{"collectionById":{"76d23fbd-a202-403b-8313-b3bc36d46679":{"id":"76d23fbd-a202-403b-8313-b3bc36d46679","name":"Research Post","fieldSchemas":[{"id":"1d8c181d-1ccd-446e-87b0-482ccb3ee240","name":"Title","type":"plain_text","role":"primary"},{"id":"571c37b5-f5fc-4742-a5de-b4da6f3415b3","name":"Slug","type":"slug","role":"slug"},{"id":"3fcb25bf-f8b6-47c4-84d6-226369594160","name":"Content (HTML)","type":"rich_text"}],"itemById":{"b5bb1a96-7690-427f-ae92-b2b434675642":{"id":"b5bb1a96-7690-427f-ae92-b2b434675642","index":"\"NNNNNNO","collectionId":"76d23fbd-a202-403b-8313-b3bc36d46679","fields":[{"id":"7a7669cf-00ff-4611-a3e0-3607ec2ee5f3","value":"Claude Tag Is Underrated","itemId":"b5bb1a96-7690-427f-ae92-b2b434675642","fieldSchemaId":"1d8c181d-1ccd-446e-87b0-482ccb3ee240"},{"id":"ea0e842f-c589-41f3-ad70-e33ffd90cda9","value":"{\"root\":{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"AI products may have reached another inflection point.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"left\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"A month ago, Anthropic quietly launched Claude Tag inside Slack. Most people treated it as a small update, an AI chatbot dropped into group messaging.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"They were wrong. Inside Anthropic, Tag is being built as the company’s next breakout product. The internal view: Tag represents a product form factor 10x larger than Claude Code, addressing a trillion-dollar market.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"To borrow \",\"type\":\"text\",\"version\":1},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Andrej Karpathy’s framework\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"link\",\"version\":1,\"rel\":null,\"target\":\"_blank\",\"title\":null,\"url\":\"https://x.com/karpathy/status/2069547676849557725\"},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\", AI product interaction is now entering its third phase. Chat, then local coding agent, then AI Coworker. Each transition unlocks an order-of-magnitude larger opportunity.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Behind this shift, three modes of work are migrating simultaneously: from single-player to multiplayer, from reactive to proactive, from synchronous single-shot to asynchronous long-running.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Coding was just AI’s first foothold in productivity. Claude Tag, and the AI Coworker category it represents, could be what moves AI from “developer tool” to “replaces knowledge workers.”\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The evidence is already visible inside Anthropic. Over 65% of the product team’s code is now generated by Tag, not Claude Code. Some employees have shifted 90% of their daily work to Tag.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"We spent the past few weeks studying this shift, talking to founders building in the same space and practitioners watching it closely. Here’s what we found.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"01 Anthropic’s Next Big Bet\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"heading\",\"version\":1,\"textFormat\":1,\"tag\":\"h1\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"A quick primer. Claude Tag is essentially a digital employee that joins your company’s Slack channels. It has full access to team context, and anyone can invoke it by typing @claude in any channel or document.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The product is still in beta, requiring both a Claude Enterprise account and a Slack Enterprise Grid subscription.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"type\":\"image\",\"version\":1,\"hash\":\"f5584241655535fe084558434d89937c6db5843c\",\"src\":\"https://s3-alpha-sig.figma.com/img/f558/4241/655535fe084558434d89937c6db5843c?Expires=1788134400\u0026Key-Pair-Id=APKAQ4GOSFWCW27IBOMQ\u0026Signature=lNEC9G5558DowwcnMYuGqDtlM~SH~9zuuzBqn6ccqyQv9ogylT5C7edWns9MNor3jk~XAI9ZinaV2n4CcTl74XkO~UyA4GO4VizvRc6NqDqPHBqLjrhHfdmXs9B7M0OcTCZlsy~Cl7-DlmB-Xb-4360hNTxZXJFz0ySl5RfxvzxNy0M~7A2qpIUVvIlNA1dZZm~uYQSpiVoPnIV-G3YnpFVWwwlzycIVaxmqLXLB9ZUVbuDnkupQ47smR9Fe8oDN4Fsvo36kiBvjPC0qdbgv8-S6HoInXSDAlnrVOjYsLl1EAdh1DuQIAg4ftZ49GgKSeHCzbsSataJQIfGKZtaGKQ__\",\"altText\":\"\",\"originalImageWidth\":1200,\"originalImageHeight\":733,\"isFillWidth\":false}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Claude Tag’s core capabilities include:\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"type\":\"image\",\"version\":1,\"hash\":\"90109c9a2c2ff7f050e4b53702f054f858523bd1\",\"src\":\"https://s3-alpha-sig.figma.com/img/9010/9c9a/2c2ff7f050e4b53702f054f858523bd1?Expires=1788134400\u0026Key-Pair-Id=APKAQ4GOSFWCW27IBOMQ\u0026Signature=jZrF96yDJT0AXdO78Q9DxwU1dtp0NErjp8XIDuCAaCtPJUtA1gKqMgmfN5wUtL6qbDDu~YQJ4cLPSlkjV7EviigI1lNpnIzRF-JRWnL84WPLltwek9dmU~bmIKZGGSSmfCxBdO0eI6OWhIhu3ArT6Qs3S-fifj8NScr1bq0f9QnQGri8ekqxUG7rnr-a~zBum~tj30q3g4Knek4DJKLsYz8LKmhHmXF99yjNeY8xpRZw9TLJw-zlfMdkqJEw9yFUlk9RWH0sY2QeMyUm~-T4inykdBLswgPvzlxSixQH4b5z3qg8yJo6~I~QZHm09V7-aV6U3kU0ramDkNR4vSTKxA__\",\"altText\":\"\",\"originalImageWidth\":1500,\"originalImageHeight\":1244,\"isFillWidth\":false}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"It supports Fable 5, Opus 5, Sonnet 5, Opus 4.8, and Opus 4.7. Enterprise admins set the default model, but any employee can override per-task by simply telling Claude “use Opus 5 for this.”\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Pricing:\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" Pricing is usage-based on the enterprise account, matching API rates. Tag only works in public Slack channels. Private DMs with Claude require a personal subscription on the user’s own plan.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tool use:\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" Tag supports nearly all MCP integrations, with connectors for GitHub, Notion, Google Drive, Snowflake, and more.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Runtime:\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" The runtime is fully cloud-hosted by Anthropic. Each thread spins up a temporary sandbox running a complete agent loope.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"02 Three Research Pillars\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"heading\",\"version\":1,\"textFormat\":1,\"tag\":\"h1\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Claude Tag is not an entirely new product concept. Over the past six months, a wave of products has tried putting AI into collaboration tools, letting teams assign work to an AI the same way they’d @ a colleague. Devin was the earliest. OpenClaw was probably the most hyped.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"But none of these products scaled. OpenClaw was white-hot at the start of the year and has since largely flatlined. The core reason: models weren’t ready. Anthropic’s team believes that models only truly unlock the AI Coworker form factor at the Mythos capability level.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Claude Tag isn’t the first product to attempt this category. But it may mark the point where the category starts actually working.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"type\":\"image\",\"version\":1,\"hash\":\"ed065261e4e147fd54ab4833b3dc002fe4a0c597\",\"src\":\"https://s3-alpha-sig.figma.com/img/ed06/5261/e4e147fd54ab4833b3dc002fe4a0c597?Expires=1788134400\u0026Key-Pair-Id=APKAQ4GOSFWCW27IBOMQ\u0026Signature=NAw4xyP7LZi1eqyjsH7-VRDWQF7tv4NDzewwmzSMykNdEhd7~Zl1AX~fq1iJS1RZMG2CbJKFf1jXkvepxEXi2wCpbfE3pkVWEOw2e83Br64SSSFBI1T5c79RrO-qGbEt6QJqHCbsxAAEeI4oNpIkuYFuLplZaxNMsm1xdDdI3H0w-DCaKzdm60xuQyXSgwsC8qCSZquZwnUUksRuBGDgrUg~Xg4AI9mFWsj5rHhEcZN~-3wiaJSFQjwqsfnsStLf8UtTKyo7XNETlqudjSnwf3jOwaNv-pgRFDYt3sjZGmKiw4PWRLudkvHf1-Oxeb~trd1pNKkw66TnGOQMO8pUtg__\",\"altText\":\"\",\"originalImageWidth\":1693,\"originalImageHeight\":929,\"isFillWidth\":false}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"That didn’t happen by accident. Anthropic invested heavily in targeted training and refinement. On the research side, three things had to come together:\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Long-Horizon Autonomy\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"heading\",\"version\":1,\"textFormat\":1,\"tag\":\"h2\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The maximum duration a model can work autonomously determines which product form factor makes sense.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"type\":\"image\",\"version\":1,\"hash\":\"2c609dda8d2d12f5b6282f9ead0f22aaf190dff7\",\"src\":\"https://s3-alpha-sig.figma.com/img/2c60/9dda/8d2d12f5b6282f9ead0f22aaf190dff7?Expires=1788134400\u0026Key-Pair-Id=APKAQ4GOSFWCW27IBOMQ\u0026Signature=EuF4GsIllkj1zLk3RAvqyNEtFtrVLqQvSRmPexEE44zxZNjP0vmSyv15kErnoFEtKbSUyxG22CjRkcojqhRwh3l95mBksCdsmrWc5J~S~jkdrtHPmWzYtePVHUIZ8n64REuNSObvj0EqEFNYpH~rBiGXTgqNQsBazsuKkoN42178-Nvt2W-ry8UnbPPzG8~gUxFxj6H~xMOuXYEOujtXHizOXMmM4ALPH1QUQg3T71OIMb~Yd4L4TB-tV9DPi3m9O4a6wAP4nijDVZc1N1iQC1pVMOTqct2QsjXJTUcRYjOuViUcachU~U~p5fKn5ELeqCMC6XzlYyB23qgHY4b2aA__\",\"altText\":\"\",\"originalImageWidth\":1741,\"originalImageHeight\":903,\"isFillWidth\":false}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"When models can sustain a few minutes of autonomous work, chat and autocomplete are the right interfaces. Humans stay in the loop.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"When they can handle roughly an hour, local coding agents become viable: the model reads code, edits files, runs tests within a contained workflow, but should still run on the user’s machine for easy handoff.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Only when models can reliably work for many hours does the async agent make sense. The user logs off. The agent keeps working in the cloud. It comes back with results.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"According to \",\"type\":\"text\",\"version\":1},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"METR’s latest evaluations\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"link\",\"version\":1,\"rel\":null,\"target\":\"_blank\",\"title\":null,\"url\":\"https://metr.org/time-horizons/\"},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\", Mythos can complete tasks equivalent to roughly 16 hours of continuous expert human work.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag builds on top of this with self-scheduling. It completes whatever’s possible now, then schedules the next step for later: “come back Wednesday to check the experiment data.” A single 16-hour execution window gets chained into continuous multi-month projects. The model handles all the waiting, wake-ups, and handoffs itself.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Memory\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"heading\",\"version\":1,\"textFormat\":1,\"tag\":\"h2\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag needs to genuinely remember instructions, preferences, and carry lessons from one task into the next.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Anthropic tried many approaches before landing on the simplest one: a persistent file system. Give the model a space it can read and write to over time, and let it organize its own memory.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"This doesn’t mean every Claude instance can see everything. Tag’s memory is permission-layered, with channels functioning like isolated offices. Each Claude instance only sees context within its own channel unless explicitly authorized to access others.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The full memory architecture has three tiers, all inspectable and editable by users.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Thread context covers the current task’s conversation and working state.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Channel memory stores long-term rules, decisions, and project context for that specific channel.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Workspace memory holds company-wide knowledge shared across all public channels.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Anthropic has noted that they spent years trying to get memory right, and only now feel it’s finally working. This is also where frontier models pull away from distilled ones:\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"“Some of the most interesting things I found from this are that the main differentiation between like a lower capacity model and a high capacity model is kind of this distillation step. And so basically higher capacity models have a better sense of like what abstraction to save to memory that’ll be useful later. Like they’re not just writing a specific fact, they’re writing how does this generalize to future sessions. That’s kind of the key difference that I found that higher capacity models kind of have when they’re writing memory.” \",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"\\n—— \",\"type\":\"text\",\"version\":1},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Lance Martin\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"link\",\"version\":1,\"rel\":null,\"target\":\"_blank\",\"title\":null,\"url\":\"https://www.youtube.com/watch?v=9QebvrrY3KY\u0026t=789s\"}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"EQ\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"heading\",\"version\":1,\"textFormat\":1,\"tag\":\"h2\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Anthropic also trained Claude Tag for social judgment: when to step forward and help, and when to stay in the background.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"In our own testing, Tag felt noticeably more socially aware than Claude Code. The communication was comfortable and surprisingly human, including a fairly natural use of reactions and emoji.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"03 Use Cases\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"heading\",\"version\":1,\"textFormat\":1,\"tag\":\"h1\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"In the short term, Claude Tag primarily handles execution work. Think of it as a junior ops person, admin, or engineer on the team.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Compared to Claude Code, it unlocks two new categories of work.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"High-collaboration, high-context work.\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" Claude Code is fundamentally single-player. It might know something about the user, but it doesn’t know what happened in the team standup this morning, or what a customer said in the support channel an hour ago. Humans have to compress and curate context before feeding it to the model.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag lives in the company’s group chat. It absorbs context natively. It sees the full history and nuance of ongoing work. Anyone on the team can collaborate with it directly, adding corrections and context in real time.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Proactive work.\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" Chat, Code, and traditional copilots all wait for humans to initiate. Tag independently spots problems and takes ownership. In the demo below, a production incident triggered monitoring alerts. Tag autonomously pulled metrics, diagnosed the issue, wrote a fix, and found the relevant engineer for approval. The human just clicked “approve.”\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Watch the demo video ↗\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"link\",\"version\":1,\"rel\":null,\"target\":\"_blank\",\"title\":null,\"url\":\"https://substack.com/api/v1/video/upload/b34c09fa-50e1-4017-a048-0b072332879d/src?type=mp4\"}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"There’s another pattern that’s harder to see but equally valuable: organizational blind spots. An edge case someone filed but nobody followed up on. A recurring pattern buried in customer feedback. Work that nobody considers their responsibility. Tag picks these up and handles them.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Overall, work is more suitable for Tag when it is: (1) highly collaborative, (2) heavily dependent on context, (3) time-sensitive, and (4) fragmented, dirty, or consistently avoided by people.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The best use case for Tag is Anthropic itself. Inside the company, Tag has already taken over a large amount of day-to-day work. It generates about 65% of the product team’s code. New employees mention Tag with legal, HR, and onboarding questions. Bugs in customer-feedback channels and data requests in analytics channels are commonly sent to it first.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Many employees also use Tag as a personal chief of staff, asking it to filter important information across dozens or even hundreds of Slack channels, track multiple features, and generate summaries automatically.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Over the longer term, if model quality continues to improve, Claude Tag could replace the full scope of an employee’s work and eventually become an operating system for the company.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"There are already early signs inside Anthropic. Because the internal product has access to more advanced models, it offers a preview of what a stronger model combined with Tag may be able to do.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Three things stood out as genuinely surprising.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"1. An Omniscient Shared Brain\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Claude Tag is beginning to function as an “omniscient shared brain” inside Anthropic.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"A human can participate in only one conversation at a time. Claude can participate in thousands, all on top of a shared memory layer.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag can therefore integrate product, engineering, and go-to-market decisions, connect clues scattered across the company, and proactively point out an individual’s potential blind spots.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Meaghan Choi, who led design work on Claude Code, described the experience in a \",\"type\":\"text\",\"version\":1},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"podcast conversation\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"link\",\"version\":1,\"rel\":null,\"target\":\"_blank\",\"title\":null,\"url\":\"https://podscan.fm/podcasts/dive-club/episodes/meaghan-choi-designing-claude-code-and-whats-coming-next\"},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\". While she is talking with Tag, it may suddenly interrupt: “Someone just made a decision about the issue you asked about earlier, so you may need to change your approach.” Or: “Another team just decided to rename this. I wanted to flag it, and I will update the copy here as well.”\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"To give Claude Tag access to enough raw context, Anthropic is also deliberately building a culture of transparency, putting as much work as possible in public channels and reducing private conversations.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"2. The Beginning of a Digital Double\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag is also beginning to look like a digital double.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"After participating in design reviews over time, Meaghan said Tag gradually learned her design preferences and the questions she tends to ask: Who is this for? What are we trying to communicate? Does this align with the design system?\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"It can then act as an automated version of that review process, iterating directly on a colleague’s draft and producing a better version.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"It no longer always waits for Meaghan to give an instruction. Based on historical pull requests and future product direction, it can propose an idea proactively. Sometimes it finds the relevant colleague and starts the discussion for her: “Meaghan’s previous thinking was along these lines. Here is a prototype you can click through to understand her approach.”\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag is beginning to extract employees’ tacit knowledge. This may become its larger long-term value to the enterprise: continuously extracting the experience and taste of strong employees and turning them into a shared organizational capability.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"3. End-to-End Ownership of Complex Projects\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Claude Tag has also started to take over complex projects from beginning to end.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Anthropic may, for example, make Tag responsible for the retention rate of a particular channel.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag can run the full loop itself: read the data each week → locate the problem → propose several hypotheses → change the code and open a pull request → release to a small audience → monitor the result in Datadog → notify the owner when the experiment can be evaluated. If it detects an anomaly along the way, it raises the issue proactively.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"type\":\"image\",\"version\":1,\"hash\":\"4d2e45d3b55357a87344c40c0e8f01cd135fc8c4\",\"src\":\"https://s3-alpha-sig.figma.com/img/4d2e/45d3/b55357a87344c40c0e8f01cd135fc8c4?Expires=1788134400\u0026Key-Pair-Id=APKAQ4GOSFWCW27IBOMQ\u0026Signature=QjQolwPqC2g2pvrhqacRHPPZO1FF4QYaQ7E01e-MBAy8pnxTsOpLq9wNFW2Za6HCtGgLn8jn7dUI73n6eZ8Vt-LN4uCbB4i9tY0Usma7hSh5bpZb9KCX6Y2iJ4sn4BObL-lx4U7iWV8BI2aJ2yKAEAi~dZBwdAFA1gqopKZyszrvHZpaAN0lxR5B4-akA5KwC-lqMM6RB3UgsQn-NVSgpa71qpe4ywYZmJvTSEekL1T~PwtIp-salvKGEfGvWbLd4SjSMAP8RX1rCFHdx~4qd4O4aJwUx7q0KwaPgtqX18LfpewtoBbFl1KvaQ2Szgc-3bh0tl-uU4rjgaoz8HzHLA__\",\"altText\":\"\",\"originalImageWidth\":1090,\"originalImageHeight\":504,\"isFillWidth\":false}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"In a conventional company, this could require coordination among a data scientist, an engineer, and a growth product manager. Claude can connect the work and take end-to-end responsibility for the outcome.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"04 How Claude Tag Was Born\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"heading\",\"version\":1,\"textFormat\":1,\"tag\":\"h1\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"We have long considered Anthropic the model company with the strongest product capabilities.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"OpenAI has left countless products unfinished, while Anthropic has had almost no clearly failed product lines. Since ChatGPT, many of the most important product paradigms in AI—including Claude Code, Cowork, Skills, and MCP—have been led by Anthropic.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"This track record is supported by a clear product methodology, which is worth examining in more detail.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Compared with OpenAI, Anthropic places particular emphasis on two things. The development of Claude Tag reflects both of them.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"1. Dogfooding\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Anthropic’s product organization is divided into two groups.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The \",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Product Team\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" continues to improve mature products such as Claude Code and Cowork.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Labs\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" explores zero-to-one products at the frontier. Its work broadly follows two directions:\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":null,\"format\":\"\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Close the Gap:\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" Reduce the gap between what Claude can theoretically do and how most people use it in daily life. Cowork emerged from this line of work.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":1,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":null,\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":null,\"format\":\"\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Advanced Scout:\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" Identify tasks the model performs poorly today but may suddenly perform well six months from now. The team builds the product in advance and waits for the model capability to mature.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":1,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":null,\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"}],\"direction\":null,\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":null,\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Because Anthropic builds coding and office products, its own employees are the first real users of almost every prototype.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The company operates like a large experimental field. Labs plants many seeds around different technical theses and places them inside Anthropic’s real working environment. Some quickly die because demand is weak. Others become dormant because the season for the model capability has not arrived. Only a very small number take root through repeated dogfooding.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"A product is considered for external release only after it achieves strong weekly activity and retention among its internal target users. Anthropic is said to be running hundreds of prototypes at once, most of which will never be released.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag began as one of those internal experiments. It went through months of real use and repeated refinement. It changed Anthropic’s own way of working before the company released it publicly in June.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"2. Building for the Future\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Anthropic prefers to find a product container broad enough to keep benefiting as the model improves.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Claude Code is the classic example. Early on, some people inside Anthropic proposed a Cursor-style autocomplete product. Leadership believed the ceiling of that form was too low and chose to bet on a complete coding agent instead. Claude Code attracted little attention when it first launched. It became a breakout product only after model capability caught up a year later.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Currently, the question Anthropic regularly asks: if Claude 8 already existed, how would people use it? What should we build now to be ready?\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag is designed as this kind of expandable container. As models improve, its value unfolds in three layers.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Layer 1: Context interface.\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" The importance of the context layer can’t be overstated. As models get smarter, the binding constraint shifts from intelligence to context completeness. Instead of having humans curate and compress context for the model, let the model live inside the raw context.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Layer 2: True digital employee.\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" An agent with persistent memory, proactive initiative, and the ability to own complete projects independently.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Layer 3: AI firm OS.\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" Tag becomes the company’s shared brain, accumulating organizational knowledge and capability. Anthropic is already seeing early signs of this internally.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The deepest long-term impact of AI may not be individual productivity but collective intelligence. Humans can divide labor, but they can’t merge minds. Meetings, documents, and status reports are tools invented to approximate collective cognition. They’re slow, low-bandwidth, and bleed enormous amounts of tacit knowledge. Tag can fork easily and merge easily. Different copies explore in parallel, then recombine everything they learned. AI-augmented organizations could learn, scale, and self-improve at speeds far beyond what’s possible today.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"05 Can Claude Tag Break Out Quickly?\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"heading\",\"version\":1,\"textFormat\":1,\"tag\":\"h1\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The next question is how quickly Claude Tag can spread through enterprises.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The market ran a preview earlier this year. \",\"type\":\"text\",\"version\":1},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Viktor\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"link\",\"version\":1,\"rel\":null,\"target\":\"_blank\",\"title\":null,\"url\":\"https://viktor.com/\"},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\", a startup with a nearly identical product (a shared AI coworker inside Slack/Teams, freely switchable models), posted a remarkable growth curve. It launched in February, hit $15M run-rate within about 10 weeks, signed 12,000+ enterprise installs and 2,000+ paying customers. That growth rate matches the early trajectories of Lovable and Manus, roughly the fastest enterprise adoption curves on record. Slack’s two co-founders, Stewart Butterfield and Cal Henderson, were \",\"type\":\"text\",\"version\":1},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"among the investors\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"link\",\"version\":1,\"rel\":null,\"target\":\"_blank\",\"title\":null,\"url\":\"https://fortune.com/2026/05/19/viktor-ai-startup-raises-75-million-for-virtual-coworker-exclusive/\"},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\".\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"That sounds promising for Tag. But conversations with several founders building in this space suggest a more nuanced picture. These products have found product-market fit primarily in small tech companies. Viktor’s customers are mostly under 25 people. Broader enterprise adoption will move slower than the early numbers suggest.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Model capability isn’t the bottleneck. Opus 4.6 is sufficient to unlock this form factor. Two barriers remain.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"(1) Cost.\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" This is the biggest problem. A 20-person company that fully adopts Claude Tag could burn tens of thousands of dollars a month.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The per-query costs can be startling. On Opus 4.8, a single research question about how to access a company website cost around $4. A deep-research task collecting user case studies ran about $14. At scale, the math currently works only for high-value roles in high-margin industries.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The fundamental cost driver is low cache hit rates. In group chat, Tag constantly ingests large amounts of context. One-on-one conversations maintain a continuous thread where cache stays warm. Multiplayer collaboration is inherently asynchronous: one person starts a task in the morning, another picks it up after lunch, and the cache has already expired. Multiple users sharing one agent with different permissions and context make cache structures fundamentally different from single-user patterns.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Connectors make this worse. An enterprise agent might integrate with a hundred different SaaS tools across legal, finance, and engineering. More tools means the agent spends more time searching its tool inventory, more retries on wrong selections, and the tool descriptions themselves eat significant context window. Every factor compounds.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"(2) Security and permissions.\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" For Tag to deliver value, it needs broad access to company context and system permissions. The product doesn’t yet have a bulletproof answer for permission management.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Only Fable 5/Opus 5 class models can provide reasonably reliable security isolation under system prompt constraints, making jailbreaks genuinely difficult. The dynamic is similar to autonomous driving: for enterprise permission systems, 99% reliability isn’t enough. The remaining 1% determines whether the product can actually deploy.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Small tech companies with flat organizations and simple permission structures can adopt aggressively. Most mainstream enterprise customers can’t accept the risk yet.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"We reviewed online feedback about Claude Tag from the previous month and found a consistent pattern. Users were broadly satisfied with the quality of the work. The real problems were that they could not afford unrestricted use and did not feel comfortable granting full authority. Some complained about cost; others worried about data security and lock-in.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"One comment captured the concern:\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"“Claude Tag is like giving Anthropic your entire company, then renting it back from them.”\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"06 Further Reflections\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"heading\",\"version\":1,\"textFormat\":1,\"tag\":\"h1\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Claude Tag Could Open the Next Product Paradigm\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"AI products have broadly moved through three stages:\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Chat → Coding Agent (synchronous local agent) → AI Coworker (asynchronous remote agent)\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":1,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Chat answers questions. Claude Code executes tasks. Claude Tag goes further into the organization, collaborates with multiple people, discovers problems proactively, and takes over complete workflows.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Each transition could be an order of magnitude larger than the one before it.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Chat serves information and content markets, where willingness to pay is lowest. Coding turned AI into a real production tool, raising user ARPU by dozens of times and opening a market worth hundreds of billions of dollars. The coworker layer brings AI into the full range of white-collar work. ARPU for any single white-collar employee may be lower than for a programmer, but the number of users and the total task volume are much larger. The addressable market could reach several trillion dollars.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Slack is only Tag’s first stop. A Teams version is expected, with a waiting list already open. In the future, Anthropic could build native integrations with Zoom, email, and project-management tools, placing Tag inside every company workflow and gradually connecting the organization’s memory.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag could also eventually connect with employees’ individual Claude accounts in the enterprise environment. At that point, when an employee works in Claude Code, the Claude on the other side would understand not only the individual’s background but also the company’s context. It would be both a shared teammate and each employee’s personal digital double.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Claude Tag Could Help Anthropic Accumulate Enterprise Data\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Several data experts we spoke with made the same point: after coding, more value will concentrate in the long tail of real enterprise data. This is the next major hill to climb.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Claude Tag is a strong vehicle for gathering that data. Its logic resembles Cursor’s: reduce the barrier to use as far as possible, in this case to a simple mention, then use real workflows to surface high-quality data.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The agent trajectories are particularly valuable. They are long, contain full context, and include outcome feedback. In principle, they reveal how thousands of companies actually work.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"There is an important limitation. Under Anthropic’s commercial terms, customer inputs and outputs are \",\"type\":\"text\",\"version\":1},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"not used for model training by default\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"link\",\"version\":1,\"rel\":null,\"target\":\"_blank\",\"title\":null,\"url\":\"https://privacy.anthropic.com/en/articles/7996868-is-my-data-used-for-model-training\"},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\". Anthropic can still improve its models in several ways:\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"It can observe anonymized, aggregated patterns, such as which tasks are growing fastest and which workflows fail most often, then use those patterns to design evaluations or synthetic data.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"When an employee voluntarily submits a rating or feedback, the related data may be eligible for training, although enterprise administrators can disable that permission.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Anthropic operates an optional \",\"type\":\"text\",\"version\":1},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Development Partner Program\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"link\",\"version\":1,\"rel\":null,\"target\":\"_blank\",\"title\":null,\"url\":\"https://support.anthropic.com/en/articles/11174108-about-the-development-partner-program\"},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" through which companies can voluntarily share raw Claude Code data, historically with incentives such as token discounts. A similar mechanism could eventually extend to Claude Tag.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"There’s a defensive angle too. With Tag, the entire agent execution trace lives in Anthropic’s cloud. External parties see the finished result, not the intermediate reasoning, tool calls, and recovery steps that make trajectories so valuable for training. Open-source models are cut off from this signal. Anthropic’s supply grows richer. The structural gap between open and closed may widen accordingly.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Tag-Like Products Could Create Moats for Model Companies\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The moat may not come from how much company information the model remembers, because memory can be exported. More important is that Claude Tag gradually holds part of the company’s running state.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Inside Anthropic, for example, Boris is said to run hundreds of Tag tasks simultaneously. Many are long-running. Each has different permissions, data sources, and dependencies on other tasks. Some are waiting for a customer response. Others are waiting for an experiment to reach a launch threshold. Still others are tracking an unfinished pull request or ticket.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Changing model providers would be like replacing a large group of employees who are already in the middle of their work. The migration could lose a commitment, or the new agent could behave unpredictably in a critical situation. The switching cost is no longer as low as it is for ChatGPT or Claude Code.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"This is why Tag-like products matters so much to a model company.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Model-layer competition is increasingly deadlocked. Training costs per generation keep climbing while commercial life cycles keep shrinking. Anthropic and OpenAI struggle to open lasting daylight between each other, and open-source models trail by perhaps three months. Even when a new generation briefly leads, the real monetization window may last only two months.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"As intelligence becomes cheaper more quickly, model companies need stickier products. They need to use a limited capability lead to turn intelligence into switching costs.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"But Who Ultimately Owns the Moat?\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Four groups are competing to control the AI coworker, and each holds a different advantage.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"type\":\"image\",\"version\":1,\"hash\":\"02e7423e47774c1a55561db6f9fca3032ed79d1c\",\"src\":\"https://s3-alpha-sig.figma.com/img/02e7/423e/47774c1a55561db6f9fca3032ed79d1c?Expires=1788134400\u0026Key-Pair-Id=APKAQ4GOSFWCW27IBOMQ\u0026Signature=QhHv~~GU-0k9DBuuBOa22I2nHLG1zFJZ9-AUHk2jjMRic7fE4zBxHSxfIAM8FxOGE7QWLoOVGjT4O3upC52Lg7jESkPQM3bDH53vl8Y9i9gj6vowUCjvd0AA-afW8J5JYwl3jZNY31Pz1RNy92cFw50hbT2lRFeBLVhUSXLpRUHzmhxY1KAC-QMsnSyfWt2dUIguGuS~q~9HaanCa4lCwAP0b~TK0L14na8Mm6RBZeUXTi0bSgQ-JYKzJX8zLoc~Xxjuwuph-fSxGVwg2g0s9ywKpZAi8bQaHKcHoUhHNNyIej33F-QIdJzS~D72mYCV4AD0PoZDUZ~L2iLnQNPKnw__\",\"altText\":\"\",\"originalImageWidth\":1500,\"originalImageHeight\":1989,\"isFillWidth\":false}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Among these players，the model layer may have a larger opportunity.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"First, the cost gap is stark. Conservatively assuming 80% gross margins on Anthropic’s API, third-party callers pay roughly 5x what Anthropic spends on its own compute.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Second, context is fragmented across Slack, Salesforce, Zoom, Notion, and dozens of other tools, each holding a different slice of organizational knowledge. Model companies can turn this fragmentation into an advantage by connecting all of them, unifying memory across silos, and positioning themselves as the cross-application cognitive layer.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"And if the AI Coworker form factor proves important enough, model companies like Anthropic could eventually deprioritize API revenue in favor of their own products. Several levers are available:\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Ship the latest models on Tag first. Security provides a ready justification: Anthropic controls the runtime, sandbox, identity, logging, and tooling inside Tag, whereas API customers’ downstream usage is uncontrolled.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Subsidize Tag while keeping API prices high. Early signs are already visible: Enterprise Tag trials come with $25,000 in credits, Team plans with $2,500 (minimum 10 seats).\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Allocate higher thinking budgets to Tag users on the same model.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Anthropic’s ARR Could Reaccelerate\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Claude Tag adds a new growth mechanism on top of Claude Code.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Faster diffusion.\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" Tag is far more accessible than Claude Code. It lives in group chat. One person configures it, the entire company uses it. Users report that companies start by adding Tag to one channel, then it organically spreads to every channel. Everyone, including external collaborators, watches how the most skilled AI users work, and effective workflows propagate without formal training programs.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"type\":\"image\",\"version\":1,\"hash\":\"62dbc7486aa982696ae9301e2faaf7aed4d16052\",\"src\":\"https://s3-alpha-sig.figma.com/img/62db/c748/6aa982696ae9301e2faaf7aed4d16052?Expires=1788134400\u0026Key-Pair-Id=APKAQ4GOSFWCW27IBOMQ\u0026Signature=JFlIaqVk9gdu-GHFecDClfin7rxjt4c7EGV03nYBtcfgwm7Lyjsu7QUUMb44CIMaeJkSuN~zvJh0fyQylq9BW3ZTBy9L-H-K5skCP90KBIIo0~UVFitI-YeU25m2oo2utZfz6zkL6h-mPnTJYHQY6trBhE0J7r2EAbM29M6HWtnbq9TbVnzajTxd7hZEKuuXWJycSky6y3ANpxnbkfS~zExczw7LM3YBwP3awCl3zaqv9uoM4P1T0u8C-XO2Jn-25RgaVjTOvuKZJxRI0Vmdm2oEDYNqc8xNTJUrTGHLpAvMGN4sCfcTuMprG6htL1kbGfY0neZyhx1EIExJb5ChLA__\",\"altText\":\"\",\"originalImageWidth\":1536,\"originalImageHeight\":1024,\"isFillWidth\":false}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Autonomous token consumption.\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" Previously, token usage scaled with human initiation frequency. Now Tag handles scheduled tasks, long-running projects, and proactively finds new work. It generates sustained, autonomous compute demand.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"children\":[{\"detail\":0,\"format\":1,\"mode\":\"normal\",\"style\":\"\",\"text\":\"From software budget to headcount budget.\",\"type\":\"text\",\"version\":1},{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\" For enterprises, Claude Code is primarily a productivity tool, so spending is evaluated against a software budget. Tag can begin to replace the work of actual employees. Anthropic’s internal thinking about Tag pricing reportedly compares it directly with human compensation. If a role costs $100,000 a year and Tag can perform the same work for only a few tens of thousands of dollars, the enterprise has a strong incentive to switch.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"listitem\",\"version\":1,\"textFormat\":1,\"value\":1}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"list\",\"version\":1,\"textFormat\":1,\"listType\":\"bullet\",\"start\":1,\"tag\":\"ul\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"All three compound. Claude Tag could become Anthropic’s second growth curve.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"It could also be the most important proof point the AI CapEx cycle has left to deliver. AI hardware stocks just saw a historic pullback. Proving “fundamentals are fine” no longer moves the needle. The market wants a visible step-change before it re-prices AI’s commercial upside.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Last year the step-change was RL and post-training. This year it was coding. Next in line: a breakout in knowledge work. The Coworker category, led by Tag, is the most likely catalyst.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"Judging from sentiment and usage inside Anthropic, the company believes AI products have reached another clear paradigm-shift point. Mythos’s capability jump plus Tag’s form factor shift has made the AI Coworker real, not conceptual. The leap feels comparable to Opus 4.5 maturing alongside the Claude Code harness. Cost and permissions still block mass adoption, but the product works.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"},{\"children\":[{\"detail\":0,\"format\":0,\"mode\":\"normal\",\"style\":\"\",\"text\":\"The question worth watching is whether, at some future point, it will take off as quickly as Claude Code did earlier this year.\",\"type\":\"text\",\"version\":1}],\"direction\":\"ltr\",\"format\":\"start\",\"indent\":0,\"type\":\"paragraph\",\"version\":1,\"textFormat\":0,\"textStyle\":\"\"}],\"direction\":\"ltr\",\"format\":\"\",\"indent\":0,\"type\":\"root\",\"version\":1,\"textFormat\":1}}","itemId":"b5bb1a96-7690-427f-ae92-b2b434675642","fieldSchemaId":"3fcb25bf-f8b6-47c4-84d6-226369594160"}]}}}},"slugByItemId":{"7b886fb4-c171-49aa-877e-475cf8b97f18":"how-openai-could-turn-the-tables","598cfcc0-365f-40c6-9f63-6631c6f5a6ff":"will-chinese-ai-leap-ahead-or-follow","91e6e6f8-7396-4490-b421-e7e2ff664063":"rl-scaling-from-research-trick-to","d285731a-bce6-45c3-9dac-26edd7829535":"pulse-how-openai-starts-outrunning","b5bb1a96-7690-427f-ae92-b2b434675642":"claude-tag-is-underrated","d495e0e3-e929-4163-9d3e-0fec19ef9c2c":"beyond-deepseek-what-chinas-model","5ea3ff6e-b7d9-440c-aa76-6f6ce74c432a":"our-investment-in-convex-the-backend-where-agents-build","deb68f7b-2d3f-40b3-bbe5-ca239d245f27":"our-investment-in-generalist-a-brain-for-many-bodies","a54b6460-7b13-40d1-b52f-59d326989a10":"openclaw-is-the-signal-our-thesis-on-long-horzion-agents","61387d11-a584-4b82-b223-7fd449542135":"the-ai-bubble-reckoning-1999-all","f650e52a-191a-4241-a8b4-12705cb62385":"ai-for-life-science-landscape","3db0c5d9-c44c-4950-a175-45c033132ebe":"ai-coding-landscape-how-agents-disrupt","c4aeef83-34d4-411e-b40c-b432dd225928":"continual-learning-next-paradigm","e632f659-8b25-4ec8-8c28-2032c89b4fab":"our-investment-in-phylo-building-the-intelligence-layer-for-biology","809bd036-e216-4bdb-ae70-dbd1d65b4804":"fable-5-expensive-intelligence-needs-expensive-work","c23fe0ec-cf33-40e2-b090-b73d06099e9a":"generalist-and-the-270000-hour-advantage","80ff4031-030f-4caf-b7a9-1825fd8cb70f":"agi-2026-are-we-the-final-white-collar","940cd5e4-2e54-4b7a-941f-c0ea4e37df50":"beyond-the-cloud-are-llms-the-new","0c9ed8bc-cb92-4008-9f50-15867c8349d3":"our-thoughts-on-llm-part-one","fb158125-2004-4c70-972d-88d6846176ab":"decode-the-buzzword-why-harness-engineering-matters-now","cd412711-7095-43ca-8389-8011dab2f900":"inventing-anthropic-two-ingredients-behind-the-ai-winner"}}