Roman Travnikov TravnikovDev

The internet never forgets? Cute myth. In 2025 the web has a goldfish memory. Your personal brand nukes anonymity, but try finding a 2014 video and you’ll feel like you’re digging in wet sand. 🧠

My AI research agent pulled the receipts, and the drift is a decade old. In 2010 Google shipped Caffeine, then a 2011 update that rewarded fresh results. Users clicked the new stuff more, so the machine learned a bad habit - serve what’s recent, bury what’s quiet.

Why it feels like everything old fell into a hole:

• The index isn’t a library card catalog. Crawling costs money. Low demand and rarely updated pages get crawled less or dropped.
• Links rot. Pew found big chunks of older references die. When links die, the signals that kept your page afloat die with them.
• Platforms locked doors. In 2021 YouTube made pre-2017 unlisted videos private unless creators opted out. Poof - years of embeds vanish from search.
• Product choices cut ladders. In 2024 Google killed the cache view. Now your fastest path to a snapsho

If resting makes you feel guilty, that’s not ambition. That’s a warning light.

I keep hearing this phrase, and yeah, it screams LinkedIn to me: the always-on itch to post another win, ship another thing, add another certificate so you don’t “fall behind.”

My AI research agent pulled the raw stuff, and the pattern is dull but real: this isn’t a medical label. It’s a mindset where your worth equals your output, and silence feels like failure. The World Health Organization does define burnout as work-related exhaustion, cynicism, and reduced effectiveness. “Toxic productivity” is the street name for the road that can take you there.

Why it sticks to LinkedIn:

• Performative work – post or disappear. The feed rewards visible grind, not quiet focus.
• Comparison at scale – you see highlight reels and decide you’re late to a race that never ends.
• Platform incentives – progress posts get love; recovery does not. That shapes behavior.

Your future might be a hallucination. Mine was. The AI word that snapped me out of it: grounded ⚓

I learned it the hard way building with large language models. Grounded means your words are tied to evidence. In AI, you force the model to speak only from what’s in its tiny short-term memory or real sources. It cuts the nonsense. Not all of it, but a lot.

Then it hit me: people work the same way.

Inside my head, I’ve got a 4K memory of years shipping features and wrestling big codebases. To a recruiter, that all shrinks into one A4 and a 2 minute skim. Their context window for me is tiny. The most grounded candidate wins — the one whose claims are backed by artifacts someone can actually see.

I was ungrounded. No clean site. No crisp portfolio. Just more tokens. So I started grounding my life like I ground a model.

Media buyers don’t buy media anymore - they babysit algorithms and run lab experiments at internet speed.

My AI research agent pulled the raw data on this, and the numbers don’t lie. Almost 9 in 10 display ad dollars are now programmatic. US internet ad revenue blew past 250B. This is where the budget lives, and the modern buyer is driving the bus.

Old school buyer: haggled TV rates and shook hands. New school buyer: lives inside platforms, flips switches, writes naming conventions, and argues with models. Think Meta Advantage+ as the daily grind - broad targeting, machine-picked placements, creative slots to feed, and a budget that needs constant pacing so the machine doesn’t set your money on fire. You edit inputs, the algo does the heavy lifting, and you keep it honest.

What does “keep it honest” look like?

• Incrementality - did the ad create sales you wouldn’t have gotten anyway. You run holdouts and lift tests, not vibes.
• ROAS - return on ad spend. Not the pretty dashboard number, the real one tied

Hot take: in 2025, a sharp video editor is more defensible than an average coder. Code is getting auto-filled. Taste isn’t.

I told a friend - a killer editor - to start a YouTube channel. He shrugged, said “AI will replace me.” Nah. Not the parts that matter.

I had my AI research agent pull receipts. Yes, there are tools that auto-cut and assemble videos - beat sync, captions, reframes, even rough montages from a messy camera roll. They’re real and useful. But most of them are power tools, not autopilots.

The pro stuff - Premiere, Resolve, Final Cut - now handle the boring grind. Transcribe and edit by text. Kill dead air. Auto-captions and translations. Clean ugly audio. Reframe for vertical. Fit music to length. It turns a 6-hour slog into an afternoon. But it still asks you the hard questions: which shot sells the feeling, when do we breathe, what’s the payoff.

There is one place where true automation already wins - sports highlights. WSC Sports chews live games and spits out polished clips in seconds

AI can spit out 10,000 songs before lunch. So why doesn’t your Discover Weekly sound like a garbage disposal? 🎧

My AI research agent pulled the receipts, and the pattern is boring in the best way - the money pipe is guarded.

The majors don’t let you upload at scale. There is no public upload API for Spotify, Apple, or the rest. Spotify even tried direct uploads and killed the experiment in 2019. If you want in, you go through distributors like DistroKid or TuneCore. That means ID checks, payment setup, metadata sanity checks, and a human who can say no. Bots hate paperwork.

Even if you slip through, Spotify watches behavior after the fact. Artificial streaming - click farms, loops, playlist stuffing - gets flagged. They added a 1,000-streams-in-12-months threshold before a track earns recorded royalties, and they can claw back, demonetize, or delist. Remember when a chunk of Boomy tracks disappeared for suspected manipulation? That wasn’t a glitch - that was the system working.

Then there’s ownership. Pla

Ten minutes of your voice on ElevenLabs is worth about a quarter. Not a typo. About 27 cents. 🎤

I tripped over ElevenLabs’ Payouts while looking for their API pricing and had my research agent pull the receipts. Here’s the deal without the sugar.

ElevenLabs pays roughly 3 cents per 1,000 characters when paid users generate audio with your shared voice. That 10-minute script is about 9,000 characters, so you pocket a hair over a quarter. To hit $1,000 in a month, you need north of 30 million characters. That’s a firehose. Weekly-ish payouts through Stripe, around a $10 minimum, and free-tier usage doesn’t pay you a cent.

Yes, you can set custom rates. Cool in theory, but if your price goes up and your discoverability goes down, you still lose. Their Agents product pays per minute, capped around a cent a minute. Same story - volume or bust.

Who actually wins here? The voices that surface on page one. This is app-store economics: a few get the feast, most get crumbs. ElevenLabs flaunts claims of top earners

1 million views is not a gold rush. It’s a tip jar unless you own the funnel.

My AI research agent pulled the raw 2025 payout data, and the math is boring and brutal. Long-form YouTube ads pay about 3k per million views. Shorts pay lunch money - 10 to 200. TikTok pays grocery money - 400 to 1k. Spotify streams are about 3-5k per million. Blogs with ads can hit 5-15k if your niche is rich. That’s the floor, not the dream.

The upside is stacking. Sponsors on a 1 million-view video often pay 10k-75k. Add your own product and things get spicy. If you follow the “5% conversion on 1M impressions” thought experiment, a 15 dollar Gumroad product could show around 640k. Reality check: 0.5-2% is what most people actually convert. At 1%, that same play is about 128k. Still heavy.

Where technical folks eat: assets. 3D models on CGTrader or TurboSquid can net 70-90% and command 5-200 per item. Code assets on Unity or Unreal keep roughly 88% and solve real pain. Theoretical 5% conversion math looks insane - over a milli

China already shipped a Suno rival that writes and sings your song, then spins it into an endless radio stream. Guinness literally recognized the stream as a world first. 🎧

My AI research agent pulled the receipts, and the pattern is clear: Kunlun Tech is the one to watch.

The product to try is Mureka. It takes your lyrics, lets you pick style, tweak sections, swap vocal timbres, and spit out full songs. It is not just a toy - there is a marketplace to sell tracks and chatter about API access for devs. It is the closest thing to Suno’s prompt to full song experience that you can actually use today.

Kunlun also runs Melodio, an AI music streaming app that generates a never ending, personalized feed. That is the one Guinness stamped as the first AI powered music streaming platform. Translation - they are not just demoing models, they are shipping distribution.

If your plan is China first distribution, Tencent Music has a different superpower. Their Lingyin Engine sits inside QQ Music and now lets creators g

Call me an AI slop peddler. I’m not offended. In a world where billions scroll with hungry thumbs, of course machines are cooking the cafeteria stew. Some of it fills you up. Some of it makes you sick. 🥣

Quick reality check: “AI slop” means low-effort, mass-produced content made to farm clicks or rank, not to help. It’s a behavior, not a tool. AI isn’t the villain - spray-and-pray is.

My research bot pulled receipts so I don’t talk out of my beer. Snopes and Wikipedia lay out the term cleanly. NewsGuard has tracked over 2,000 AI “news” sites by 2025. Google’s March 2024 update went after scaled content abuse - think endless auto-pages designed to game search. TikTok and Meta now label realistic AI media. The numbers move, but the trend is obvious.

The good: AI is a blender for curious people. It translates, summarizes, captions, and personalizes at a pace humans can’t touch. It lets a solo creator remix formats that used to need a team. It makes alt-text and plain-language versions fast, so more people can