Anthropic's Latest Report Reveals Global Workers' Patterns: Seeking Sleep at 5 AM, Asking for Recipes at 6 PM

marsbitPublished on 2026-06-29Last updated on 2026-06-29

Abstract

A new report from Anthropic analyzes millions of hourly user interactions with Claude AI, revealing detailed patterns in daily life and work. The data shows distinct rhythms: people most frequently ask about sleep help around 5 AM, seek news at 7 AM, and search for dinner recipes at 6 PM—the day's single largest query spike. Usage sharply diverges between weekdays and weekends. Workdays are dominated by professional tasks like business emails and coding (backend, APIs). Weekends see a surge in personal use—nearly 50% of conversations—focused on emotional support, creative writing (especially fan fiction), medical advice, and side projects like AI agent design or game development. Weekend "entrepreneurial" queries peak globally, while job-hunting activity drops. The report introduces "artifact" analysis, finding 93% of conversations produce a tangible output (explanation, document, code, etc.). Blog posts are 81% work-related, while creative writing is over 80% personal. High-wage professionals (e.g., marketing managers, programmers) use Claude more intensively outside work hours, with longer conversations, more tokens consumed, and greater use of deep thinking features compared to lower-wage roles. Interestingly, Claude's responses typically register at a higher reading level than user prompts (by about one educational year on average), except for audience-focused writing like emails or blogs where the gap nearly disappears. The data also captures specific cultural moments...

Did you know?

At 5 a.m., the most common question people ask AI is how to fall asleep.

At 7 a.m., it's what major events happened in the world.

At 6 p.m., it's what to cook for dinner.

Just last night, Anthropic released the sixth report in its economic index series—for the first time, increasing the sampling precision of millions of Claude conversations from weekly to hourly!

What time you feel anxious, when you crave food, and when you can't sleep—it's all in the data.

AI knows your daily routine better than your partner.

AI Knows When You're Anxious or Craving Better Than Your Partner

First, there's the distinction between weekdays and weekends.

Monday to Friday: Business emails, PowerPoint presentations, marketing copy.

Saturday and Sunday: Emotional support, medical questions, investment advice.

In Claude conversations, the proportion of personal use remains stable at around 35% on weekdays. But on weekends, it jumps to nearly 50%.

The usage of Claude Code also changes accordingly. Backend architecture, API debugging, and data storage all decline over the weekend, replaced by AI Agent design, quantitative trading, and game development.

The same group of people: working for five days, being themselves for two.

However, this "being themselves" isn't all about relaxing.

Entrepreneurship-related conversations peak across all countries on weekends, but job-seeking activities drop along with other work tasks.

Weekends are for dreaming of being a boss, not for submitting resumes.

Then, there's the 24-hour cycle of a day.

Anthropic plotted the frequency of different conversation categories by hour, creating what can be called an electrocardiogram of human life rhythm—

7 a.m.: News. 10-11 a.m.: A small peak for email writing. 6 p.m.: Recipe searches, the largest single-category spike of the day. Evening: Concentrated requests for TV show recommendations. Around 5 a.m.: The insomniacs arrive.

In contrast, gardening topics remain almost completely flat from sunrise to sunset.

Anthropic couldn't resist adding a pun in the report, calling gardening a "perennial topic of interest"—both "consistently popular" and referring to "perennial plants."

The post-work and weekend data also hides another layer of information: The work tasks Claude handles are clearly skewed towards higher-paying professions.

Conversations for low-wage positions like secretaries and telemarketers decline after hours, but the proportion for high-wage positions like marketing managers and programmers actually increases.

High-income workers have no off-hours. This isn't a new conclusion, but now it's backed by hourly data.

Of course, the most dramatic data point is Tax Day.

On April 14th, tax-related conversations were 8 times the daily average in May. They remained high on April 15th. On April 16th, they plummeted.

The American public collectively rushed to AI for tax help the day before the deadline, then scattered faster than anyone once it passed.

Creating PowerPoints by Day, Fan Fiction by Night

In this report, Anthropic also introduced a new analytical dimension: artifact.

The thing you take away after a conversation with Claude—a document, a piece of code, an explanation, an email—counts as an artifact.

93% of conversations produced an artifact. Only 7% were pure chat, leaving nothing behind.

The top three categories were: Explanations (17%), Documents & Reports (15%), and Guidance & Advice (11%).

Overall, conversational outputs and written deliverables each account for about one-third, while code and technical work make up one-sixth.

After categorization, Anthropic asked a follow-up question: Are these outputs for work or for life?

The answer varies by category.

Blogs and articles: 81% are for work.

Creative writing is the exact opposite: Over 80% are for personal use, mainly fan fiction, world-building, and poetry. Of the remaining work scenarios, 13% are for short video scripts and speeches.

Translation is the most "neutral," with 42% for work and 44% for personal use. Planning is similar: 44% for work (startup strategy, content strategy), 49% for personal use (travel itineraries, fitness plans).

By day, it's a productivity engine. By night, it's a life assistant.

The Higher the Pay, the Harder AI Works

More interesting is the relationship between token consumption and salary.

Anthropic matched each conversation to the most relevant occupation and then compared it to the median wage for that profession.

Thus, a pattern emerged: Conversations for high-salary professions consume more tokens.

Conversations associated with Marketing Managers ($80/hour) use about 2.5 times the tokens of those for Editors ($37/hour).

A conversation to build a website consumes over 3 times the median token count. An explanation uses only one-fifth of the median.

And high-income users don't simply "throw tasks at AI."

They output more per turn (1.34x), have more interaction turns (1.53x), and use the deep thinking feature more frequently (34% vs. 31%).

Claude isn't slacking, and neither are the people using it.

Of course, Claude not only works more but also works "higher."

Its responses generally have a higher reading level than user prompts, averaging about one year more of education.

The largest gaps are in Images & Graphics (+2.6 years), Games (+1.9 years), and Websites/Apps (+1.7 years).

But for audience-facing writing, the gap almost disappears: Blogs (-0.1 years), Academic Papers (+0.0 years), Emails (+0.3 years).

The reason is that prompts for such tasks often include text samples at the same level as the desired output. If you ask it to help write an email, you've likely already drafted a version yourself, so the reading levels are similar.

A Diary You Never Intended to Write

This so-called "rhythm" is simply you opening a dialog box every day, asking a few questions, and taking what you need.

But when these conversations are sliced hourly, outputs are divided into over 30 categories, and each interaction is matched to an occupation and salary bracket, the fragments form a picture.

Insomnia at 5 a.m., dinner anxiety at 6 p.m., sudden entrepreneurial thoughts on weekends, and emotional lows flooding in late at night.

Viewed individually, these are just hundreds of unrelated questions. But strung together, they become a person's schedule, emotional cycles, and days.

You might not have fully shared these things with people around you. But you've entrusted them all to a dialog box.

93% of conversations produced something. Conversely, 93% of conversations also left a trace of you.

Anthropic says this report aims to see how AI integrates into economic life. But once data becomes precise to the hour, what it reflects is more than just economics.

By day, Claude is your work buddy. At 5 a.m., only it knows you're still awake.

References:

https://x.com/AnthropicAI/status/2070528961235575278

https://www.anthropic.com/research/economic-index-june-2026-report

This article is from the WeChat public account "新智元" (New Zhiyuan), author: ASI启示录 (ASI Apocalypse)

Trending Cryptos

Related Questions

QAccording to the Anthropic report, what are the most common questions people ask AI at 5 AM, 7 AM, and 6 PM?

AAccording to the Anthropic report, at 5 AM, people most commonly ask AI for help with how to fall asleep. At 7 AM, they ask about major world news events. At 6 PM, the most common question is about what to cook for dinner.

QHow does Claude's usage differ between weekdays and weekends?

AOn weekdays, usage is dominated by work-related tasks such as business emails, PPTs, and marketing copy, with personal use accounting for about 35% of conversations. On weekends, personal use jumps to nearly 50%, focusing on emotional support, medical questions, and investment advice. Interestingly, weekend entrepreneurial conversations peak, while job-hunting activities decline.

QWhat does the report reveal about the relationship between profession/task complexity and AI interaction?

AThe report shows a correlation between higher-income professions and more complex AI interactions. Conversations related to high-paying jobs like marketing managers and programmers involve higher token consumption, more user input per round, and greater use of features like deep thinking. In contrast, lower-paying jobs have simpler interactions with lower resource usage.

QWhat are the three most common types of 'artifacts' or outputs produced from conversations with Claude?

AThe three most common types of 'artifacts' produced from conversations with Claude are: explanations (17%), documents and reports (15%), and guidance/advice (11%).

QWhat does the Anthropic report suggest about how AI usage reflects people's daily lives beyond just economic activity?

AThe report suggests that by analyzing hourly data, AI usage patterns reveal the daily rhythms, personal anxieties, and emotional cycles of users. It captures moments like 5 AM insomnia and 6 PM dinner anxiety, creating an unintentional diary of a person's life and well-being, not just their economic activities.

Related Reads

Shanghai's $10 Billion Unicorn Is About to Go Public

Shanghai-based automotive-grade millimeter-wave radar chip unicorn Calterah Microelectronics Technology (Shanghai) Co., Ltd. has filed for an IPO on Shanghai's STAR Market, aiming to raise 3.49 billion yuan. Founded in 2014 by Chen Jiashu, a UC Berkeley PhD graduate, and his professor Ali Niknejad, Calterah pioneered CMOS technology for 77GHz radar chips, breaking the decades-long monopoly of international giants like Texas Instruments. Its low-cost, highly integrated solutions enabled millimeter-wave radar to move from luxury to mass-market vehicles. By 2025, Calterah captured a 31.1% share in China's automotive millimeter-wave radar chip market (second domestically, fourth globally), with cumulative shipments exceeding 30 million units. Its client list includes BYD, Geely, Nio, and Volvo. The company has undergone 11 funding rounds, attracting high-profile investors such as the National Integrated Circuit Industry Investment Fund Phase II, China Capital Management, and GD Capital. Its valuation has reached tens of billions of yuan, with a projected post-IPO valuation of approximately 14 billion yuan. Despite rapid revenue growth—increasing from 206 million yuan in 2023 to 632 million yuan in 2025 with a 75.28% CAGR—Calterah remains unprofitable. It reported net losses of 323 million yuan, 334 million yuan, and 193 million yuan from 2023 to 2025, accumulating over 900 million yuan in losses over three and a half years. These losses are primarily attributed to heavy R&D investment, which totaled over 1.039 billion yuan in the reporting period, often exceeding annual revenue. The company faces significant risks, including high customer concentration (its top five customers accounted for over 99% of revenue from 2023-2025, with BYD alone representing over 50% in 2025) and supply chain concentration. Revenue pressure from key customers and dependencies on overseas suppliers for EDA tools and IP pose challenges to sustainable growth. The IPO is seen as crucial for securing capital to expand production, diversify its customer base, and reduce supply chain dependencies.

marsbit29m ago

Shanghai's $10 Billion Unicorn Is About to Go Public

marsbit29m ago

Ray Dalio's Latest Macro Analysis Full Text: Buy More Gold, Add Some Bitcoin

In his latest macro analysis, Ray Dalio applies his framework from "How Countries Go Broke: The Big Cycle" to the current global debt environment. He highlights recent events like Japan selling U.S. Treasuries and rising U.S. long-term yields as signs of an unsustainable debt dynamic. Dalio explains that excessive government debt leads to either unacceptably high interest rates, severe economic downturns, or significant currency debasement through central bank money printing. He summarizes the U.S. fiscal situation: with $5.5 trillion in revenue, $7.5 trillion in spending, a $2 trillion deficit, and total debt at six times annual revenue, debt servicing costs are immense. Without correction, U.S. debt could reach $55-$60 trillion in a decade. Dalio proposes a "3% Three-Way" solution: reducing the budget deficit to 3% of GDP through balanced spending cuts, tax increases, and interest rate reductions to avoid a traumatic adjustment. In response to FAQs, he argues that the risk of a U.S. debt crisis is high and could materialize within a few years if the current path continues. He dismisses the notion that the dollar's reserve status makes the U.S. immune, citing historical precedents of reserve currency declines. He is also unconvinced by Japan's high-debt stability, noting poor returns for yen-denominated assets. For investors, Dalio recommends diversifying globally, underweighting bonds, and overweighting assets like gold and a small allocation to Bitcoin (around 10-15% to gold) to hedge against currency debasement and poor debt returns.

marsbit1h ago

Ray Dalio's Latest Macro Analysis Full Text: Buy More Gold, Add Some Bitcoin

marsbit1h ago

Stripe’s 16-Year Chronicle: From 7 Lines of Code to a $100 Billion Valuation

Stripe's 16-year journey began with a simple promise: "7 lines of code to accept payments." Founded by Patrick and John Collison, the company started by hiding the complexity of bank integrations and merchant accounts behind a clean API, initially targeting developers at startups. This early focus on user experience and technical simplicity fueled rapid adoption. A key early milestone was establishing vital bank partnerships, a challenge overcome by hiring Billy Alvarado, who brought crucial institutional relationship skills. From this foundation, Stripe systematically expanded its product boundaries. It launched Connect for platform payments, Atlas for company formation, Radar for fraud prevention, and Billing for subscriptions. This transformed Stripe from a payment processor into a broader financial infrastructure suite for internet businesses. The COVID-19 pandemic accelerated growth but also led to over-hiring. A 14% layoff in 2022 marked a period of organizational correction. Subsequently, Stripe shifted its growth strategy towards strategic acquisitions to enter new domains quickly. It acquired Bridge (stablecoin infrastructure), Privy (wallet infrastructure), Metronome (usage-based billing), and agreed to buy OpenRouter (AI model routing). These moves signal Stripe's ambition to build a "programmable money system" for the emerging AI and agent-based economy, managing not just currency flows but also the measurement and pricing of computational resources like AI tokens. Internally, Stripe leverages AI agents (like "Minions") to boost engineering productivity. Despite scaling to nearly 8,000 employees and processing $1.9 trillion in payment volume annually, the company remains private. A recent employee tender offer valued it at $159 billion. The core question for Stripe's future is whether it can successfully integrate its expanding product matrix—spanning payments, crypto, and AI infrastructure—into a cohesive platform, positioning itself as the foundational economic layer for autonomous software agents.

marsbit1h ago

Stripe’s 16-Year Chronicle: From 7 Lines of Code to a $100 Billion Valuation

marsbit1h ago

Treasury Secretary's Move to Suppress Treasury Yields Ignites 'Currency Debasement Trade'! Gold Hits Three-Month High, Bitcoin Surges Over 25% in a Single Week

US Treasury Secretary Besant's efforts to lower long-term Treasury yields by announcing expanded buybacks had only a brief market impact. However, this move fueled a "currency devaluation trade," weakening the US dollar while boosting both gold (to a three-month high) and Bitcoin (up over 25% for the week). Analysts attribute this reaction to deepening market concerns over the massive US fiscal deficit and structural pressures keeping long-term rates elevated, including fierce competition for capital from global government borrowing and massive AI sector financing. Despite the Treasury's actions, fundamental forces like growth, inflation, and capital demand are seen as limiting its ability to sustainably suppress yields. Bitcoin's strong positive correlation with gold has reinforced its narrative as a hedge against devaluation. While equity markets have shown resilience, some strategists warn that Treasury yields nearing 5% increase pressure on the dollar and high-leverage assets. Figures like Ray Dalio have advised reducing bond exposure in favor of gold and some Bitcoin, citing US debt risks. Market opinions are divided on the sustainability of the devaluation trade, with some noting the lack of a near-term catalyst for its next leg higher. The underlying tension between the Treasury's desire for lower borrowing costs and the Federal Reserve's focus on inflation and reducing market intervention remains a key theme. Upcoming events like Nvidia's earnings and the Jackson Hole symposium will test whether AI profits can continue supporting stocks and if the Fed aligns more with Washington's preference for easier financial conditions.

华尔街日报3h ago

Treasury Secretary's Move to Suppress Treasury Yields Ignites 'Currency Debasement Trade'! Gold Hits Three-Month High, Bitcoin Surges Over 25% in a Single Week

华尔街日报3h ago

Trading

Spot

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of S (S) are presented below.

活动图片