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AI 2027

AddyOsmani.com - The Code Agent Orchestra - what makes multi-agent coding work

AI Learning Resources & Guides from Anthropic Anthropic

AI layoffs to backfire: Half quietly rehired at lower pay • The Register

FedEx Is Planning an AI Agent Workforce - WSJ

Anthropic Courses

Conductor - Run a team of coding agents on your Mac

Aakash Gupta on X: "You need to have started using OpenClaw yesterday. Here's the web's easiest setup guide + 5 killer use cases: 38:06 - 1. Live knowledge bot 47:47 - 2. Automated standups 54:46 - 3. Push-based comp intel 1:13:26 - 4. VOC reporting 1:24:

Ronin on X: "How to become an AI Engineer in 6 months (RESOURCES)" / X

(112) Inside Ramp, the $32B Company Where AI Agents Run Everything | Geoff Charles - YouTube

We're All in the Lab Now - by will murphy

(138) AI Agents Full Course 59 Minutes (for beginners) - YouTube

Deedy on X: "Every single one of the 103 companies Jensen called AI Native today. https://t.co/cjna7Oc3AN" / X

With 1 AI Feature No One Asked For, Grammarly Burned Its Brand

AI Is Boosting Productivity—but Data Shows Employee Workloads Are Getting Heavier

Silicon Valley’s New Obsession: Watching Bots Do Their Grunt Work - WSJ

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mariodian/jobs: Analyzing how susceptible every occupation in the US economy is to AI and automation, using data from the Bureau of Labor Statistics

AI, Human Cognition and Knowledge Collapse | NBER

Chapter One Of My Book - Investing In AI: Six Mental Models To Tell Moats From Traps

[2601.12339] The Economics of Digital Intelligence Capital: Endogenous Depreciation and the Structural Jevons Paradox

The Red Queen Effect (Endogenous Depreciation): Unlike a factory that wears out physically, AI assets lose value because competitors get smarter. Firms must invest at massive levels just to maintain their relative market position, creating a permanent "innovation tax."The Structural Jevons Paradox: As the cost of AI "tokens" (intelligence units) drops, total demand actually increases rather than stabilizes. This is because developers adopt more complex "agentic" architectures (like recursive reasoning loops) that consume vastly more compute than simple prompts.The Data Flywheel: Superior models attract more users, which generates more feedback data, further improving the model. This creates a "winner-takes-all" dynamic where the market naturally tips toward a monopoly once a certain threshold of data efficiency is reached.