Enoch | White-Label Web Developer
1.5K posts

Enoch | White-Label Web Developer
@birimian_dev
White-label WordPress developer for design and marketing agencies in 🇺🇸🇨🇦 | DMs open for partnerships
Lagos, Nigeria 加入时间 Haziran 2020
485 关注145 粉丝

@shop4rmloveth Normal reaction, they told my uncle to show them the gun, then they finished their robbing, and I think they took it along 😂
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Armed thieves broke into my Uncle’s house in Benin many years back. As everybody dey cooperate make dem thief, comot, na so my cousin (very young then) look one of the robbers shout “my daddy have gun too!”
Chukwuedozie Nwa Charlie@TheCharlesIsidi
Children are security risks men, tell me why this child just told me his fathers date of birth unprovoked? 😭😭😭😭
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@Mussskky @DeFiJesss @Mussskky Hi bro KFB i want to talk to you about getting referal for this P2p project. Good deal
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You can win with other projects on OUTLIER, not just Aether.
Below is what I’ve done within 3 days on Whitebeard.
If you have Whitebeard or other specialist projects and need help managing the account, kindly hit my DM. Let’s get to work.

JESSICA 🌺@DeFiJesss
Another successful onboarding on OUTLIER! If you have the Aether project and you don’t know how to go about the assessment, I’m here for you! If you have other projects on OUTLIER, such as Whitebeard, Almanac, Data Science, Catalyst, and many special skill projects, I’m just a DM away. My team and I deliver clean work 😮💨
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@UnkleAyo Black South Africans are so so daft
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Enoch | White-Label Web Developer 已转推
Enoch | White-Label Web Developer 已转推
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🚨 JUST IN: @claudeai got a huge update today and I'm flattered to be a part of it. As of now, Claude Opus 4.6 can build mobile apps and prepare shipping them on the Apple + Google app stores.
We just launched Shipper a new package that empowers Claude to:
→ Build complete mobile apps
→ Recreate existing apps
→ Assure iOS & Android compatibility
→ Autofill listings for both app stores (app icon, images, descriptions, keywords, privacy policy etc)
Claude Opus 4.6 can do all of the above in one prompt for ~$0.17/app... Publishable from the first prompt & built in 5 mins, not months.
You can try it on Shipper by asking Claude to "create an AI chatbot like Perplexity" or "eBay style marketplace app for local goods".
To celebrate this huge step forward, if you comment "SHIP" you will get free credits.
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90% of American businesses still don’t use AI in production. That single number reframes this entire post.
An AI startup CEO wrote 5,000 words comparing AI to Covid in February 2020. His argument: he describes what he wants built in plain English, walks away for four hours, comes back to finished software. He says every white-collar job faces the same experience within 1-5 years. Millions of people are sharing it as a wake-up call.
The capability trend he’s describing is real. METR, the independent research org measuring AI task completion, shows the length of tasks AI handles autonomously has been doubling roughly every seven months. The models released in early February represent a genuine step change for coding work specifically. If you build software, you’ve felt this.
Here’s what the post skips entirely. Anthropic’s own economic research, published with Census Bureau data, shows AI adoption among US firms went from 3.7% in fall 2023 to 9.7% by August 2025. Two years of the fastest capability improvement in computing history, and fewer than one in ten businesses use AI in production. ISG’s 2025 enterprise study found only 31% of AI use cases reached full production. Lucidworks surveyed 1,600 AI leaders and found 71% of organizations have introduced generative AI, but only 6% have implemented agentic AI, the autonomous agent capability this post describes.
This tells you everything about where the bottleneck actually sits. It moved from “can AI do this task” to “can our organization deploy it.” That second bottleneck runs on procurement cycles, compliance reviews, data infrastructure buildouts, change management, and institutional trust. None of those compress the way model capabilities do.
The pattern repeats throughout technology history. ATMs deployed widely starting in the 1970s. The number of US bank tellers increased until 2007, three full decades later, because ATMs made branches cheaper to operate, which expanded total branch count. Electricity took 30 years to reshape manufacturing after the first power plants went live. Factories had to be physically redesigned around electric motors instead of steam-driven belt systems. The resistance wasn’t technological. It was architectural.
What makes this interesting for your career: the deployment gap is the opportunity. The Deloitte 2026 AI report found only 34% of companies are reimagining their business around AI. 83% of AI leaders report major concerns about generative AI implementation, an eightfold increase in two years. The organizational machinery moves at a fraction of the capability speed.
The people who gain the most from AI over the next three years aren’t the ones panicking about replacement timelines. They’re the ones who understand that slow enterprise adoption creates a massive window to become the person who actually knows how to use these tools. That window is real and valuable. It exists precisely because adoption is slow, which is the opposite of the premise driving the panic.
The capability curve is exponential. The deployment curve is logarithmic. The distance between those two lines is where the actual opportunity lives.
Matt Shumer@mattshumer_
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@nOiCeCrEaMtOdAy @LadyDonli If you’re looking, you can find me
On this cold heartless streets
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