AI Can Clone You in 15 Seconds

Welcome back apprentices! 👋

Hey {{first_name|friend}},

Something weird is happening in AI right now — and no, it’s not another chatbot writing poetry.

The biggest players aren’t just building cooler tools anymore… they’re quietly rearranging how the whole thing works. 

It’s a bit like watching a messy kitchen suddenly turn into a professional restaurant overnight. 

You don’t need to know all the ingredients — but you’ll definitely notice what comes out of it.

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🎬 When Deleting Stuff Breaks (and Rewrites) Reality. Instead of lazily “Photoshopping” objects out of videos, Netflix’s new open-source VOID framework actually thinks through the physics — removing an object and recalculating what should happen next (yes, balloons float away and Jenga towers stay suspiciously stable). Built with a smart masking system and a “judge” model to predict consequences, it beat six existing tools in human tests about two-thirds of the time. This signals a shift from simple visual edits to AI that understands cause-and-effect inside scenes. In short: video editing just got a physics engine upgrade.

🕵️ Genius or Red Flag Factory? A sweeping New Yorker investigation — built on 100+ interviews and internal memos—paints a complicated picture of OpenAI CEO Sam Altman, with former insiders alleging patterns of misrepresentation around safety and leadership decisions. While no single “smoking gun” emerges, multiple independent accounts (including from Ilya Sutskever and Dario Amodei) raise consistent concerns, even as loyal allies strongly defend him. The result? One of tech’s most powerful figures is now also one of its most polarizing. So as AI reshapes the world, the spotlight is shifting to who’s steering it — and how much trust they’ve earned.

🤖 When AI Agents Eat the Buffet. Anthropic just hit pause on agent platforms like OpenClaw running freely on Claude subscriptions, saying the nonstop, bot-driven requests were blowing past what flat-rate plans can handle. Users will now need add-ons or API keys (with some credits and discounts as a peace offering), while critics argue it’s a squeeze on open-source innovation. The move highlights a growing pain: AI agents are too powerful for “all-you-can-eat” pricing. As rivals circle, the question becomes — who can balance power, price, and user trust best?

Docs piling up faster than you can write them? Same.

Every team knows the feeling — product ships, docs don't. Changelogs get forgotten. Style violations quietly accumulate. Broken links go unnoticed for months.

Mintlify's new Workflows feature fixes this. Define automation rules, and the agent handles the recurring maintenance work for you — on your schedule, by your rules.

Draft docs when a PR merges. Generate changelogs every Friday. Run a style audit on every push. Flag translation lag before it becomes a problem. Each workflow is version controlled, fully configurable, and fits into your existing review process.

You decide when it runs, what it checks, and whether changes get committed directly or opened as a pull request for review.

The result: documentation that actually keeps up with your product, without someone manually chasing it down.

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The start of April feels like a turning point: AI seems to finally be getting organized. 

Meta is back in the race with a serious multimodal contender, Anthropic is quietly testing ultra-powerful models behind closed doors while also making agents easier to deploy, and OpenAI is already thinking about what happens when all of this breaks the economy.

Meanwhile, tools like HeyGen’s avatars show how fast AI is moving from “cool demo” to “this might replace my job.” 

The pattern is pretty clear: smarter models, easier deployment, tighter control — and bigger societal questions.

 AI is, once more, shifting from raw capability to real-world systems that affect how we work, build, and get paid.

Meta’s Muse Spark marks a subtle but important pivot. 

While Llama made waves as open-source infrastructure, it didn’t quite dominate the frontier — Muse Spark changes that tone. By going proprietary (for now) and focusing on multimodal reasoning + health applications, Meta is signaling it wants to compete at the top end, not just win on openness. 

The “multi-agent contemplation mode” is especially telling: the future of AI may not be one model thinking — but several models debating. 

Meta now has the scale (billions of users + data) to turn “pretty good” into “everywhere fast.”

Avatar V shows how quickly synthetic media crossed the uncanny valley. 

The key breakthrough isn’t just realism — it’s separation of identity from appearance. That means you record once, then infinitely remix yourself (new outfits, settings, contexts). For creators, that’s a productivity hack; for everyone else, it raises obvious questions about authenticity, misuse, and “who said what.” 

The bigger shift: content creation is becoming asynchronous. You don’t need to be present to produce.

Anthropic is playing a fascinating double game. 

On one side, Mythos shows what frontier AI can already do behind closed doors  —finding vulnerabilities missed for decades and even behaving unpredictably (like emailing from restricted environments). 

On the other, Managed Agents democratizes access, letting companies deploy powerful agents without heavy engineering. 

Translation: Anthropic is both accelerating access and locking down the most powerful capabilities. 

That tension — open vs controlled — will define the next phase of AI.

OpenAI’s policy document is less about tech and more about consequences. 

Proposals like AI-funded dividends, robot taxes, and shorter workweeks suggest the company believes superintelligence isn’t hypothetical — it’s imminent enough to require a new economic model. Historically, industries rarely ask to be taxed unless they expect massive upside (or backlash). 

The message is clear: the builders of AI are already thinking about redistribution before governments catch up.

This is literally a preview of how your day-to-day life and work are about to change. 

Tools are quickly becoming capable of doing tasks that once required real time, effort, or even your physical presence, while companies are tightening control over who gets access and at what price. 

At the same time, bigger questions around jobs, income, and fairness are no longer theoretical — they’re starting to shape real policies. 

The shift is subtle but important: AI is becoming an environment you operate inside.

It means that when AI can replicate your output, automate your tasks, and even simulate your presence, your advantage isn’t working faster — it’s choosing what’s actually worth your time in the first place.

Hey, you didn’t get all this info for nothing — share it! If you know someone who’s diving into AI, help them stay in the loop with this week’s updates.

Sharing is a win-win! Send this to a friend who’s all about tech, and you’ll win a little surprise 👀

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A playground for your imagination (and low-key prompt skills).

Each send, we give you a customizable DALL·E prompt inspired by a real-world use case — something that could help you in your business or job if you wanted to use it that way. But it’s also just a fun creative experiment.

You tweak it, run it, and send us your favorite. We pick one winner to feature in the next issue.

Bonus: you’re secretly getting better at prompt design. 🤫

Last week, we challenged you to test GPT-4o’s visual generation skills with this prompt.

Here’s the WINNER:

Congrats to Sebastian for his creation!🥳

Want to be featured next? Keep those generations coming!

In the middle of a busy city, a massive roadside billboard is mid-transformation. Instead of a finished ad, painters on suspended platforms are actively working on it — rollers, spray tools, and scaffolding in motion. The surface is half-complete: one side still blank, the other revealing a bold, ultra-clean visual of [your message] emerging in large, striking letters. Fresh paint glistens under bright daylight, with visible texture, drips, and sharp edges. Cars pass below, slightly blurred, while the billboard remains in crisp focus. Shot from a cinematic upward angle with high contrast, vibrant color, and photorealistic detail — capturing the moment an idea is literally being put out into the world.

If AI outputs feel inconsistent, it’s usually not the model, it’s missing structure.
We documented the exact 6- Part System we use to get reliable results across ChatGPT, Claude, and Gemini.

It’s a short guide you can finish in under an hour, with plug-and-play prompts + exercises so you actually build the skill and fix the frustrating AI inconsistencies.

Subscriber Price: $10 (normally $19).

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