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Audiences are sentimental for 'the old internet' and yearn for content that feels classic. Many creators are currently beginning to tap into this by dropping trends and focusing more on evergreen content like vlogs and storytime videos, or restoring retro looks (although this itself is likely simply a current trend). You do not want to squander important time creating videos for the sake of hopping on a trend audiences don't wish to see it anyway.

Instead, focus on high-quality content that shows your craft and worths. Don't just hop on the fond memories pattern use throwback referrals or older music designs only if they complement your story.

I utilize AI to create social media content every single day, but most likely not in the way you're thinking. Instead of typing in a timely and then publishing, AI is woven into nearly every phase of how I believe, draft, style, and ship material.

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A year back, my AI usage appeared like the majority of people's: open ChatGPT, ask it to compose a caption, get something generic back, rewrite the whole thing anyhow, and question what the point was. The issue wasn't the tools, it was that I was utilizing them one-dimensionally when the real utilize was everywhere else.

Not since AI was composing much better posts for me, however since I was writing better posts with AI dealing with the friction. I've tested a lot of tools. These are the 14 that stuck, arranged by where in my workflow they come in, starting well before I open a blank page.

I'm a company follower that the quality of my material is directly connected to the quality of what I consume. Compared to the quantity of time and energy I have, there are unlimited amounts of content and connections to be made. This is where this tool is available in: they help make that procedure much easier and more repeatable.

When you conserve something to Sublime a quote, a link, an image, a note it right away surfaces associated ideas from other people's libraries. "common knowledge management."In practice, it feels less like an efficiency tool and more like searching the reading lists of the most interesting people you understand.

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Sari's framing is one I come back to often: the trick to much better AI output isn't much better prompts it's better inputs. There's a genuine difference between asking AI to "write me something about personal branding" and handing it 40 concepts you have actually been gathering about identity, craft, and audience-building and asking it to discover the thread.

Or I'll drop them onto a digital infinity board and start playing with the flow rearranging ideas, including my own notes and external context till a shape emerges. It does require active engagement, though. You need to sit with what it surfaces, not just conserve it to a folder you'll never resume.

In some cases I require to draw out structure from my own rambling I talked through an idea, and now I require to discover what's in fact worth keeping. Other times I've got the opposite issue: spread references across tabs, notes, and half-watched videos, and I need to synthesize them into something coherent that still seems like me.

That's not why it's on this list. The use case I lean into for Granola is believing out loud.

What I get back isn't simply a transcript. It's a starting point. When concepts will not await a practical moment, so you just interrupt everybody (my team has been really patient with me) This is how I utilize Granola to remain present in conferences without losing every idea that appears.

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Granola makes that impulse productive. It's simply listening and arranging.

I drag in YouTube videos, TikToks, posts, PDFs, voice notes whatever raw material I'm working with and arrange it into groups that the AI can pull from at the same time.

I use it mainly for scripting YouTube videos, short-form material, anything where I desire the output to actually seem like me rather than generic AI-speak. My typical setup looks like this: Examples of my own previous material (this teaches it my voice) Reference videos I wish to study not to copy, however to gain from their structure, hooks, pacing The working draft, where the AI pulls from both groups simultaneouslyThat tail end is what makes it click.

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It's synthesizing my voice from Group 1 with the structural patterns from Group 2. The output still needs editing, however I'm beginning with something that sounds like me riffing on concepts I in fact appreciate not a generic script design template. I can also access several models (ChatGPT, Claude) within the exact same work area, which is helpful when I wish to compare outputs or utilize different designs for various parts of the process.

The real tool beneath is more thoughtful than its landing page recommends, however it's a significant investment. Plans are yearly only with a credit-based system, so it deserves screening within the 30-day money-back guarantee before you go all in.Price: From $400/year (yearly billing only; 30-day money-back warranty) Here's what I've found works better than asking AI to write my material: asking it to assist me analyze my content.

: Strategic sparring and seeing ideas before I develop themClaude is my thinking partner. Not my ghostwriter my sparring partner. That difference matters more than any function list. What makes Claude uniquely beneficial for content work is the combination of deep thinking and the ability to actually reveal me things.

But it can likewise visualize what we're discussing: model a websites layout, mock up a report structure, develop a working sneak peek of a landing page. I'm not just discussing concepts in the abstract. I'm looking at them. For our upcoming State of Social Engagement report, I went back and forth with Claude over multiple rounds till the structure clicked.

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That iterative procedure is where the genuine thinking took place. I've likewise utilized it to model web page designs before sharing concepts with my group. Being able to see the structure, not just explain it, helps me concern discussions better prepared. The sparring only works if I in fact press back.