The Accidental Coders, the Algorithm, and the Next Black Renaissance

Anyone who knows me knows my vibe is TikTok and YouTube.

I have a best friend who is a Tumblr girl. Another who is a Threads girly. Family members who live on WhatsApp. Cousins who still swear by Facebook Marketplace. A whole generation of younger relatives who think email is ancient history.

We are all online, but we are not online the same way.

Understanding where you fit online matters more than most people realize.

A Computer Was Always Nearby

Throughout my life, I have been fortunate enough to always have some access to the internet. I had a father who was a librarian, and being a millennial meant that no matter where we lived in the world, there was usually a computer nearby. From my earliest memories, there was always one in the house.

Back when floppy disks were a thing. When Solitaire and Minesweeper were peak entertainment. When the internet screamed at you before it connected. The iconic dial-up tone meant you had about 45 seconds to grab a snack before the homepage loaded.

We did not have smartphones. We had shared family desktops in living rooms and libraries. Screen time was negotiated, not infinite. And yet, even with those limitations, something was forming. A relationship with technology that was hands-on. Experimental. Sometimes frustrating. Always formative.

As millennials, we may not have been the inventors of the web, but we were the frontier generation of social media. And early social media was not passive.

It required effort.

When Social Media Required Skill

Platforms like Myspace, BlackPlanet, AsianAvenue, and MiGente did not just ask you to show up. They asked you to build.

If you wanted your page to look right, sound right, feel like you, you had to learn HTML and CSS. You had to figure out how to embed music, change layouts, host images on third-party sites, and troubleshoot broken code when your background image disappeared or your custom cursor stopped working.

There were no templates. No drag-and-drop editors. No creator funds. No algorithm pushing your content to strangers. You built your corner of the internet with your own hands, and people found you because they were looking.

People were coding without realizing they were coding.

We learned to read documentation not because we wanted to become developers, but because we wanted our pages to autoplay a specific song when someone visited. We wanted the right font. The right vibe. And the only way to get it was to figure it out ourselves.

Black online communities took this even further. Platforms like BlackPlanet were more than social networks. They were digital gathering spaces where culture was exchanged, relationships were formed, and identity was expressed through customization. You could tell who someone was by how their page looked. It was art. It was personal branding before that term existed.

And then there was the broader internet culture. Before we outsourced thinking to apps, we Googled things. We read forums. We followed random blogs written by strangers who became authorities simply because they showed up consistently and explained things clearly.

We fixed our own laptops. We put phones in rice. We opened devices we had no business opening because who was paying for repairs when there was a step-by-step guide online written by someone named “TechGuy47” on a forum from 2007?

Then YouTube arrived.

Suddenly everything became, “Let me see if there’s a YouTube video for that.”

Wikipedia replaced encyclopedias, even though teachers insisted it was not a “real” source. Time proved otherwise. The collective knowledge of the internet, constantly edited and updated by millions, turned out to be more accurate and current than the dusty Britannica sets gathering dust in school libraries.

The early internet rewarded curiosity. Trial and error. Self-teaching. Skill accumulation. It was messy, but it was ours.

Then convenience won.

Platforms Changed. Users Changed.

As social media evolved, platforms optimized for ease, speed, and dopamine. The barrier to entry dropped to zero. No coding required. No learning curve. Just download the app, create an account, and start scrolling.

Learning became optional. Consumption became default.

Accessibility matters. Not everyone needs to understand how the engine works to drive the car. But something was lost in the transition: a certain agency, a certain literacy, a certain relationship with the tools we use.

Here is what I noticed, though: we did not all move the same way.

Over time, I started to notice patterns. Digital archetypes. Different types of users drawn to different platforms, not just because of age or demographics, but because of how they think, process information, and interact with the world.

Most people fall into one to three of these categories. And understanding where you fit can change how you approach the internet, content creation, and even income.

The Digital User Archetypes

The Visual Curators

Platforms like Pinterest and Instagram attract users who think in aesthetics. Mood boards. Color palettes. Branding. Vibes. They see the world in compositions and collections. These are often natural product sellers, affiliate marketers, and brand builders. Their superpower is taste, and taste can be monetized when packaged correctly.

The Conversationalists

Long-form thinkers who thrive on YouTube and podcasts. These are teachers, storytellers, analysts, and explainers. They don’t rush. They build trust and community over time, often across hours of content that compounds. Monetization works through education, memberships, courses, and authority. If you’ve ever thought, “I could talk about this for hours,” this might be you.

The Dopamine Sprinters

Short-form natives drawn to TikTok, Reels, and Shorts. Fast thinkers. Trend riders. Discovery machines. They can capture attention in three seconds and hold it for sixty. Their power is reach, not ownership. Monetization works best when they funnel attention elsewhere: to products, services, longer content, or owned platforms. The algorithm giveth, and the algorithm taketh away.

The Town Square Regulars

Found on Facebook and WhatsApp. These users value connection, logistics, and familiarity over novelty. They are hugely underrated for service businesses, local organizing, and community building. While tech circles dismiss Facebook as “for old people,” entire economies run on Facebook Groups and WhatsApp chains. Never underestimate where the people actually are.

The Professionals

Living in LinkedIn. Reputation builders. Consultants. Operators. Executives. Recruiters. Where expertise turns into contracts, where thought leadership translates to opportunities, where your professional identity is curated and broadcast. It is performative, yes, but performance has value when it opens doors.

The Live Hustlers

Streaming on platforms like TikTok Live, Twitch, Kick, and Bigo Live. Digital street performers. Algorithmic buskers. Real-time monetization through attention, interaction, gifts, and tips. Entertainment becomes labor, presence becomes product. It is exhausting and lucrative in equal measure for those who master it.

The Deep Thinkers

The Redditors. The writers. The long-attention-span users on Reddit, Medium, and Substack. They trade speed for depth. They write essays when others write captions. They build audiences that read, not just scroll. Monetization comes through insight, influence, and the kind of trust that only sustained thinking can build.

The Dark Corners

Spaces like 4chan and other anonymous forums exist on the edges, shaping culture without accountability. Memes are born here. Movements are organized here. Language mutates here before it reaches the mainstream. They matter and influence more than most people realize, but they are not the focus of this piece.

The New Frontier

Decentralized platforms like Mastodon and Bluesky feel like the early internet again. Small communities. Fewer algorithms. More intention. Still niche, still finding their footing. But historically, niches are where renaissances start. The mainstream is where they end up.

The Harlem Renaissance and Economic Constraint

I have heard many Black TikTok users point out something that often gets glossed over in history classes.

The Harlem Renaissance happened alongside the Great Depression.

The timing was not coincidental. Economic constraint was the catalyst.

The Harlem Renaissance, roughly spanning from the late 1910s into the 1930s, emerged during a time of severe racial discrimination, economic hardship, and limited access to traditional labor markets for Black Americans. The Great Migration had brought millions of Black families from the rural South to Northern cities, seeking opportunity and fleeing violence. What they found was segregation by another name: redlining, job discrimination, and social exclusion.

Black women were particularly affected, often being the first pushed out of domestic and clerical jobs during economic downturns. When the economy contracted, Black women were told to go home so white women could have their jobs. Not a metaphor. Policy.

And yet.

Art exploded. Literature flourished. Music transformed the world. Political thought sharpened. New institutions were built. Black newspapers, Black theaters, Black publishing houses, Black intellectual circles. All of it emerged not despite the constraints, but in response to them.

Writers like Langston Hughes, Zora Neale Hurston, and Claude McKay were not creating in comfortable conditions. They were creating because creation was both survival and resistance. Musicians like Duke Ellington and Bessie Smith were not waiting for permission. They were building culture that would outlast the systems trying to exclude them.

Black culture became both survival and currency.

Constraint did not kill creativity. It redirected it.

Black Women, AI, and Displacement

Fast forward to now.

Black women are again disproportionately impacted by economic shifts. According to the Bureau of Labor Statistics, Black women’s unemployment rate climbed from 5.4% at the start of 2025 to 7.3% by year’s end, the highest in four years. By December 2025, Black women averaged nearly 30 weeks unemployed, the longest duration among all demographic groups. Approximately 335,000 federal workers lost positions in 2025, and Black women, who comprise 12% of the federal workforce compared to 7% of the overall workforce, bore a disproportionate share of those cuts.

The displacement is not limited to any single sector. Professional and business services, manufacturing, public administration, and financial services all saw significant declines in Black women’s employment throughout 2025. The jobs that were supposed to be “safe” are not safe anymore. The ladder that previous generations climbed is being pulled up, rung by rung, by algorithms and policy decisions that favor efficiency over equity.

The data confirms it. The shift is already underway.

But here is the flip side.

AI is also removing gatekeepers.

Credentials matter less. Speed matters more. Learning curves are compressed. A single person with the right knowledge can now do the work of a small team. The same technology that threatens certain jobs also democratizes capability for those who learn to use it.

AI is not magic. It is leverage.

Those who learn how to prompt effectively, automate repetitive tasks, package knowledge into products, and build small digital assets will not just survive the transition. They will shape what comes next.

This moment mirrors the conditions that historically produced Black renaissances:

• Economic pressure pushing people out of traditional paths
• Exclusion from systems that were never designed to include them
• New tools that lower barriers to creation and distribution
• New networks that allow community to form outside institutional control
• New ways of creating value that don’t require permission

The internet gave us the first wave. AI is giving us the second.

A Renaissance Does Not Start in Comfort

A renaissance does not begin when conditions are ideal.

It begins when people are forced to adapt and choose creation over disappearance.

Millennials were the accidental coders, learning to build without knowing we were building. Black communities were early digital architects, creating culture and connection on platforms that have since been forgotten by mainstream tech history. The lessons from both eras converge: tools change, but agency remains the variable that matters most.

AI is the next inflection point.

The people who will thrive are not necessarily the most credentialed, the most connected, or the most resourced. They are the ones who recognize the pattern early enough to position themselves on the right side of it.

The lesson here is not about nostalgia. It is about recognition.

The tools have changed. The pressure is familiar.

And history suggests what comes next.

What This Means for You

If you are reading this and feeling the pressure, the layoffs, the automation anxiety, the sense that the ground is shifting beneath you, know that you are not imagining it. The shift is real.

But shifts create openings.

The question is not whether AI will change the landscape. It already has. The question is whether you will be positioned as someone who uses these tools or someone who is replaced by them.

Start learning. Start building. Start now.

The next renaissance will not be announced. It will not ask permission. It will not wait for conditions to improve.

It will be built by people who decided to build anyway.

Forward → Upward ↑ Onward ↗︎
Mstimaj

Sources and Further Reading

• Gates, Henry Louis Jr. The Harlem Renaissance: A Brief History with Documents. Bedford/St. Martin’s.
• Lewis, David Levering. When Harlem Was in Vogue. Penguin Books.
• U.S. Bureau of Labor Statistics. Employment Projections and Occupational Displacement Data.
• Noble, Safiya Umoja. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press.
• Pew Research Center. Social Media Usage and Demographic Trends.
• Benjamin, Ruha. Race After Technology: Abolitionist Tools for the New Jim Code. Polity Press.
• McMillan Cottom, Tressie. Thick: And Other Essays. The New Press.
• Wikipedia. Harlem Renaissance.
• Wikipedia. BlackPlanet.
• The 19th News. Black women’s unemployment rate hit 7.3% in December. January 2026.