I had 535,000 followers—so why wasn’t anyone seeing my content?

In 2009, I figured out how to build an audience on Twitter. Back then, followers were everything because the social media algorithm was really just the social graph. If people followed you, they saw what you posted.

So I spent years growing a following and working within that system, and I ended up with a sizable 535,000 followers. That was the old game. But 17 years later, on June 24, 2026, my posts were only getting about 200 views.

In social media terms, those are “impressions.” In reality, compared with 2014, I was almost invisible. TikTok’s new interest graph had changed everything. The distance between the old world and the new one was enormous, and it meant that the time and money I had invested back then were now worth almost nothing.

That gap tells the story of social media history. Platforms have shifted from the social graph, where your followers determine who sees you, to the interest graph, where the algorithm decides what each person is interested in and serves them that instead. Your followers are now just one signal among many.

And you’re competing in feeds packed with content that AI can create in seconds, at virtually no cost, without limit. So in June, I started an experiment. I’m 69, and I wanted to see whether I could crack the code again: how do you get seen on the interest graph when AI content is flooding everything?

I posted every day and used AI to analyze every number X gave me. Four months later, my posts had been seen 2.7 million times since July 1, and I’d gained more than 3,000 followers. In October alone, I averaged 35,000 views a day.

When I began, it was 200. But views don’t tell you who is actually listening. So this week, I went back through every reply to my posts since July: 3,660 replies from 2,020 people.

I used AI to help sort and count them. The clearest sign is in my replies. Only about one in five of the people who replied to me were following me.

If they’re any guide, most of the people seeing my posts weren’t on my follower list at all. X had decided they’d be interested. To be fair, the algorithm isn’t hiding me from every old follower.

Many accounts from 2009 to 2015 are no longer active. But even accounting for that, a typical post now reaches less than 1% of my followers. The audience I spent years building now buys me very little reach.

So what actually gets you seen? Using X as a research platform, I looked at the 3,660 replies to my posts and pulled out the insights that have changed how I create content and use social media on X. 1.

Name the feeling On the interest graph, the algorithm watches what people stop for and then shows the post to more people like them. So the question is: what makes a stranger stop? Since early October, I’ve posted ten questions in the same format.

Four of them took off, reaching between 12,600 and 25,100 people. The other six stalled below 3,600. The difference wasn’t timing or length.

Every question that took off asked how AI makes you feel. “Does AI make you feel left behind, or let back in?” drew 283 replies. “Has AI made you more excited about your future, or more uncertain?” drew 313.

The ones that stalled asked practical questions, like whether starting again is harder now than at 30, or who still asks for your advice. They were fair questions, but they asked people to think rather than feel. People don’t stop for a topic.

They stop for a feeling they recognize in themselves. A machine can produce endless content about AI. It’s much harder to fake the moment someone reads a question and thinks, “that’s me.” Even then, only about one in three of those questions broke through.

The answer isn’t to post more. It’s to take more shots with the kind of post that can land. 2.

Write for an audience, not a topic The interest graph doesn’t just decide how many people see you. It decides which people see you. Write broadly, and it will find you a broad crowd.

From July to September, I wrote about AI in general: its risks, its contradictions, and what it does to thinking. Those posts attracted a crowd, but the wrong one. About four in ten of the real people replying were debating AI itself.

Very few were thinking about their own next chapter. In October, I narrowed the focus. I wrote for experienced people trying to work out what AI means for their work and their lives.

Since mid-October, nine in ten of the real people replying fit the four groups I’m building Zyrro for: Builders making something new: 30% Rediscoverers getting back skills and energy they thought they’d lost: 22% Defenders of experience, arguing that judgment matters more now, not less: 20% People who feel threatened or worn out by the pace of change: 18% A community is starting to form. About half of the people replying since mid-October had replied before, and 232 people have now replied across more than one period. By contrast, from July to September, only 98 of 582 came back in October.

The posts that brought in the most followers were personal, not clever. A post about why I’m not retiring brought 304 profile visits and 41 new followers in a day. The story of the year my business collapsed and my marriage ended brought 524 profile visits, more than any post since July.

Personal detail tells both the algorithm and the reader exactly who you are for. 3. Count people, not replies This was a surprise.

The flood of AI content isn’t just in the feed. It’s in the replies too. As I read through them, I kept seeing the same kind of response: polished, agreeable, and just repeating what I’d said in slightly grander language.

“The good question is the hard bit, the agent will happily answer a bad one.” One account had replied to me 72 times. Its bio said it was building a tool that writes replies for people. So I counted.

From July to September, about four in ten replies to my posts read as machine-written. Since mid-October, it’s been about one in four, from 139 different accounts. This isn’t just my account.

Imperva’s 2025 Bad Bot Report found that bots made up 51% of all web traffic in 2024. The machines aren’t just reading the internet now. They’re joining the conversation.

That makes the numbers misleading. Reply counts no longer measure connection. If you judge your content by replies, you’re partly judging how attractive it is to software.

I now count people: profile visits, new followers, and real people who come back. 4. Reply more, don’t post more When anyone can publish endless content, adding more of your own is the weakest move.

I learned that the hard way. In the week of July 20, I posted 22 times a day, and at first it worked. Views jumped from about 7,000 a day to 55,000.

So I kept that pace into August. Reach then fell week after week. In October, I posted about eight times a day.

Views were higher than in August, and profile visits per 1,000 views tripled, from 1.0 to 3.1. When I lined up the daily numbers, profile visits barely moved with how many posts I published. They moved with how many replies I wrote to people in my threads.

Posting is the shop window. Replying is the conversation that brings someone inside. And real conversation is the one thing the flood can’t copy at scale.

There’s a cost to this, and I should be honest about it. I did all of it by hand, and replying turned into a treadmill. The next stage has to fit into about an hour a day.

5. The people reading aren’t always the people replying In 2009, I figured out how to build an audience on Twitter. Back then, followers were everything because social media ran on the social graph.

If people followed you, they saw what you posted. So I spent years growing my following and learning how to work within that system. At one point, I had 535,000 followers.

That was the old game. But 17 years later, on June 24, 2026, my posts were being seen only about 200 times. In social media terms, those are “impressions.” In reality, compared with 2014, I was almost invisible.

TikTok’s interest graph had changed the rules entirely. The difference between the old model and the new one was enormous, which meant that the time and money I had invested back then had become almost worthless. That gap is the story of social media’s history.

Platforms have shifted from the social graph, where the people who follow you determine who sees you, to the interest graph, where the algorithm decides what each person is interested in and serves them that content. Your followers are now only one signal among many. And the feed you’re competing in is packed with content that AI can create in seconds, at virtually no cost, with no real limit.

So in June, I started an experiment. I’m 69, and I wanted to see whether I could crack the code a second time: how do you get seen on the interest graph in a world flooded with AI content? I posted every day and used AI to analyze every metric X gave me.

Four months later, my posts have been viewed 2.7 million times since July 1, and I’ve gained more than 3,000 followers. In October alone, I averaged 35,000 views a day. When I started, it was 200.

But views don’t tell you who is actually listening. So this week, I went back through every reply to my posts since July: 3,660 replies from 2,020 people. I used AI to help sort and count them.

The clearest sign is in those replies. Only about one in five of the people who replied to me were following me. If that’s any indication, most of the people seeing my posts weren’t on my follower list at all.

X had decided they would be interested. To be fair, the algorithm isn’t hiding me from every old follower. Many accounts from 2009 to 2015 are no longer active.

But even allowing for that, a typical post today reaches less than 1% of my followers. The audience I spent years building now gives me very little reach. So what actually gets you seen?

I used X as a research tool and studied the 3,660 replies my posts received. These are the lessons that changed how I create content and how I use X. 1.

Name the feeling On the interest graph, the algorithm watches what people stop for and then shows the post to more people like them. So the real question is: what makes a stranger stop? Since early October, I’ve posted ten questions in the same format.

Four of them took off, reaching between 12,600 and 25,100 people. The other six stalled below 3,600. The difference wasn’t timing or length.

Every question that took off asked how AI makes you feel. “Does AI make you feel left behind, or let back in?” drew 283 replies. “Has AI made you more excited about your future, or more uncertain?” drew 313.

The ones that stalled asked practical questions, like whether starting over is harder now than at 30, or who still asks for your advice. They were fair questions, but they asked people to think, not feel. People don’t stop for a topic.

They stop for a feeling they recognize in themselves. A machine can produce endless content about AI. It’s much harder to fake the moment someone reads a question and thinks, “that’s me.” Even then, only about one in three of those questions broke through.

The answer isn’t to post more. It’s to take more shots with the kind of post that can land. 2.

Write for an audience, not a topic The interest graph doesn’t just decide how many people see you. It decides which people. If you write broadly, it will find you a broad crowd.

From July to September, I wrote about AI in general: its risks, its contradictions, what it does to thinking. Those posts drew an audience, but not the right one. About four in ten of the real people replying were debating AI itself.

Very few were thinking about their own next chapter. In October, I narrowed the focus. I wrote for experienced people trying to understand what AI means for their own work and lives.

Since mid-October, nine in ten of the real people replying fit the four groups I’m building Zyrro for: Builders making something new: 30% Rediscoverers getting back skills and energy they thought they’d lost: 22% Defenders of experience, arguing that judgment matters more now, not less: 20% People who feel threatened or worn down by the pace of change: 18% A community is beginning to form. About half of the people replying since mid-October had replied before, and 232 people have now replied across more than one period. Compare that with the July-to-September crowd: only 98 of 582 came back in October.

The posts that brought in the most followers were personal, not clever. A post about why I’m not retiring brought 304 profile visits and 41 new followers in a day. The story of the year my business collapsed and my marriage ended brought 524 profile visits, more than any post since July.

Personal detail tells the algorithm, and the reader, exactly who you are for. 3. Count people, not replies This was a surprise.

The flood of AI content isn’t just in the feed. It’s in the replies too. As I read through them, I kept seeing the same kind of response: polished, agreeable, and repeating what I’d just said in slightly grander language.

“The good question is the hard bit, the agent will happily answer a bad one.” One account had replied to me 72 times. Its bio said it was building a tool that writes replies for people. So I counted.

From July to September, about four in ten replies to my posts read as machine-written. Since mid-October, it’s about one in four, from 139 different accounts. This isn’t just happening on my account.

Imperva’s 2025 Bad Bot Report found that bots made up 51% of all web traffic in 2024. Machines aren’t just reading the internet now. They’re joining the conversation.

That’s easy to miss. Reply counts no longer measure connection. If you judge your content by replies, you’re partly judging how attractive it is to software.

I now count people: profile visits, new followers, and real people who come back. 4. Reply more, don’t post more When anyone can publish endless content, the weakest move is to add even more of your own.

I learned that the hard way. In the week of July 20, I posted 22 times a day, and at first it worked. Views jumped from about 7,000 a day to 55,000.

So I kept going at nearly that pace into August. Reach then fell week after week. In October, I posted about eight times a day.

Views were higher than in August, and profile visits per 1,000 views tripled, from 1.0 to 3.1. When I lined up the daily numbers, profile visits barely moved with the number of posts I published. They moved with how many replies I wrote to people in my threads.

Posting is the shop window. Replying is the conversation that brings someone inside. And a real conversation is the one thing the flood can’t copy at scale.

There’s a cost to this, and I should be honest about it. I did all of it by hand, and replying became a treadmill. The next stage has to fit into about an hour a day.

5. The people reading aren’t always the people replying