Peter-Yang

Peter Yang's early-access demo generates five scenes with sound and live edits. Failed actions, disappearing objects, and weak gameplay keep the limits visible.

Jake Moran demonstrates an AI editing workflow built around accurate timestamps, storyboards, brand references and feedback drawn directly on video frames.

Peter Yang turns account cleanup into a read-only AI review: inspect access, passwords, sign-ins, API keys, updates and suspicious messages, then approve specific fixes.

Scheduled check-ins and useful work artifacts stand out; browser handoff and access to local skills remain obstacles in Yang's early-access test.

Peter Yang's video-short skill combines an edit plan, generated visuals and frame-specific feedback. His demo still needs several rounds of human review.

Peter Yang compares code-built scenes, games, storytelling, websites, and writing—and finds different winners for different tasks. These are selected demos, not a controlled benchmark.

Isolated workspaces, a readable code structure, before-and-after evidence, and bounded review loops—with a human still deciding what ships.

Peter Yang builds a voice-first Japanese travel tutor from a spec and screen designs, then fixes the voice loop, improves the lessons, and deploys a small private beta.

Granola co-founder Sam Stephenson on pre-meeting briefs, turning conversations into organizational memory, designing AI that lowers stress, and building an AI-native company without the 996 grind.

Peter Yang tests code-generated motion graphics, product launches, talking-head edits, music videos, and anime—then extracts a practical workflow for making better AI-assisted video.

Peter Yang stress-tests the new Opus on five tasks: a Golden Gate Bridge 3D flyover in Blender, a playable Soaring Over the World ride artifact, stroke-by-stroke impressionist painting, Claude Design inside Claude Code, and frame-by-frame video editing - plus the personality prompt that Opus 5 failed.

Ethan Bloch, product lead for ChatGPT Finances, demos a 90-day subscription audit that emails the biller for you, tax optimization, ETF fee swaps, credit-card reward analysis, and interactive decision sites for rent-vs-buy and taking time off.

Peter Yang's hands-on tour of Meta's Muse: $40/month off AT&T by finding an autopay discount, an agent that phones Comcast and negotiates in its own voice, native connectors to Meta's apps, a personalized feed with no ads yet, habit artifacts with streaks, and Marketplace listings it can haggle over.

Peter Yang's 15-step podcast pipeline, split into three ChatGPT Skills (prep, edit, production) that call each other; pastes his manual edits back into the skill as a numbered diff so it one-shots next time.

Brex CEO Pedro Franceschi on scoping agents as virtual employees with a job, skills, manager and budget — the Jim recruiting demo, CrabTrap's LLM-as-a-judge proxy, Magpie for token spend, and the OpenClaw harness he runs his own life on.

Brilliant CEO Sue Khim on why students mostly use AI to cheat today, her AI tutor Cooji that refuses to hand over answers or explanations, and why the most defensible AI products live in domains the frontier labs can't RL on.

Peter Yang builds four games in one night with GPT-6 Astra on the $20 ChatGPT Plus plan — Star Fox-style shooter, train FPS, Starcraft-like RTS, and a roguelike deckbuilder — using free Blender/Godot MCP servers, concept art, and mostly lazy voice feedback.

Peter Yang runs four personal AI agents at once — Instinct, Grok Bot, ChatGPT/Codex, and open-source Hermes — and stress-tests what you're really handing over: passwords, 2FA codes, prompt-injection surface, and whether you can ever get the data back.

Replit's head of engineering on non-coders building real businesses with AI, the cost-of-code-zero test for what SaaS survives, and why app-layer companies are thriving.

Peter Yang's head-to-head across design, writing, planning, coding, browser use, voice, image/video gen, and personal agents — with live demos and a clear overall winner.

Shreya Shankar and Hamel Husain walk through the practical evals loop: top-down vs bottom-up criteria, an open-source Claude Code "error discovery" workflow that turns your taste into a rubric, and why automated eval tools get you a baseline but never replace reading your own data.

A full tutorial on Grok Bot's dedicated cloud computer: advisor, YouTube researcher, X Scout, digital Marie Kondo, and travel concierge — plus the trust question.

Riley Brown's full content stack on Codex: skills for research, hooks, thumbnails, and diagrams — plus his test-based, outcome-driven way of improving skills.

Linear's Nan Yu and Jacob Shumway on the Linear Agent: the skills architecture, evals that grow from usage, minimal instruction, and agents tied to humans.

Nous Research's Karan Malhotra on why Hermes outperforms native harnesses, reward hacking and sycophancy, the Hermes Curator, and a Sonic Chao Garden mod built entirely by his agent.