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The unit of validation is an assumption, not an idea. Kohavi's data shows the industry median experiment success rate is ~10%, which means roughly 22% of 'winning' experiments at p<0.05 are false positives. Sean Ellis's 40% threshold has no publicly available dataset. AI product retention should be baselined at M3 rather than M0, and GRR splits from 23% below $50/mo to 70% above $250/mo.
A Product Builder runs the full loop from problem discovery to design to build, alone. The core difference from a PM: PMs influence execution through authority, Product Builders influence it by directly shipping working products. LinkedIn replaced its APM program with an Associate Product Builder track, and PayFit defined the role back in 2019.
The dominant paradigm in 3D generation in 2026 is video diffusion feeding feed-forward 3D reconstruction, and Lyra 2.0 is the flagship of that line. But three Best Papers at CVPR 2026 point at what comes next: SAM 3D brings foundation-model-scale object reconstruction, D4RT rebuilds dynamic 4D scenes in seconds from a unified transformer, and O-Voxel replaces Gaussians with structured latents. 3DGS still rules, but surface primitives are challenging it, and pixel-space diffusion is pushing back against latent space.
Take apart the feed ranking of ten platforms and they're all solving the same problem: how to trade off between newest, best, and letting new content be seen. What actually decides your answer isn't how clever the algorithm is, but whether your content is oversupplied or scarce — big platforms rank to filter content out, small communities want every post to be seen.
Every official course platform from OpenAI, Anthropic, and Google, plus Stanford CS146S/CS336, Elements of AI, Hugging Face, MIT 6.S191 and more — scraped page by page, then re-sorted into four tiers: AI-curious, vibe coding, shipping to production, and how models actually work. Also covers self-study repos still being updated in 2026 and browser-based platforms that need no local setup, filtered by last-commit date rather than star count. The conclusion: nearly all of it is free. What is scarce is not courses, it is the judgment to pick one. And tier four will not fix your tier three problem.
24 evergreen books across productivity, life design, brain science, psychology, and money — selected using actual discussion evidence from Threads, Dcard, PTT, and Vocus between late 2025 and mid-2026. Strongest signal: Rewire by Nicole Vignola hit top 3 on both Eslite and Books.com.tw H1 2026 bestseller charts.
Most teams don't need five databases. PostgreSQL's extension ecosystem covers caching, queues, full-text search, and vector search — but the real decision isn't 'can it do it' but 'where does ops cost cross performance needs.'
HeyGen's open-source HyperFrames defines video timelines with HTML data attributes, uses headless Chrome for frame-accurate seek-and-capture, then encodes via FFmpeg to MP4. 33k stars in 3 months, Apache 2.0, 21 agent skills — AI agents write HTML to produce video, no React needed.
SRF is the Mini Yuanta Taiwan 50 ETF Futures, tracking the 0050 ETF itself. A NT$7,900 initial margin controls a contract worth roughly NT$110,000 — about 14x leverage. Dividends are handled through an equity adjustment, not the backwardation mechanism used by index futures.
Saw a trading post about going from NT$150k to NT$2.4M in half a year. Didn't understand a word of it — warrants, stock futures, maintenance ratio — so I looked them all up.
Loop Engineering is the practice of designing systems that automatically prompt AI agents, rather than prompting them manually. Boris Cherny runs hundreds of agents, Addy Osmani coined the term, and Blake Crosley identified verification cost as the real bottleneck — this article covers primary sources, the five building blocks, applicability boundaries, and criticisms.
Climbing books don't exist in isolation — they represent competing schools of thought, philosophical differences, and knowledge gaps. This post maps the relationships between 60+ books to help you pick the right one to read next.
It's really a two-way choice now: @playwright/mcp (cross-browser, accessibility tree, token-cheap) versus chrome-devtools-mcp (Chrome's official server, performance and memory diagnostics). @modelcontextprotocol/server-puppeteer has been archived and is no longer a candidate. The dividing line is no longer abstraction level — it's 'drive the page' versus 'diagnose Chrome'.
chrome-devtools-mcp, maintained by the Chrome team, packages DevTools capability as an MCP server: performance traces and insights, Lighthouse audits, heap snapshots, extension management — none of which @playwright/mcp exposes. It runs on Puppeteer, so interactions auto-wait; the costs are Chrome-only support and usage statistics reported to Google by default.
@playwright/mcp defaults to an accessibility tree (browser_snapshot) instead of screenshots, cutting token consumption sharply. Combined with Playwright's native auto-wait it's a sensible starting point for AI agents doing web automation — but note it now runs headed by default, keeps a persistent profile by default, and gates advanced tool groups behind --caps.
server-puppeteer is the Puppeteer wrapper in the official MCP servers monorepo — seven lean tools built around screenshots and evaluate. It has since been archived (moved to servers-archived, no longer published), so it is not a choice for new projects; if you want Puppeteer lineage in an MCP server today, look at the Chrome team's chrome-devtools-mcp.
A 2x leveraged ETF system traces its philosophy to three books: A Random Walk Down Wall Street answers 'what to hold' (index funds), Lifecycle Investing answers 'how to accelerate' (leverage to diversify time risk), and The Four Pillars of Investing answers 'how to survive' (rebalancing discipline). Combined: 60% 2x ETF + 40% cash, Beta=1.2, ±10% rebalancing trigger.
From the CLI tool kin3o to the CVPR 2026 paper OmniLottie — a survey of open-source approaches for converting text and images into Lottie animations, with performance benchmarks and selection guidance.
AI agents running tests are non-reproducible; hand-written Playwright is hard to maintain. Four tools that emerged in 2024-2025 each tackle this dilemma with very different design philosophies.
MUSE-Autoskill (2026) introduces a five-stage skill lifecycle framework. Self-created skills achieve 60.35% (+7.16%) on SkillsBench overall, and an impressive 87.94% on tasks where skill generation succeeds — surpassing the human-authored skill ceiling. This post synthesizes six arXiv papers to map the full landscape of skill evolution research.