Just saw this on X. Posting it here verbatim. Credit: Khairallah AL-Awady

Most people download Claude and start typing questions immediately.

Save this :)

They treat it like a chatbot. They get decent answers. They think that is all it does.

Meanwhile a small group of users is running automated workflows, building full applications, delegating entire workdays to Claude, and producing output that looks like it came from a team of five.

The difference is not intelligence. It is not experience. It is not some secret prompting hack.

It is setup.

Claude ships with dozens of features, settings, and capabilities that are either buried in menus, disabled by default, or simply never mentioned anywhere obvious. Most beginners never find them. Most intermediate users only discover half of them.

That ends today.

I went through every corner of Claude - the web app, the desktop app, the API, Claude Code, Cowork, and the entire ecosystem - and pulled out the 40 features that most users have never configured.

Every single one of these will make you faster, sharper, and more productive immediately.

Let's go.

Part 1: Claude Chat Settings (Features 1–12)

These are inside the Claude web and desktop app. Most of them take thirty seconds to set up.

1. Custom Instructions (Your Permanent System Prompt)

Go to Settings and find Custom Instructions. This is a persistent prompt that gets injected into every single conversation you start. Most people leave this blank. That is like hiring someone and never telling them who you are or what you do.

Write your role, your industry, your preferred output format, and your communication style here. Once you do this, every conversation starts with context instead of from zero.

2. Memory

Claude can remember things about you across conversations. Your name. Your projects. Your preferences. Your tools. But it only works if you actively tell it things worth remembering during conversations. Say "remember that I use Next.js and Supabase for all my projects" and it sticks permanently.

Most beginners do not know this exists. They re-explain their entire setup every single session.

3. Projects

Projects let you create a dedicated workspace with its own system prompt and uploaded files. Instead of pasting the same context into every chat, create a project for each major workflow. One for content writing. One for code reviews. One for research. Each one has its own persistent memory and instructions.

This alone changes how productive you are with Claude.

4. Artifacts

When Claude generates code, documents, or visualizations, it can render them in a live preview panel right next to the conversation. Most beginners see code as text in the chat. Artifacts display it as an interactive, runnable, editable output. You can copy, download, or iterate on it directly.

Turn this on. It changes the entire experience.

5. Knowledge Files in Projects

You can upload documents directly into a Claude Project and they become permanent context. Style guides. Brand documents. Product specs. Code documentation. Anything you would normally paste at the start of every conversation can live inside the project permanently.

Most beginners paste the same document into chat fifty times. Upload it once. Never think about it again.

6. Extended Thinking

Claude can reason through complex problems step by step before giving you an answer. Most users get a fast response and assume that is all Claude can do. Extended thinking makes Claude slow down, consider edge cases, explore alternatives, and produce dramatically better output on complex tasks.

Ask Claude to "think step by step" or enable extended thinking in settings and watch the difference on anything that requires real analysis.

7. LaTeX Rendering

If you work with math, science, finance, or anything involving equations and formulas, Claude renders LaTeX natively. Most beginners see raw LaTeX code and think Claude is broken. It is not broken. The rendering is happening. You just need to know it is there.

8. Web Search

Claude can search the web in real time. No more stale training data. No more "as of my last update." If you need current information - stock prices, news, recent events, live documentation - Claude can pull it directly.

Most beginners do not realize this is available and keep getting outdated information without questioning it.

9. Conversation Styles

You can customize how Claude communicates. More concise. More detailed. More casual. More formal. Instead of asking Claude to adjust its tone in every single conversation, set your preferred style once and it applies everywhere.

10. Keyboard Shortcuts

Claude has a full set of keyboard shortcuts that most users never discover. New conversation, toggle sidebar, copy last response, navigate between chats - all available without touching the mouse. If you use Claude daily, these save you real time every single week.

11. Multiple Conversations Running Simultaneously

You can have several conversations open at once in different tabs. One for research. One for writing. One for coding. Most beginners use Claude in one single thread and lose context when they switch topics. Separate your workflows. Keep each conversation focused.

12. Download and Share Artifacts

Every artifact Claude creates can be downloaded as a file or shared via a link. Code, documents, visualizations, interactive apps - all of it is exportable. Most beginners screenshot their outputs or copy-paste manually. Download the actual file instead.

Part 2: Claude Desktop and Cowork (Features 13–22)

This is where Claude stops being a chatbot and starts being an employee.

13. Claude Cowork Tab

Inside Claude Desktop there is a tab called Cowork. This is not chat. This is delegation. You describe the outcome you want and Claude executes it directly on your files. It reads folders, creates documents, organizes data, processes files in bulk - everything happens on your actual computer.

Most beginners never switch from the Chat tab. Cowork is the most underrated feature in the entire product.

14. Folder Access Permissions

When using Cowork, you grant Claude access to specific folders on your machine. Everything runs in a sandboxed environment. You control exactly what Claude can see and touch. Most beginners are either afraid to give any access or do not know they need to configure this.

Set your working folders. Give Claude access. Watch it actually work.

15. Scheduled Tasks

Type /schedule in Cowork and you can set up recurring automated tasks. Daily morning briefings. Weekly report generation. Friday file cleanup. Claude runs them on schedule as long as your desktop app is open.

This is a personal AI assistant running on autopilot. Most users have no idea this exists.

16. Sub-Agents (Parallel Processing)

When Claude gets a complex task in Cowork, it can spin up multiple sub-agents that work simultaneously. Instead of processing ten files one at a time, it runs five agents in parallel and finishes in a fraction of the time.

Most beginners give Claude one task at a time and wait. Give it a batch and let the sub-agents handle it.

17. Slash Commands

Cowork has built-in slash commands for common operations. /schedule, /strategy, /plan-launch, and many more depending on which plugins you have installed. These are pre-built workflows triggered by a single command.

Most users type everything from scratch every time. Slash commands eliminate that.

18. Plugins

Claude has a plugin marketplace with pre-built capability bundles for specific roles. Product management, marketing, finance, legal - each plugin gives Claude a set of specialized workflows and slash commands. Install the ones relevant to your work.

Think of plugins as job training for your AI employee.

19. Connectors (Gmail, Slack, Google Drive, Calendar)

Claude connects directly to your apps. Gmail, Google Calendar, Slack, Google Drive, Notion, OneDrive, SharePoint, Microsoft 365. It can pull data, read emails, check your schedule, and reference your files without you copy-pasting anything.

Most beginners manually paste information from their apps into Claude. Connect them and let Claude pull what it needs.

20. Claude in Chrome

Add the Claude in Chrome extension and Cowork can do browser-based research alongside its file operations. It picks the fastest path - connectors for integrated apps, Chrome for web research, direct file access for local work.

21. File Processing at Scale

Cowork can process entire folders of files at once. Rename every file following a naming convention. Convert formats in bulk. Extract data from a hundred PDFs. Organize thousands of files by type and date.

Most beginners process files one at a time. Give Claude the whole folder.

22. Session History

Every Cowork session is saved with a full history of what Claude did, what files it created or modified, and what decisions it made. You can review any past session and see exactly what happened. If a scheduled task runs while you are away, the full log is waiting for you.

Part 3: Claude Code and Developer Features (Features 23–32)

This is where Claude becomes a programming partner.

23. Claude Code (Terminal-Based AI)

Claude Code runs directly in your terminal. It reads your codebase, writes code, edits files, runs tests, and executes commands - all from the command line. It is not a chat window. It is an AI developer sitting inside your development environment.

Most beginners use the web chat for coding. Claude Code is an entirely different level.

24. Plan Mode (Shift + Tab)

Before Claude Code starts building anything, switch to Plan Mode. In this mode Claude thinks through the architecture, asks clarifying questions, and maps out the approach before writing a single line of code. This prevents the most common mistake beginners make - jumping straight into implementation without a plan.

25. CLAUDE.md

File

Create a file called CLAUDE.md

in your project root. This is a persistent instruction file that Claude Code reads before every session. Your tech stack, coding conventions, folder structure, things to avoid - all of it lives here. Every time you correct Claude twice on the same thing, add it to CLAUDE.md.

This is the single most powerful feature most developers never set up.

26. /compact and /clear Commands

As conversations get longer, Claude's output quality drops because the context window fills up. Use /compact to compress the conversation history into a summary. Use /clear to start fresh while keeping your

CLAUDE.md

instructions.

Fresh context equals better output. Always.

27. Model Switching (Opus vs Sonnet)

Use Opus for planning, architecture, and complex reasoning. Use Sonnet for fast execution and implementation. Most beginners stick to one model for everything. Switching between them based on the task gives you the best of both worlds.

28. Screenshot Feedback

Something looks wrong visually? Take a screenshot, paste it directly into Claude Code with Ctrl+V, and describe the issue. Visual feedback is faster and more precise than trying to describe UI problems in words. Circle the problem area and say "this spacing feels off" or "this button needs to be larger."

29. One Conversation Per Feature

Never build authentication, then refactor the database, then redesign the UI in the same conversation. Claude's context gets messy and quality drops. Start a new conversation for each feature. Keep each thread focused on one thing.

30. Git Integration

Claude Code works with Git. It can commit changes, create branches, and even write commit messages. If you are not using version control with Claude Code, you are taking unnecessary risk. Every change should be committed so you can roll back if something breaks.

31. MCP Server Connections

MCP (Model Context Protocol) gives Claude access to external tools and data sources. Connect MCP servers for web search, database access, file processing, browser automation, and hundreds of other capabilities. Each MCP server is a new superpower.

Most beginners use Claude in isolation. MCP connects it to the real world.

32. Context Engineering with .md Files

Beyond

CLAUDE.md

, you can create additional markdown files that give Claude specific knowledge for specific tasks. A

rules.md

for writing style. A

stack.md

for your tech stack. A

personas.md

for your audience profiles. Reference these files in your prompts and Claude follows them perfectly.

Part 4: API and Advanced Settings (Features 33–40)

These are for users ready to go beyond the consumer interface.

33. API Access

Claude has a full API that lets you integrate it into your own applications, scripts, and workflows. Everything you do in the chat you can do programmatically - and more. Get your API key and start building.

34. System Prompts via API

Through the API, you can set system prompts that define Claude's behavior at a level the web interface cannot match. Production applications use this to create highly specialized, consistent AI behavior for specific use cases.

35. Streaming Responses

The API supports streaming, which means Claude's response starts appearing in real time as it generates rather than waiting for the full response. For applications where speed matters, this is essential.

36. Tool Use and Function Calling

Through the API, Claude can call functions you define. It decides when to use a tool, generates the function call, and processes the result. This is what turns Claude from a text generator into an autonomous agent that can take real actions.

37. Temperature Control

Temperature controls how creative or deterministic Claude's responses are. Lower temperature means more predictable, consistent outputs. Higher temperature means more creative, varied responses. Most users never touch this. For production use cases, it matters enormously.

38. Structured Outputs (JSON Mode)

Force Claude to return responses in exact JSON formats that match a schema you define. No more parsing messy text. No more hoping the format is right. Define the structure and Claude matches it perfectly every time.

39. Batch Processing

The API supports batch requests - send multiple prompts at once and get all results back together. If you need to process a hundred documents, analyze a thousand data points, or generate fifty pieces of content, batch processing makes it practical.

40. Evaluation Frameworks

Build automated tests that check whether Claude's outputs meet your standards. Set up expected outputs, run your prompts against them, and measure accuracy automatically. This is what separates someone experimenting with Claude from someone running Claude in production.

The Real Cost of Not Setting These Up

Here is the honest math.

If you are using Claude for an hour a day without these features configured, you are losing roughly two to three hours of potential output every single week. That is over a hundred hours a year spent re-explaining context, manually processing files, copy-pasting between apps, and getting mediocre outputs because Claude does not know who you are or what you need.

Every feature on this list takes minutes to set up. The time they save compounds forever.

The people getting the most out of Claude right now are not smarter than you. They are not more technical than you. They just turned on the features you did not know existed.

Now you know they exist.

The only question left is whether you will actually set them up or keep doing things the hard way.

When you are running a startup on a tight budget, founder burnout and a disappearing runway are your biggest threats. To survive, you have to ruthlessly automate tasks that eat up your time.

Here are 10 lean, highly efficient tools to build into your workflow before you waste capital on massive enterprise software.

1/ Apify

What it does: A cloud platform with thousands of pre-built "Actors" (ready-to-use web scraping and automation scripts).

The Use Case: Instantly scrape Google Maps for B2B leads, track competitor updates, or pull clean website data into Markdown to feed into your AI models—all without writing or maintaining fragile scraping code.

2/ Mailtrap

What it does: A dual-purpose email platform built for development testing (sandbox) and live transactional delivery.

The Use Case: Use the Email Sandbox to safely test your signup and onboarding emails in a staging environment to ensure links and HTML layouts work before emailing real users. Then switch to their high-deliverability API to send live billing alerts.

3/ Koalendar

What it does: A clean, lightweight, friction-free meeting scheduling tool.

The Use Case: Set up dedicated booking pages for sales calls or user interviews with automatic timezone detection and reminders. It gives you a professional calendar link in 5 minutes without the bloat or cost of enterprise schedulers.

4/ OpusClip

What it does: An AI video tool that turns long-form footage into short, vertical social media clips.

The Use Case: Drop a link to a product demo or webinar. The AI automatically crops the video, isolates the best hooks, adds dynamic auto-captions, and generates viral-ready marketing collateral in seconds.

5/ Claude (Anthropic)

What it does: The current gold-standard LLM for complex technical tasks, logical reasoning, and coding.

The Use Case: Feed an entire code repository or complex API documentation into a Project window. Use it to build functional front-end prototypes, write backend scripts, and debug deployment issues without hiring an agency.

6/ Make.com

What it does: A visual workflow automation engine connecting thousands of apps.

The Use Case: Map out multi-step logic workflows—like automatically piping a new Stripe customer into a Slack notification, running their company through data enrichment, and adding them to an onboarding sequence.

7/ Tally.so

What it does: A form builder that handles like a Notion document.

The Use Case: Build clean early-access waitlists, user feedback forms, and onboarding surveys. It offers advanced features like logic jumps, conditional tracking fields, and payment collection on a highly generous free tier.

8/ Perplexity AI

What it does: A live-web conversational search engine that synthesizes information and cites sources.

The Use Case: Replace hours of clicking through SEO-bloated articles during market research. Drop a prompt to map out a competitor's pricing tiers or pull cited industry statistics directly into your pitch decks.

9/ Plausible Analytics

What it does: A lightweight, privacy-first alternative to Google Analytics.

The Use Case: Track your site's referral traffic, top pages, and conversion goals on a simple, one-page dashboard. The script is under 1KB, ensuring it won't slow down your site's SEO or require complex cookie banners.

10/ Carrd

What it does: An ultra-fast, single-page website and landing page builder.

The Use Case: Don't waste weeks building a complex site to validate an idea. Spin up a conversion-focused landing page with a custom domain and an embedded email capture form in less than an hour.

What's your experience with these?

Google is returning to the smart glasses market with a new line of AI-powered audio glasses announced at Google I/O, developed in partnership with Warby Parker and Gentle Monster, designed to work with both Android and iOS devices.

Key Details:

• The glasses are designed to pair with Android and iOS devices and were developed in collaboration with Samsung
• Users can issue verbal commands to the glasses to complete tasks through Google's ecosystem, including Gemini (demo showed ordering coffee by voice)
• The devices will be available later in 2026
• This marks Google's return to smart glasses after the notoriously unsuccessful Google Glass launch years ago
• The smart glasses market has evolved significantly, with major companies like Meta and numerous startups now investing in the space

Why It Matters: Google's re-entry into smart glasses with a focus on voice-activated AI assistance represents a significant shift in how the company is approaching wearable technology in an increasingly competitive market.

Ocean, a new startup founded by former hacker Shay Shwartz, has emerged from stealth mode with $28 million in funding to launch an agentic email security platform designed specifically to counter AI-powered phishing attacks.

Key Details:

• Founder Background: Shay Shwartz, a former teenage hacker turned cybersecurity expert, spent a decade in elite Israeli defense and intelligence roles before co-founding Ocean with CTO Oran Moyal.
• Funding Round: The $28 million raise was led by Lightspeed Venture Partners, with participation from Picture Capital, Cerca Partners, and high-profile angel investors including Wiz co-founder Assaf Rappaport and Armis co-founders Yevgeny Dibrov and Nadir Izrael.
• Technology: Ocean utilizes a tailored small language model to analyze the context of incoming emails, evaluate sender intent, and detect sophisticated, AI-generated impersonation attempts that traditional tools miss.
• Market Gap: While vendors like Proofpoint and Mimecast handle standard phishing, Ocean argues that AI has automated and scaled targeted spear-phishing, requiring a new defensive approach that understands organizational context "like having a guard in every door."
• Current Traction: The platform is currently processing billions of emails monthly for customers including Kayak, Kingston Technology, and Headspace.

Why It Matters: Ocean's launch addresses a critical shift in cybersecurity where AI has democratized sophisticated attacks, moving defense from manual analysis to automated, context-aware AI agents.

Andrej Karpathy announced his departure from his startup, Eureka Labs, and his return to the research frontier by joining Anthropic this week, starting under team lead Nick Joseph.

He will focus on pre-training, the massive, compute-intensive phase of building foundational models, and is tasked with building a new team dedicated to using Claude to speed up this research process.

This hiring signals Anthropic's belief that AI-assisted research is the key to competing with rivals like OpenAI and Google, rather than relying solely on raw compute power.

A veteran of the field, he co-founded OpenAI (2015), led Tesla's Autopilot and Full Self-Driving programs (2017–2022), returned to OpenAI (2023–2024), and most recently founded Eureka Labs to apply AI to education.

Despite the new corporate role, Karpathy stated he remains passionate about education and plans to resume his work on teaching AI, including his popular "Neural Networks: Zero to Hero" course.

Anthropic also recently hired cybersecurity veteran Chris Rohlf to its frontier red team to stress-test models against severe threats.

This is a great list of some of the best official AI guides from OpenAI, Google, and Anthropic.

Credit: Charly Wargnier

1/ 1,302 real-world gen AI use cases from the world's leading organizations by Google

2/ Agents Companion by Kaggle

3/ A practical guide to building agents by OpenAI

4/ Building effective agents by Anthropic

5/ AI in the Enterprise by OpenAI

6/ Prompt Engineering by Google

7/ Prompt engineering overview by Anthropic

8/ Identifying and scaling AI use cases by OpenAI

9/ Prompting Guide 101 by Google

Enjoy!

Will.i.am, the Black Eyed Peas frontman and tech entrepreneur, debuted as a college professor in January 2026, teaching "The Agentic Self," a 16-week artificial intelligence course at Arizona State University where students learn to create their own AI agents.

Key Details:

• Will.i.am (William Adams), 51, experienced significant stage fright before his first class but drew inspiration from the band's 2003 song "Where Is The Love?" to structure his teaching approach around identifying problems, discussing solutions, and reflecting on outcomes
• The course enrolled approximately 80 students, with half attending in person at his custom-built Los Angeles campus lecture hall and half joining remotely from ASU
• Adams has been deeply invested in technology for over two decades, including early investments in OpenAI and Tesla, serving as Intel's director of creative innovation, and recently debuting an AI-equipped electric vehicle called Trinity at CES
• Guest speakers included LinkedIn co-founder Reid Hoffman and executives from major AI companies like Nvidia and OpenAI
• Adams's tech journey began in 2001 after visiting MIT's Media Lab; he made his first major investment around 2006 by converting an $80,000 Hummer sale into Tesla stock and later took a stake in Beats Electronics before Apple's $3 billion acquisition
• He uses analog design methods (scissors, cardboard, tape) to prototype products and believes AI will become increasingly personalized, empowering individuals over tech companies

Why It Matters:

Adams represents a bridge between entertainment and technology innovation, demonstrating how creative thinking and long-term tech investment can culminate in meaningful educational contributions and shaping the next generation of AI developers.

Master's degrees, once a reliable pathway to career advancement, have lost their job-market guarantee as programs have proliferated 69% over two decades while employers increasingly adopt skills-based hiring and question whether advanced degrees are necessary.

Key Details:

• The unemployment rate for workers under 35 with a master's degree has rarely been higher in the past 20 years, now at the 77th percentile of unemployment (where 50th is normal), according to Burning Glass Institute analysis of Bureau of Labor Statistics data.
• By contrast, unemployment for workers under 35 with Ph.D.s, law degrees, or medical degrees has rarely been lower — these professional degrees still function as licenses to practice, while master's degrees are merely signals that lose value when oversupplied.
• Master's degree programs increased 69% to over 33,500 between 2005 and 2021, with even more launching in the past five years, many focused on AI reskilling. New specialties include online M.B.A.s, one-year data science degrees, and healthcare management programs.
• More than 40% of employers surveyed by Drexel University's LeBow College of Business said they had no plans to hire M.B.A.s in 2026, up sharply from 26.8% in 2025.
• Johnny C. Taylor Jr., president of SHRM (the main HR lobbying group), said AI has accelerated employers' shift to skills-first hiring: companies now ask "Can you do it?" rather than requiring credentials. This trend is especially pronounced in the past two to three years.
• Kevin Vado graduated from University of Florida's M.B.A. program after applying for ~200 positions and networking with 80+ alumni, but has received fewer offers than expected and struggles to land interviews despite banking experience at Morgan Stanley and Wells Fargo.
• Amir Zeltzer, who enrolled in Texas A&M's M.B.A. program after a brutal internship search, landed an operations role at Texas Instruments — though he credits the school's intensive career-management resources, not just the degree itself, with securing the position.

Why It Matters: As employers prioritize demonstrated skills over credentials and AI accelerates the devaluation of standardized signals, master's degrees have shifted from a competitive advantage to an expensive credential that may not meaningfully improve job prospects — reversing decades of career-advancement wisdom.

Companies running bug bounty programs are being overwhelmed by low-quality, AI-generated vulnerability reports, forcing some to suspend their schemes entirely.

Key Details:

• Bugcrowd reported a more than fourfold increase in submissions over three weeks in March 2026, with most proving false; Curl suspended its paid bug bounty program in January citing an "explosion in AI slop reports"
• Nextcloud also suspended its program in April due to massive increases in low-quality reports, while HackerOne saw submissions jump 76 percent year-over-year despite the legitimate vulnerability rate remaining steady at 25 percent
• The problem stems from three groups: amateurs using AI tools for the first time, existing researchers misled by AI agents, and experienced developers building automated end-to-end scanning and submission systems
• Companies are responding by implementing stricter background checks and deploying AI agents to triage submissions; HackerOne introduced "agentic validation capabilities" to manage high volumes of findings
• Anthropic's recent launch of Mythos, a cyber AI model designed to find software flaws faster than humans, is expected to accelerate this trend
• Bug bounties have grown significantly since the early 2000s, with Google's program disbursing $17 million in 2025, up from $7.5 million in 2021

Why It Matters:

While AI tools can help experienced security researchers work more efficiently, the flood of automated low-quality submissions is straining the economics of bug bounty programs and forcing companies to rethink how they filter and validate vulnerability reports.

A Montreal-style bagel shop owner in Vermont used AI to edit social media posts and generate product images — only to face backlash from customers who saw through the synthetic content and left one-star reviews, prompting him to apologize and reconsider his approach.

Key Details:

• Adam Jones, owner of Myer's Bagels in Burlington, Vermont, used an AI service designed for small businesses to create and edit Instagram posts, including generating images and captions to promote seasonal offerings like graduation-themed bagels.
• The AI tool imported real photos of the shop's bagels and retail bags but then manipulated them — superimposing images onto backgrounds that didn't match the actual store layout, adding fires and kettles that weren't present, and creating fake handwritten customer testimonials.
• One post took a real customer review from "Sam" and transformed it into a handwritten note displayed in front of a wood fire that wasn't theirs. Another combined a real photo of a baker rolling dough with a superimposed wooden cutting board, fire, and kettle — a setup customers knew wasn't how the shop actually operates.
• Customers quickly noticed the AI edits and expressed frustration in Instagram comments and Google reviews. Multiple people left one-star ratings attacking the use of AI, not the food quality. While a few defended the shop as a small business trying to be creative, negative comments vastly outnumbered supportive ones.
• Jones removed the posts and apologized, framing it as an experiment he was willing to abandon. He emphasized he's "not anti-AI" and plans to continue using it for business operations, HR, accounting, and other functions — but will be much more cautious about social media.
• Jones argues AI is necessary for small businesses to stay competitive and keep prices down, but acknowledges social media requires a different approach: "I need to tread much more carefully."

Why It Matters: The episode illustrates a tension in AI adoption for small businesses — while automation can boost efficiency and affordability, using generative AI to create false or misleading content erodes customer trust faster than it saves time. Authenticity, especially for food businesses built on local loyalty, may matter more than polished AI-generated posts.

A federal judge has delayed final approval of what would be the largest copyright settlement in US history, citing concerns from class members about excessive lawyer compensation and inadequate author payouts.

Key Details:

• Judge Araceli Martinez-Olguin postponed approval after multiple authors and class members objected to the $1.5 billion settlement over Anthropic's use of copyrighted books to train AI models.
• Lawyers are requesting over $320 million in legal fees while individual authors expect only $3,000 payouts, prompting objectors to argue the compensation structure is unfair and disproportionate.
• Objector Pierce Story calculated that lawyer fees could equate to $10,000–$12,000 per hour and proposed reducing attorney compensation to $70 million, which would increase individual author awards by nearly 25%.
• Class members have raised additional concerns about lack of prospective relief, with some demanding Anthropic destroy all copies of pirated works before settlement approval.
• Objectors reported difficulties submitting concerns through court systems and alleged that the authors' legal team attempted to exclude or invalidate certain objections from the record.
• Authors must respond to objections by May 21, and the judge ordered Anthropic to explain why late opt-outs should not be honored; a separate lawsuit has also been filed by 25 class members opting out of the settlement.

Why It Matters:

The delays and objections highlight ongoing tensions in class-action settlements between attorney compensation, plaintiff recovery, and broader protections against future misuse of creative works.

The US Commodity Futures Trading Commission is ramping up enforcement against insider traders using offshore prediction markets like Polymarket, leveraging AI tools to detect suspicious trading patterns.

Key Details:

• The CFTC is staffing up and using AI-powered surveillance systems to analyze trading data and flag potential market manipulation, including tools like Chainalysis for crypto platforms and Nasdaq Smarts for centralized markets
• Traders have been accessing offshore prediction markets blocked in the US by using virtual private networks, making bets on geopolitical events like the Venezuela raid and Iran War
• CFTC chairman Michael Selig stated the agency is pursuing "hundreds, if not thousands" of insider trading tips and will use extraterritorial jurisdiction to pursue wrongdoers on offshore platforms
• Prediction market companies including Kalshi and Polymarket have announced partnerships with blockchain tracing and market integrity firms to catch suspicious traders
• As of the article's publication, only one person—a US Army special forces soldier—has been charged with insider trading related to Polymarket trades on Venezuelan political events
• Congressional pressure has mounted, with lawmakers questioning whether White House staffers engaged in insider trading on war-related contracts

Why It Matters: The CFTC's commitment to aggressive enforcement, backed by AI automation and international cooperation, signals a serious crackdown on what had appeared to be largely unregulated fraud on offshore prediction markets.