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Audiences are classic for 'the old internet' and long for material that feels classic. Many creators are currently starting to use this by ditching patterns and focusing more on evergreen content like vlogs and storytime videos, or reviving retro visual appeals (although this itself is likely just a current pattern). You do not want to squander valuable time developing videos for the sake of hopping on a trend audiences do not want to see it anyway.

Rather, focus on high-quality material that reflects your craft and values. Do not just hop on the fond memories pattern usage throwback references or older music designs only if they complement your story.

I use AI to develop social media content every single day, but most likely not in the way you're thinking. Instead of typing in a prompt and then publishing, AI is woven into almost every stage of how I believe, draft, style, and ship material.

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A year earlier, my AI usage appeared like many people's: open ChatGPT, ask it to write a caption, get something generic back, rewrite the entire thing anyhow, and question what the point was. The issue wasn't the tools, it was that I was using them one-dimensionally when the genuine take advantage of was all over else.

Not since AI was composing better posts for me, but because I was composing better posts with AI managing the friction. I have actually tested a lot of tools. These are the 14 that stuck, organized by where in my workflow they are available in, beginning well before I open a blank page.

I'm a company believer that the quality of my material is directly connected to the quality of what I consume. However compared to the amount of time and energy I have, there are unlimited amounts of material 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 immediately surface areas related ideas from other individuals's libraries. "common understanding management."In practice, it feels less like a performance tool and more like searching the reading lists of the most intriguing people you understand.

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Sari's framing is one I return to often: the trick to much better AI output isn't much better triggers it's much better inputs. There's a real difference in between asking AI to "write me something about individual branding" and handing it 40 concepts you've been gathering about identity, craft, and audience-building and asking it to find the thread.

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

Often I need to extract structure from my own rambling I talked through an idea, and now I need to find what's really worth keeping. Other times I've got the opposite issue: scattered recommendations across tabs, notes, and half-watched videos, and I need to synthesize them into something meaningful that still sounds like me.

Turning spoken ideas into structured beginning pointsGranola is technically a conference transcription tool it catches audio straight from my gadget (no uncomfortable bot joining the call) and utilizes AI to turn raw discussion into organized notes. But that's not why it's on this list. The usage case I lean into for Granola is considering loud.

What I return isn't simply a records. It's a beginning point. When ideas won't wait on a convenient moment, so you just interrupt everyone (my group has actually been really patient with me) This is how I utilize Granola to stay present in conferences without losing every thought that pops up.

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Granola makes that instinct productive. I could perhaps do this with most chatbots' voice modes ChatGPT, Claude, even a fundamental voice memo plus a manual summary. Granola's edge is that it's purpose-built for capture and extraction. It's not attempting to have a conversation back at me. It's simply listening and arranging.

Here are a number of articles from fellow spoken processors on the team to dig deeper into rambling-as-processing.: Free (standard); $14/user/month for endless Visual thinkers who require to manufacture several sources into content as rapidly as possiblePoppy's interface is a visual canvas. I drag in YouTube videos, TikToks, articles, PDFs, voice notes whatever raw product I'm working with and arrange it into groups that the AI can pull from concurrently.

I use it mostly for scripting YouTube videos, short-form material, anything where I want the output to actually seem like me instead of generic AI-speak. My typical setup appears like this: Examples of my own previous content (this teaches it my voice) Reference videos I wish to study not to copy, but to discover 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 manufacturing my voice from Group 1 with the structural patterns from Group 2. The output still requires modifying, but I'm beginning with something that sounds like me riffing on ideas I in fact appreciate not a generic script template. I can also access several designs (ChatGPT, Claude) within the exact same work space, which is beneficial when I wish to compare outputs or use various designs for various parts of the process.

The actual tool underneath is more thoughtful than its landing page suggests, however it's a significant investment. Strategies are yearly just with a credit-based system, so it's worth testing within the 30-day money-back assurance before you go all in.Price: From $400/year (annual billing only; 30-day money-back guarantee) Here's what I have actually discovered works much better than asking AI to compose my material: asking it to assist me analyze my material.

: Strategic sparring and seeing ideas before I build themClaude is my thinking partner. Not my ghostwriter my sparring partner. That distinction matters more than any function list. What makes Claude uniquely helpful for material work is the combination of deep reasoning and the capability to in fact show me things.

It can likewise picture what we're discussing: model a web page design, mock up a report structure, build a working sneak peek of a landing page. I'm not simply talking about 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 several rounds up until the structure clicked.

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I've likewise utilized it to model web page designs before sharing concepts with my group. Being able to see the structure, not simply explain it, helps me come to conversations much better prepared.