A daily news analysis show on all things artificial intelligence. NLW looks at AI from multiple angles, from the explosion of creativity brought on by new tools like Midjourney and ChatGPT to the potential disruptions to work and industries as we know them to the great philosophical, ethical and practical questions of advanced general intelligence, alignment and x-risk.
NLW looks at two different ways to categories agents -- by functioning and by focus -- both of which have seven subcategories. Understanding how to organize different types of agents can help you better plan your agentic strategy.
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In today's episode, we dive into the latest predictions around AI-driven job displacement, highlighted by Ford CEO Jim Farley's blunt warning that AI could eliminate half of all white-collar jobs in the U.S. Farley's remarks at the Aspen Ideas Festival, echoed in a pointed Wall Street Journal article, underscore an emerging trend: executives outside Silicon Valley are increasingly acknowledging AI's profound workfor...
At the midpoint of 2025, private markets dominate AI growth, reasoning models spark rapid adoption, and consumer AI reaches unprecedented penetration. NLW analyzes recent reports from Coatue and Menlo, highlighting accelerated IPOs, surging AI coding revenues, shifting public market leaders, and emerging consumer behaviors reshaping the future AI landscape.
Coatue Report: https://drive.google.com/file/d/1Srl8Y4pBoKtNVYZBxmfj2TEMYM5t...
A new band called Velvet Sundown appeared on Spotify with two albums and hundreds of thousands of listeners, but has no evidence of real members or a history online. Music sites note that the music sounds like it could be generated by AI tools, while the band insists it is real. NLW explores the big question: does it matter if it IS AI?
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This episode explores a recent report on how AI companies themselves are utilizing AI. The discussion highlights key trends, including popular AI models, common deployment challenges like hallucinations, and the rapid rise of AI agents. It also examines prominent AI use cases delivering significant productivity gains—especially coding assistance—and discusses evolving business models and cost considerations as companies transition ...
OpenAI is hiring forward deployed engineers and building services that overlap with Palantir, Accenture, and McKinsey. The role focuses on embedding technical staff with clients to fine tune models and develop apps, often backed by $10 million deals.
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The talent war between Meta and OpenAI is intensifying. Meta is handing out massive offers, some rumored at $100 million, as Mark Zuckerberg tries to build a superintelligence team. In this episode NLW talks about why the rest of us who don't work for these two companies should care.
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Andrej Karpathy's Software 3.0 talk reframes LLMs as a new kind of software—programmable, agent-native, and fundamentally different from past computing models. This episode breaks down his key ideas, from autonomy sliders to the need for new infrastructure designed for AI-first users.
Source: https://www.youtube.com/watch?v=LCEmiRjPEtQ
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Enterprise AI agents are moving past experiments and into real use at a record pace. KPMG’s latest survey of over 130 executives at billion-dollar companies shows full deployments of AI agents tripled from Q1 to Q2.
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Vibe coding has taken over. Google’s Gemini CLI and Anthropic’s latest Claude update are making text-to-code workflows easy for everyone. Big platforms like Airtable and Asana are rebuilding around these tools.
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Context engineering quickly becomes a core skill for anyone working with large language models (LLMs) and AI agents. Unlike prompt engineering, which is about crafting single questions or requests, context engineering focuses on providing the right background, files, and environment so LLMs can solve your task.
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As tiny team Base44 sells for $80m just six months after being launched by a single vibecoding founder, are we on our way to our first solocorn? Startups used to be all about big teams and heavy funding. Now, a new trend is taking over: solo founders using AI tools to build huge businesses with almost no staff. Today’s top solo founders are hitting millions in revenue on their own.
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Apple missed the early AI wave and is struggling to catch up. Could acquiring the AI search startup Perplexity be the solution? Insiders reveal Apple executives have considered buying Perplexity, which could replace Google search on iPhones and help revive Apple’s weak AI strategy.
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Although many of the formal AI learning resources are stuck 6-12 months ago, NLW argues that there are a few practical things that anyone can do to get out ahead of the curve on AI right now.
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Google’s Veo 3 launch changed AI video overnight. Suddenly, TikTok and Instagram are full of AI videos with synced sound, sharp effects, and wild new genres. You’ll see viral ASMR clips, Bigfoot vlogs, historical figure parodies, Harry Potter spin-offs, and Star Wars stormtrooper diaries.
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AI might change or even replace many existing roles, but new jobs will emerge to bridge human needs with AI capabilities. From AI auditors ensuring model transparency to AI personality directors crafting how brands interact through AI, fresh opportunities are on the horizon.
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Companies have two main options for building agent systems. Anthropic suggests multi-agent setups, dividing tasks between separate sub-agents. Devon's creators prefer single-agent or linear setups, maintaining context clearly and consistently for tasks like coding.
https://www.anthropic.com/engineering/built-multi-agent-research-system
Cognition: https://cognition.ai/blog/dont-build-multi-agents
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Enterprise AI is evolving quickly. Budgets are rising, agents are becoming essential, and companies demand state-of-the-art AI as soon as possible. Here are 16 insights from Andreessen Horowitz’s latest analysis on how AI transforms the enterprise.
Source: https://a16z.com/ai-enterprise-2025/
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The CEO of OpenAI reflects on the radical transformation we've already beheld and what's to come. He argues that the leaps from 2020 to now are more implausible than from now to 2030.
Source: https://blog.samaltman.com/the-gentle-singularity
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NLW argues that 1) things are moving faster than we think; 2) AI will be even more transformative than we think; and 3) that the winners of a decade from now will be made in the next 1-2 years. Find out why.
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