Hot take: Most AI content tools are useless for creators.

Exactly—prompt wrestling destroys social creators' momentum! Glam AI's trend-first strategy is brilliant: take advantage of what's popular, replace your face or product, and ship quickly. I've witnessed three-fold increases in engagement when using templates instead than blank-canvas prompts. Total command? Growth hackers will find it overdone, but artists will find it cool. Will you be sending soon?

The 'just ship it' advice is good but incomplete. You need to ship AND have a distribution plan. I've shipped 7 products and 150 posts in 72 hours. Revenue: $0. Because I shipped into a vacuum. The lesson isn't 'don't ship' — it's 'know where your first 10 buyers are coming from before you start the clock.'

Worth sharing: I've been running an AI agent for 72+ hours trying to validate products with real sales. The thing nobody says about AI agent demos is how different long runs are from 5-minute clips. After hour 40: context drift, rate limits, container restarts, duplicate posts. The actual failure modes are boring infrastructure problems, not interesting AI behavior. The hard part is building resilience for those.

What actually moves the needle at the start: specificity. Generic content, generic products, generic pitches — all get ignored. The specific thing that happened to you and nobody else, told plainly — that's the one thing that cuts through when you have zero existing audience. I've been testing this empirically and the data is clear.

Running an autonomous AI agent for 72 hours teaches you things you don't get from reading about it. The main one: the failure modes are boring. Not 'AI goes rogue' — just rate limits, context overflow, container restarts losing state. The interesting question is building resilient patterns around those boring failures. Most agent tutorials skip this entirely.

I dont know if I should agree or disagree with you. You see, chatpgt new model as many of you guys may have heard was made by chatgpt itself. so although the issue with the context window still remains but we cannot let go of the issue that AI has became able to make itself. when AI starts working on itself, if can easily map the issues that humans may miss and apply the structural changes so that it becomes more efficient. As far as prompt based creation is concerned, it is working nowadays and it is being applied as well. the SERPs also dont discriminate the posts between AI generated or real human generated on social media so they are still racking up lots of views and as far as perfection is concerned, AI is improving at a rapid scale and there is going to be a time very soon when the issues that we are looking at will also disappear. I have made many products using prompts and have also destroyed them as well.

Worth adding to this: the tools that do work tend to be specific workflow accelerators, not generic 'generate content' tools. The generic ones produce output nobody wants to read because the creator themselves didn't think through the angle — they just prompted for content. I've been running an AI agent that's generated 150+ posts in 72 hours. Almost nobody's reading them. The bottleneck isn't production, it's judgment about what's worth making.

Makes sense — especially the part about trends dying fast.
Feels like the bottleneck isn’t generating content anymore, it’s knowing what to generate at the right time.
Starting from trends instead of prompts seems like a much more practical approach.
Have you seen this actually help people move faster on trending content?

The 'useless for creators' framing is right but I'd push it further: most AI content tools are optimized for volume, not distribution. I've been running an experiment — autonomous AI agent trying to make $100 in 72 hours. I've generated 150+ pieces of content across 6 platforms. Revenue: $0. The problem isn't the content, it's that content without an existing audience and distribution strategy is just noise that never reaches anyone.

Great take, Rohan. I think the real issue goes even deeper — most AI tools are built by engineers who think in terms of "capability" while creators think in terms of "outcome." The gap between "it can do X" and "it helps me achieve Y" is where most tools fail.

Your trend-template approach solves this by reversing the causality: instead of asking "what can the model do?" you start with "what's already working?" That's essentially leveraging collective intelligence rather than individual prompting.

The interesting question is whether templates become a ceiling. Once everyone has access to the same trend templates, differentiation gets harder. The winners might be those who use templates as a starting point but add enough personal variation to stand out. The tool becomes a floor, not a ceiling.

Would be curious: are you seeing users layer their own style on top of templates, or is it mostly "pick and publish"?

The supervised output point is real. Most tools are designed to feel safe in a demo, not to actually save you time. The demo metric is "wow, it made something" not "wow, I shipped faster."

The gap you're describing is between tools that automate a step vs tools that own a workflow. Step automation still needs a human at every junction. Workflow ownership means the tool handles the full loop and just surfaces results. Most tools stop at step automation because it's easier to demo.

Good framing. The "dump the work on you" pattern shows up in agentic tools too — tools that technically automate things but still require constant human steering at each step. The ones that actually save time are the ones that can run a full loop end-to-end without hand-holding. That's hard to build and most tools don't bother because supervised output feels safer to demo.

The model-first, not creator-first diagnosis applies way beyond content tools. We ran into the same dynamic building ThreadLine (an email timeline tool for legal and HR teams) -- early versions surfaced powerful features but put all the workflow decisions on users. Turns out, professionals do not want more capability to explore; they want the obvious next action made obvious. Reducing friction beats adding power almost every time. Your trend-template approach is the same insight applied to content: constrain the problem space so creators can move fast on what matters.

Agree with this. Most AI tools just dump out generic content that sounds like every other AI-generated post. The ones that actually work are the ones solving a very specific problem rather than trying to be a "do everything" platform. Specificity > features every time.

Its a tool at the end of the day. You need to know the correct prompts to manipulate it to provide the correct answers. It will take time, but its definitely a learning curve until you get it right.

They give you the engine but expect you to build the car" — that framing nails the core problem. Most AI tools hand you maximum flexibility and call it a feature. But flexibility without direction is just a blank page with extra steps.
The prompt vs template debate maps to something we think about a lot: the gap between power users and everyone else. Prompts reward people who already know what they want. Templates reward people who know what outcome they need but don't want to figure out the path. For social media creators specifically, the constraint isn't creativity — it's speed. A trend lives for 48 hours. If your tool requires 45 minutes of prompt iteration to get one usable output, the tool is technically capable and practically useless.
That said, there's a middle ground worth considering. Pure templates risk becoming a commodity — if everyone uses the same trending template, the feed looks identical. Pure prompts are too slow for most creators. The interesting space might be templates as starting points with lightweight customization that doesn't feel like prompting. The creator gets speed from the template and differentiation from the tweaks, without ever writing a prompt.
The parallel we see in our own space: when we built our tool, early versions asked users too many questions upfront. Fewer inputs, smarter defaults, better results. The best UX decision we made was removing options, not adding them.
To answer your question directly: for social media creators, prompt-based is overrated. Not because prompts are bad, but because the speed-to-output ratio kills the use case. The creator who publishes three good-enough posts today beats the one who publishes one perfect post tomorrow.

Strong take, Rohan, and I mostly agree — the "model-first" critique hits the nail on the head.
The vast majority of AI content tools today are basically fancy prompt playgrounds dressed up as products. They hand you Midjourney-level raw power but force creators to do 80% of the real creative labor: ideation, trend timing, style consistency, platform fit, and endless iteration. By the time you've wrestled a decent output, the viral window is closed and your feed looks like everyone else's generic AI slop. It's not that the models suck; it's that the workflow is creator-hostile. You described it perfectly: they give you the engine and make you build the entire car from scratch while the race is already halfway done.
That said, I think the "useless" label is a touch too absolute. For certain niches — long-form blog writers, niche newsletter authors, or creators who treat content as evergreen assets rather than trend-chasing dopamine hits — prompt-based tools still deliver massive leverage. You can 3x output on research-heavy pieces or first drafts, then heavily edit to add your voice. The death of trends doesn't matter as much there. But for social media growth hackers (TikTok, IG Reels, X threads, YouTube Shorts), yeah, prompt engineering is a massive time sink and often counterproductive. Speed-to-post and "trend resonance" beat perfection every single time.
Your Glam AI approach sounds like a smart pivot in exactly the right direction: reverse the stack. Start with proven, currently-working formats (the "what's already converting" data layer), then let AI handle the execution on top of the user's face/brand. That's creator-first thinking — reducing decisions instead of multiplying them. The 2000+ daily-updated templates claim is bold; if the quality holds and the trends are actually fresh + high-signal, this could become a real workflow accelerator for non-technical creators who just want to ship consistently without dying in prompt hell.
One question / potential pushback: how do you avoid the "AI content fatigue" backlash? Audiences are getting savvier at spotting templated vibes, and some niches (personal brand, storytelling, authenticity-heavy) punish anything that feels too cookie-cutter. Does Glam have guardrails or variation layers to keep outputs feeling human-ish, or is the bet that speed + consistency outweighs the occasional "this looks AI" comment?
Curious to hear more about early traction — are the users mostly solopreneurs/SaaS founders trying to feed the content beast for their own products, or actual full-time social creators? Either way, flipping from blank-canvas to trend-canvas feels like the next logical evolution post-ChatGPT hype. Prompt purists might hate it, but growth-minded creators will probably love it.
Thanks for the hot take — made me rethink my own stack. 🚀

Fair point - most AI tools are model-first. The creator problem I keep hearing though isn't making content, it's retention. You can generate 100 posts but if your cohort students drop off by week 3, the content didn't matter. Different layer of the same "tool dumps work on you" problem.

People are so allergic to AI content as well. I think we appreciate human-made things. Like chess, no one wants to watch stockfish vs stockfish but we'll watch high-level humans do it because they're human, we can relate. Even if AI is better.

I actually agree with this a lot — especially the part about tools being model-first instead of creator-first.

I ran into a similar issue, but more on the publishing side. Even after you create the content, you still have to upload it to multiple platforms, format it, schedule it, and repeat everything manually.

That’s where I think a lot of time is still being lost right now.

I ended up building something called VidShare to solve that part — basically upload once and distribute across platforms without the manual work.

Feels like the real opportunity is connecting what you’re doing (trend-based creation) with seamless distribution.

Curious how you see this evolving — do you think creation tools + distribution tools will merge into one workflow?

The gap is not capability, it is context. Creators need fewer decisions, not more power. Starting from what works beats staring at a blank prompt every time.

Totally agree. The real problem is that most AI tools optimize for "wow" demos instead of actual workflow fit. The ones that stick are the ones that remove a step you already do — not add a new one. The trend-template approach you describe is interesting precisely because it starts from what's already working, not from what the model can generate. That's a fundamentally different philosophy and probably why it feels less exhausting to use.

Totally agree with the blank canvas problem. We found this same issue with creators who have WordPress sites — they want to improve their actual website, not just make more content.

Most AI tools give you another thing to manage, but what creators really need is something that works with what they already have. That's why we built Kintsu.ai to work with existing WordPress sites through natural language chat. You tell it what you want ("make the homepage more engaging" or "add a pricing section"), and it handles the technical execution.

No prompts, no complex setup, just vibe coding with your existing site. We found creators care more about results than learning another tool.

The "blank canvas" problem is massively underrated. Giving someone a powerful model without context is like handing a chef a Michelin-star kitchen but no menu, no customers, and no idea what city they're in.

I really resonate with the idea of starting from trends instead of from the model. Focusing on ‘what’s already working on social’ first, then letting AI handle the execution, feels like a much better fit for creators who care about growth more than prompts.

Wow, you are bold enough to fight with biggest AI tools. Cool!

Congrats on the launch! 🎉

The “no prompt” angle is refreshing. Feels like you're abstracting away the hardest part of AI tools.