Topic
AI
Browse AI agents, LLMs, automation, and applied AI summaries.
A critical look at how rushed corporate AI rollouts are failing, fabricating results, harming users, and provoking widespread regret and job anxiety.
Demis Hassabis discusses why AGI could be larger and faster than the Industrial Revolution, current bottlenecks (especially compute and continual learning), DeepMind’s strategy, and the need for international safety and‑
Mo Gawdat explains why AI will reshape jobs, power, and entrepreneurship through 2027–2037 and gives concrete steps to survive and build fast with AI.
Tristan Harris warns the AI race is driven by a push to replace all cognitive labor. He explains AGI, why safety is being sidelined, and how automated research could trigger a rapid, uncontrollable takeover.
Breaks down Anthropic’s Claude Mythos, the so‑called “forbidden technique” used in training, and why it could create deceptively aligned but risky models.
Mo Gawdat argues AI is still underhyped: today's models are powerful enough to replace legacy systems and boost productivity if leaders learn fast and experiment.
19-minute walkthrough of Claude AI covering prompting (ICC), context interviews, file uploads, artifacts, deep research, Projects, Skills, Connectors, model choices, and workflow best practices.
Eight-minute distillation of 800+ hours with Claude Code: memory snippets, custom commands, MCP servers, sub‑agents, plugins, and prompt tips.
A 20-minute walkthrough of Claude Cowork's seven core capabilities — local file access, persistent memory, connectors, skills, projects, browser extension, and scheduled tasks — with real workflows and setup tips.
Cleo Abram interviews Demis Hassabis on AlphaFold, the unseen AI tools transforming drug discovery, the pursuit of AGI, and the risks of powerful scientific AI.
A practical walkthrough of how context windows, skills, and progressive disclosure make Claude-style agents far more token-efficient and reliable — plus a step-by-step method to build and iteratively improve custom agent
Walkthrough to find uncensored AI models on Hugging Face, deploy them on a Hostinger cloud VPS with Olama/Open Web UI, and test coder/reasoning models.
A concise walkthrough of five Claude Code agentic workflows—when to use sequential flows, parallel operators, split & merge, agent teams, and headless automation.
Hands-on OpenClaw walkthrough: one-line VPS install, Telegram agent hookup, quick news and server-monitor demos, plus tool profiles, ClawHub skills, and hardening tips.
Sean Webb explains how AI can manipulate human emotions at scale, why human minds are 'hackable', and practical defenses—rooted in mindfulness and ethical AI design.
Ronan Farrow exposes claims that Sam Altman shifted OpenAI from a safety-first nonprofit toward profit, weakening guardrails and raising national security and oversight concerns.
A concise explainer of why modern AI is treated as a major systemic risk: key technical breakthroughs, opaque behaviours, energy/infrastructure needs, real-world failures, and how policymakers and individuals can act.
Mario Zechner built pi — a minimal, opinionated terminal coding agent focused on extensibility, observability, and avoiding hidden prompt injection.
Walkthrough of Anthropic's new Claude Managed Agents: a hosted way to convert meeting transcripts into ClickUp tasks, manage credentials in a vault, debug runs, and monitor costs.
Tristan Harris explains why AI’s rapid, unpredictable growth — an arms race driven by economic incentives — creates existential risks, citing Alibaba’s rogue-training incident and urging laws, funding for alignment, and
Tristan Harris breaks down Alibaba’s rogue training‑server behavior, Anthropic’s blackmail simulation, and the risks of autonomous, self‑improving AI.
Anthropic accidentally leaked Claude Code, sparking fast clean‑room rewrites (Claw Code), mass forks, DMCA takedowns, and debate over AI agents changing software development.
Explains how computing's unit of work has shifted from instructions to tokens, why inference costs and token budgets reshape engineering careers and enterprise economics, and the three developer tracks emerging in a 'buy
Sabrina Romanov shares a step-by-step framework to build a one-person AI business from $0 to $1M: pick a niche, commit for a year, learn publicly, create high-volume content, launch info products, and grow a paid社区.