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Audiences are nostalgic for 'the old web' and yearn for content that feels classic. Lots of developers are currently beginning to use this by dumping trends and focusing more on evergreen content like vlogs and storytime videos, or restoring retro looks (although this itself is likely just a present trend). You don't want to squander valuable time producing videos for the sake of hopping on a trend audiences do not desire to see it anyhow.

Rather, focus on high-quality content that shows your craft and worths. Don't just hop on the nostalgia trend use throwback recommendations or older music styles just if they complement your story.

I use AI to develop social media material every single day, however probably not in the method you're thinking. Instead of typing in a timely and then publishing, AI is woven into almost every phase of how I believe, prepare, design, and ship material.

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A year ago, my AI usage looked like many people's: open ChatGPT, ask it to compose 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 real leverage was all over else.

Not because AI was writing much better posts for me, but because I was composing much better posts with AI dealing with the friction. I've evaluated a great deal of tools. These are the 14 that stuck, arranged by where in my workflow they are available in, beginning well before I open a blank page.

I'm a firm follower that the quality of my material is straight connected to the quality of what I take in. Compared to the amount of time and energy I have, there are limitless amounts of content and connections to be made. This is where this tool comes in: they assist make that procedure simpler and more repeatable.

When you save something to Sublime a quote, a link, an image, a note it instantly surfaces associated concepts from other individuals's libraries. "common knowledge management."In practice, it feels less like a productivity tool and more like searching the reading lists of the most intriguing individuals you know.

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Sari's framing is one I come back to often: the trick to better AI output isn't better prompts it's much better inputs. There's a genuine difference in between asking AI to "write me something about individual branding" and handing it 40 ideas you have actually 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 begin having fun with the circulation rearranging ideas, adding my own notes and external context up until a shape emerges. It does require active engagement. You have to sit with what it surface areas, not simply 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 a concept, and now I need to find what's in fact worth keeping. Other times I've got the opposite problem: spread references across tabs, notes, and half-watched videos, and I require to synthesize them into something coherent that still sounds like me.

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

What I get back isn't simply a records. It's a starting point. When ideas will not await a practical minute, so you just disrupt everybody (my group has been very patient with me) This is how I use Granola to stay present in meetings without losing every thought that turns up.

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Granola makes that impulse productive. I could probably do this with most chatbots' voice modes ChatGPT, Claude, even a standard voice memo plus a manual summary. Granola's edge is that it's purpose-built for capture and extraction. It's not trying to have a conversation back at me. It's just listening and organizing.

I drag in YouTube videos, TikToks, short articles, PDFs, voice notes whatever raw product I'm working with and organize it into groups that the AI can pull from simultaneously.

I use it primarily for scripting YouTube videos, short-form content, anything where I desire the output to in fact sound like me instead of generic AI-speak. My typical setup looks like this: Examples of my own previous material (this teaches it my voice) Reference videos I want 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 manufacturing my voice from Group 1 with the structural patterns from Group 2. The output still needs modifying, but I'm beginning with something that sounds like me riffing on ideas I in fact care about not a generic script template. I can also access several models (ChatGPT, Claude) within the exact same office, which is beneficial when I desire to compare outputs or utilize various designs for different parts of the process.

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

: Strategic sparring and seeing concepts before I build themClaude is my thinking partner. What makes Claude distinctively beneficial for content work is the mix of deep reasoning and the capability to actually show me things.

It can likewise envision what we're discussing: model a web page layout, mock up a report structure, develop a working preview of a landing page. I'm not just discussing ideas in the abstract. I'm looking at them. For our upcoming State of Social Engagement report, I went back and forth with Claude over numerous rounds till the structure clicked.

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I've likewise used it to model web page layouts before sharing principles with my group. Being able to see the structure, not just explain it, helps me come to discussions better prepared.