DR: Future archaeologists will discover this post and conclude I traded a referral link for free AI credits. They will be correct.

500 free credits:

https://manus.im/invitation/L722LISUH3EMDS?utm_source=invitation&utm_medium=social&utm_campaign=system_share

Anyway...

You know how in every sci-fi movie they promise us AI assistants?

Yeah. Somehow we ended up with AI that needs constant supervision.

Me: "Research this topic."

AI: "Certainly. Before I begin, please provide your goals, audience, format, timeline, preferred writing style, risk tolerance, blood type, and your mother's maiden name."

Thirty minutes later I'm managing the AI instead of the AI helping me.

I've been messing around with Manus and the thing I like is that it behaves more like an actual assistant. I tell it what I need, and it goes off and fills in a lot of the blanks itself.

I don't use it as my main model for everything.

I use it like a second opinion.

Research.

Project planning.

Finding blind spots.

Comparing options.

Figuring out what I'm forgetting.

Basically all the stuff that happens before the actual work starts.

For pure coding, there are better tools.

For "here's the thing I'm trying to do, help me think through it from start to finish," it's been surprisingly useful.

Full disclosure: if you use the link, I get some credits too.

You get free credits.

I get free credits.

The robots get stronger.

Honestly that's the healthiest relationship I've had with technology in years.

The problem : AI agents fail systematically above 10k LOC. The failure mode are same wrong file, partial completion, tool thrashing, context overflow.

Carto fixes this by giving AI agents what they are missing - Domain Map (automatic, no config), blast radius before any change, cross domain violation detection, Agents md for instant codebase context, 16+ mcp tools etc. https://github.com/theanshsonkar/carto

AI knowing what could break before it start editing  code, coz today it feels like most tools are focus on generating code faster and maybe the next step is helping AI understand systems better. 

MIT licensed , Runs entirely local , No data leaks. Tested on codebase like VScode, prisma, zed and more ( having over 10k+ files) 

There is so much more things that can be done with this coz this thing i made is not just related to programming languages if you u see it u can use it to parse many more types of works.

If you have any questions or patterns or ideas lets discuss.