AI characters keep changing faces between clips. So before making any video, I built mine a reference kit: master face, turnaround, character sheet. Same prompts on 4 image models. Only one got the character sheet right. Process + prompts below.

Bro has better diplomatic clearance than the entire UN at this point. I literally cannot escape this mascot anywhere on my timeline.

Opus 5.5 building Beijing's Temple of Heaven 👀 I asked Claude Code to build the Hall of Prayer for Good Harvests. It: > coded all 773 parts, no 3D models, no Blender > pushed back on my brick and cement: it's marble, timber, glazed tile > followed the real build order

Try these in your first Opus 5.5 session: → Hand over a whole task. Define "done" and when to check in. → Drop "think carefully". It always thinks first. → After a long run, check what it needs to go further. Our playbook: claude.dev/blog/getting-the-…

Green Eggs and Ham, retold as a patchwork quilt. Every frame was drawn in JavaScript by Claude Opus 5.5. The music is code too, and the voices come from Kokoro, an open-source model running on my laptop.

Fascinating aesthetic contrast on Seedance 2.5: • GPT-6 Sol: Heavy horizon lines, cinematic framing, grounded spatial depth. • Claude Opus 5.5: Minimalist ink-wash flow, delicate brushwork, and superior use of negative space.

GPT-6 Sol x Blender

AI race is going crazy this week All the frontier models come out at the same day

She brought a cannon to class. The teacher confiscated her phone. 💀 Apparently, this is exactly what Chinese classrooms are like.

Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe. GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of its strengths into faster and more affordable models to support work at scale. We’ve also made caching and inference more efficient, and we’re passing the savings directly to you: 50% lower API prices for Sol and Luna compared with GPT‑5.6 promotional pricing.

What if @Apple launched a puppy? Introducing Puppy Pro Max. 🐶 Made with grok 4.7 @elonmusk. Designed to be petted.

ByteDance / BytePlus just launched Dramagic for short dramas & video production (Script ➔ Assets ➔ Storyboard ➔ Video). Has anyone here tested the Beta yet? How’s the actual hands-on feel, especially around multi-shot character/scene consistency and collaboration? Would love to hear your thoughts!

I've made 300+ pre-seed investments. The founders who died slowest all had one thing in common: they stopped talking to customers and started talking to their dashboard. Marcus Aurelius ran an empire and still walked the Forum. You have 40 users. Go see them.

Hormozi says the #1 AI play right now is building automations inside businesses that already exist. That job is called GTM engineering. Postings for it grew 205% year over year. Vercel pays $252k and Open AI pays $250k. I wrote the full course/guide on how to master it: - The technical skills - The commercial skills - The 5 core systems - Writing prompts that hold - Building the portfolio - The career ladder - Etc Full breakdown is in the article below:

Jev is "Internet" moment for AI: up to 193x faster and 444x cheaper in tests with Claude Fable 5.1 and GPT-6 Astra Whar is Jev, how to use and unlock its real 100х advantage in my 10-page research: step 1 → meet Jev: LLM writes, agents act, Jev chooses the next move - split intelligence from execution step 2 → turn every agent fork into three primitives: Choice selects one route, Score measures a defined scale, Noul returns the probability of yes step 3 → build before getting access: use TypeSafe’s official adapter with OpenAI, Anthropic or xAI, then swap in Jev without rebuilding the graph step 4 → setup first Jev: one state, three parallel decisions, risk-based thresholds and a real queue your agents can execute step 5 → batch decisions instead of serializing them: 13 questions in one call ran 10x faster and 12.2x cheaper than 13 sequential calls step 6 → place Jev at every bounded fork: choose the agent, model, tool, browser action or human escalation, then read fresh state step 7 → benchmark the entire loop: Browser Use hit Google Flights in 7.1s, Every ran 777 checks in under 0.7s, Mobile Jev completed 9 actions in 21s step 8 → rank wide, read narrow: Jev cut wrong Hermes skill loads from 16.8% to 7.3% and pushed legal Top-10 retrieval from 38% to 62% step 9 → steal a system, not a prompt: Chief of Staff, model router, inbox firewall, research feed, browser controller and safety gate all use State → Questions → Action → Verify step 10 → keep Jev out of math, writing and irreversible execution: code computes, LLMs create, Jev decides, fresh state proves the result the result: one slow, expensive agent becomes an always-on decision machine that routes, scores and escalates in milliseconds Copy the complete 10-page Jev blueprint - then read full 10-step roadmap below ↓