AI News

#1 Productivity & Automation

Every Enterprise Is About to Have a 100,000 Agent Problem | Oren Michaels of Barndoor AI

As AI agents gain access to your business tools, the critical challenge isn't connectivity—it's control. Enterprises face a governance crisis where agents can misinterpret instructions and act across multiple systems simultaneously, creating risks that traditional security systems weren't designed to handle. The solution requires granular permission frameworks that specify exactly what each agent can do in each context.

Key Takeaways

• Treat AI agents like enthusiastic interns: they'll execute tasks when asked, but may misunderstand instructions with far-reaching consequences across connected systems
• Prepare for governance at scale: each discrete agent task requires its own permission rules, quickly scaling beyond manual oversight capacity
• Recognize the new threat model: the risk isn't unauthorized access, but authorized users with agents that execute unintended actions

Source: Eye on AI

email communication planning documents

#2 Research & Analysis

Agentic BI: A Practical Guide for BI Teams and Business Users

Agentic BI represents a shift from traditional business intelligence dashboards to AI agents that can autonomously query data, generate insights, and answer business questions in natural language. This means professionals can get answers to complex data questions without waiting for analysts or learning SQL, potentially transforming how teams access and act on business data in their daily workflows.

Key Takeaways

• Evaluate whether your team spends significant time waiting for data analysts to answer routine business questions—agentic BI tools could automate these requests
• Consider piloting natural language data queries for common business metrics like sales trends, customer behavior, or operational KPIs instead of relying on static dashboards
• Prepare your data infrastructure by ensuring clean, well-documented datasets since AI agents require quality data to generate reliable insights

Source: Databricks Blog

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#3 Productivity & Automation

AI News: Microsoft Finally Reveals Their Plan!

Microsoft unveiled a comprehensive AI strategy including seven new MAI models, Scout (an always-on personal agent), and GitHub Copilot desktop app, alongside major partnerships with NVIDIA and Mayo Clinic. The announcements signal a shift toward persistent AI agents that work across applications rather than isolated tools. Professionals should prepare for AI assistants that maintain context across work sessions and integrate more deeply into Windows and Microsoft 365 workflows.

Key Takeaways

• Explore Microsoft Scout when available—it promises to act as an always-on personal agent that maintains context across your work sessions and applications
• Download the GitHub Copilot desktop app to access AI coding assistance outside your browser and IDE, enabling more flexible development workflows
• Monitor NVIDIA's RTX Spark integration for Windows PCs, which will bring local AI agent capabilities to your desktop without cloud dependency

Source: Matt Wolfe (YouTube)

code documents planning communication

#4 Productivity & Automation

Zapier Formatter: Automatically format text the way you want

Zapier's Formatter tool automates text formatting when connecting different applications, eliminating manual data cleanup tasks like splitting names, reformatting dates, or adjusting phone numbers. This addresses a common workflow friction point where data exports from one tool don't match the import requirements of another, saving time on repetitive formatting work.

Key Takeaways

• Use Zapier Formatter to automatically standardize data formats between apps instead of manual editing
• Automate common formatting tasks like splitting full names into first/last fields or converting date formats
• Eliminate data preparation bottlenecks when integrating tools in your workflow

Source: Zapier AI Blog

spreadsheets documents email planning

#5 Coding & Development

Anthropic says 80% of its new production code is now authored by Claude — how your enterprise can catch up (7 minute read)

Anthropic's engineers now generate 8x more code by having Claude write 80% of their production code, demonstrating that AI coding assistants can dramatically scale individual developer output in real-world enterprise settings. This validates that AI-assisted development is ready for production use beyond simple autocomplete, potentially transforming how development teams should structure their workflows and capacity planning.

Key Takeaways

• Evaluate AI coding assistants for production code generation, not just boilerplate—Anthropic's results show these tools can handle substantial portions of real development work
• Adjust team capacity planning to account for potential 8x productivity multipliers when developers fully integrate AI coding tools into their workflow
• Focus code review processes on AI-generated code quality and security, as the volume of code requiring human oversight will increase dramatically

Source: TLDR AI

code planning

#6 Productivity & Automation

ChatGPT Dreaming V3 (7 minute read)

OpenAI's new memory synthesis system for ChatGPT enables the AI to maintain better context and continuity across extended conversations, particularly valuable for professionals managing long-term projects or recurring workflows. The feature is rolling out to Plus and Pro subscribers in the US, allowing ChatGPT to better remember and reference past interactions for more relevant responses over time.

Key Takeaways

• Evaluate upgrading to ChatGPT Plus or Pro if you regularly return to the same projects or topics, as improved memory will reduce repetitive context-setting
• Leverage enhanced continuity for ongoing client work, project management, or iterative document creation where ChatGPT needs to recall previous decisions and preferences
• Test the memory system with recurring workflows like weekly reports or client communications to see if it reduces setup time

Source: TLDR AI

documents communication planning research

#7 Productivity & Automation

OpenAI Help: Lockdown Mode

OpenAI has launched Lockdown Mode for ChatGPT users to prevent data theft through prompt injection attacks by blocking unauthorized outbound network requests. This security feature is now available across Free, Plus, Pro, and Business accounts, but its existence confirms that ChatGPT's default settings don't fully protect against determined data exfiltration attempts.

Key Takeaways

• Enable Lockdown Mode in your ChatGPT account settings if you regularly process sensitive business data or confidential documents
• Understand that Lockdown Mode prevents data theft but doesn't stop prompt injections from appearing in uploaded files or web content
• Avoid uploading highly sensitive information to ChatGPT in default mode, as it lacks robust protection against sophisticated data exfiltration attacks

Source: Simon Willison's Blog

documents research email

#8 Industry News

The token bill comes due: Inside the industry scramble to manage AI’s runaway costs

AI costs are spiraling beyond initial expectations, forcing companies to shift from rapid adoption to implementing strict usage controls and budget guardrails. The industry is moving away from unlimited AI access toward measured deployment, which means professionals should expect more restrictions on their AI tool usage and may need to justify ROI more carefully.

Key Takeaways

• Monitor your team's AI spending now before leadership imposes sudden restrictions—track which tools and features consume the most tokens
• Prepare cost-benefit justifications for your AI tool usage as finance teams increasingly scrutinize these expenses
• Consider switching to fixed-price AI tools or plans where possible to avoid unpredictable token-based billing

Source: TechCrunch - AI

planning documents code

#9 Productivity & Automation

AI is rewriting the logic of management

AI automation of routine reporting and analysis tasks is fundamentally changing management roles, shifting focus from data collection to strategic decision-making and team development. This transition creates an opportunity for managers to reclaim time for high-value activities like coaching, relationship-building, and complex problem-solving that AI cannot replicate.

Key Takeaways

• Delegate routine reporting and data analysis tasks to AI tools to free up management time for strategic work
• Redirect reclaimed time toward coaching team members and developing talent rather than processing information
• Focus on relationship-building and cross-functional collaboration that requires human judgment and emotional intelligence

Source: Fast Company

planning meetings spreadsheets

#10 Productivity & Automation

Power Automate pricing and plans for 2026

Power Automate's pricing structure can catch Microsoft 365 users off-guard, with essential connectors often requiring paid plans beyond the free tier. Understanding the pricing tiers before building critical workflows is essential, as costs can escalate quickly—including a $5,000/month enterprise add-on. For professionals already invested in Microsoft's ecosystem, reviewing your automation needs against actual plan costs prevents budget surprises.

Key Takeaways

• Audit your current Power Automate workflows to identify which connectors you're using and verify they're included in your plan tier
• Review pricing before building new automations to avoid discovering mid-project that required connectors need plan upgrades
• Budget for Power Automate costs separately from your Microsoft 365 subscription, as automation features layer on top of existing licenses

Source: Zapier AI Blog

email documents spreadsheets planning

Coding & Development

Anthropic says 80% of its new production code is now authored by Claude — how your enterprise can catch up (7 minute read)

Anthropic's engineers now generate 8x more code by having Claude write 80% of their production code, demonstrating that AI coding assistants can dramatically scale individual developer output in real-world enterprise settings. This validates that AI-assisted development is ready for production use beyond simple autocomplete, potentially transforming how development teams should structure their workflows and capacity planning.

Key Takeaways

• Evaluate AI coding assistants for production code generation, not just boilerplate—Anthropic's results show these tools can handle substantial portions of real development work
• Adjust team capacity planning to account for potential 8x productivity multipliers when developers fully integrate AI coding tools into their workflow
• Focus code review processes on AI-generated code quality and security, as the volume of code requiring human oversight will increase dramatically

Source: TLDR AI

code planning

Coding & Development

Building Semantic Search with Transformers.js and Sentence Embeddings

Semantic search using transformer-based sentence embeddings can solve the common problem where exact keyword matching fails to return relevant results. This technology enables search functionality that understands meaning and context, not just exact text matches, making it particularly valuable for internal knowledge bases, product catalogs, and customer support systems. The article demonstrates implementation using Transformers.js, making this capability accessible without requiring backend inf

Key Takeaways

• Consider implementing semantic search for your internal documentation or product catalogs to reduce 'zero results' frustration when users search with synonyms or related terms
• Evaluate Transformers.js as a client-side solution that runs directly in browsers, eliminating the need for dedicated search infrastructure or API costs
• Test semantic search on your existing search problems where keyword matching fails, such as support ticket routing or FAQ systems

Source: Machine Learning Mastery

code documents research

Coding & Development

Quoting Andreas Kling

The Ladybird browser project is closing public pull requests due to AI-generated code submissions that lack accountability. This signals a broader shift in open-source development: the origin of code matters less than who takes responsibility for maintaining it. For professionals using AI coding tools, this highlights the critical importance of owning and understanding any AI-generated code you submit or deploy.

Key Takeaways

• Review all AI-generated code thoroughly before submitting to projects or deploying in production—you are accountable for its quality and consequences
• Consider establishing clear policies within your team about AI code contributions and who owns responsibility for reviewing and maintaining them
• Recognize that AI-generated content volume doesn't equal quality or good faith effort—apply the same scrutiny to AI output as you would to any external code

Source: Simon Willison's Blog

code

Coding & Development

Bring Databricks into Kiro IDE with the AI Dev Kit Power

Databricks has integrated its AI Dev Kit with Kiro IDE, enabling AI coding assistants to access actual database schemas, table structures, and column names instead of guessing. This integration means developers working with data pipelines get more accurate code suggestions that reference real database objects, reducing errors and iteration time when writing data transformation code.

Key Takeaways

• Connect your Databricks workspace to Kiro IDE to give AI assistants direct access to your actual database schemas and table structures
• Expect more accurate code completions when writing SQL queries or data pipeline code, as the AI can reference real column names and data types
• Consider this integration if you frequently write data transformation code and spend time correcting AI suggestions that reference non-existent tables or columns

Source: Databricks Blog

code research

Coding & Development

Defending Code Reference Harness (GitHub Repo)

Anthropic has released an open-source reference implementation that uses Claude to automatically find and fix security vulnerabilities in code. Development teams can either build custom vulnerability scanning pipelines using this GitHub repository or opt for Anthropic's managed service to scan multiple projects simultaneously. This represents a practical application of AI for improving code security without manual review.

Key Takeaways

• Explore Anthropic's open-source repository to build automated security scanning into your development workflow using Claude
• Consider the managed service option if you need to scan vulnerabilities across multiple codebases without maintaining custom infrastructure
• Evaluate whether autonomous vulnerability detection could reduce your team's manual security review time and catch issues earlier

Source: TLDR AI

code

Coding & Development

Ollama Model Tester (GitHub Repo)

Ollama Model Tester is a command-line tool that helps professionals evaluate and compare different local AI models by running identical prompts across multiple models and organizing the results for side-by-side comparison. This addresses a common challenge for teams running local AI infrastructure: determining which model performs best for their specific use cases without manual testing. The tool is particularly valuable for organizations prioritizing data privacy through local model deployment.

Key Takeaways

• Test multiple local Ollama models systematically by running the same prompt across different models to identify which performs best for your specific tasks
• Save time on model evaluation by automating the comparison process rather than manually switching between models and copying results
• Consider using this tool before committing to a specific local model for production workflows, especially when balancing performance against resource constraints

Source: TLDR AI

code research

Coding & Development

When AI builds itself (25 minute read)

Anthropic's recursive self-improvement approach is enabling AI systems to help build better AI systems, resulting in engineers shipping 8x more code. This signals a fundamental shift in how AI development tools will evolve—expect your coding assistants and automation tools to become dramatically more capable at an accelerating pace.

Key Takeaways

• Anticipate rapid capability improvements in your AI coding tools as recursive development methods become standard across the industry
• Evaluate your development workflows now to identify bottlenecks that next-generation AI assistants could eliminate entirely
• Monitor your AI tool providers for updates that leverage self-improving systems to enhance productivity

Source: TLDR AI

code

Coding & Development

3 SpaCy Tricks for Efficient Text Processing & Entity Recognition

SpaCy, a popular natural language processing library, offers optimization techniques that can significantly speed up text processing and improve entity recognition accuracy. For professionals working with large volumes of text data or building custom NLP workflows, these performance tricks can reduce processing time and enable more sophisticated text analysis in business applications.

Key Takeaways

• Optimize spaCy pipeline performance by disabling unused components to reduce processing overhead when analyzing large document sets
• Customize entity recognition models to identify industry-specific terms and business entities relevant to your domain
• Leverage batch processing techniques to handle multiple documents simultaneously and improve throughput for text analysis workflows

Source: KDnuggets

code documents research

Coding & Development

Stop wrangling GPU clusters. Fine-tune open-source models in an afternoon with Crusoe Cloud (Sponsor)

Crusoe Cloud has launched a serverless fine-tuning service that eliminates the technical complexity of customizing open-source AI models. Instead of managing GPU infrastructure and clusters, professionals can now submit fine-tuning jobs and receive customized model weights without handling any backend systems. This service aims to make model customization accessible to businesses without dedicated ML infrastructure teams.

Key Takeaways

• Consider requesting early access if your team needs custom AI models but lacks infrastructure expertise or dedicated ML engineers
• Evaluate whether serverless fine-tuning could reduce your AI development costs by eliminating cluster management overhead
• Watch for pricing details and service availability as this moves from private preview to general release

Source: TLDR AI

code

Coding & Development

Running Python code in a sandbox with MicroPython and WASM

Developer Simon Willison has released an alpha package that enables safe execution of Python code in isolated sandboxes using MicroPython and WebAssembly. This approach addresses a critical need for developers building AI agents and plugins that need to run untrusted code securely, particularly relevant for tools that generate and execute code automatically.

Key Takeaways

• Consider this solution if you're building AI agents or tools that need to execute generated Python code safely without risking your system security
• Evaluate WebAssembly-based sandboxing as an alternative to traditional containerization for lightweight code execution in AI workflows
• Watch for the production release of micropython-wasm if your workflow involves AI-generated code that needs isolated execution environments

Source: Simon Willison's Blog

code

Coding & Development

micropython-wasm 0.1a2

Simon Willison released micropython-wasm 0.1a2, a tool that runs MicroPython code in a sandboxed WebAssembly environment with a new command-line interface. This development enables safer execution of untrusted Python code, which is particularly relevant for professionals building AI applications that generate or execute code dynamically. The sandboxing capability addresses security concerns when integrating AI-generated code into workflows.

Key Takeaways

• Consider micropython-wasm for safely testing AI-generated Python code snippets before running them in production environments
• Explore WebAssembly sandboxing as a security layer when building applications that execute user-provided or LLM-generated code
• Watch for the CLI addition which simplifies integration into automated workflows and testing pipelines

Source: Simon Willison's Blog

code

Research & Analysis

Agentic BI: A Practical Guide for BI Teams and Business Users

Agentic BI represents a shift from traditional business intelligence dashboards to AI agents that can autonomously query data, generate insights, and answer business questions in natural language. This means professionals can get answers to complex data questions without waiting for analysts or learning SQL, potentially transforming how teams access and act on business data in their daily workflows.

Key Takeaways

• Evaluate whether your team spends significant time waiting for data analysts to answer routine business questions—agentic BI tools could automate these requests
• Consider piloting natural language data queries for common business metrics like sales trends, customer behavior, or operational KPIs instead of relying on static dashboards
• Prepare your data infrastructure by ensuring clean, well-documented datasets since AI agents require quality data to generate reliable insights

Source: Databricks Blog

research spreadsheets planning communication

Research & Analysis

LinkedIn signal quality: A playbook for pipeline

Marketing teams can now prioritize speed-to-insight over speed-to-lead by using AI-powered analytics to quickly identify which campaigns drive actual conversions, not just lead volume. This shift means professionals can make confident budget decisions based on conversion data without waiting for lengthy manual reconciliation processes. The approach is particularly valuable for scaling teams that need to optimize marketing spend efficiently.

Key Takeaways

• Shift your focus from response speed to insight speed when evaluating marketing campaigns and lead quality
• Use AI analytics tools to track conversion events in real-time rather than relying on monthly reconciliation reports
• Compare campaigns based on actual conversion quality, not just cost-per-lead or lead volume metrics

Source: Zapier AI Blog

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Creative & Media

I Didn’t Know AI Could Do THIS

AI tools can now generate realistic video footage following custom routes drawn on Google Maps screenshots, offering a cost-effective alternative to drone filming for establishing shots. This capability is particularly valuable for content creators and marketers who need location-based video content without production budgets or travel expenses.

Key Takeaways

• Consider using AI-generated route videos for marketing materials, presentations, or social media content when you need location-specific establishing shots
• Explore this technique as a budget alternative to hiring drone operators or traveling to locations for B-roll footage
• Test the quality against your brand standards before using in client-facing materials, as AI-generated content may have limitations

Source: Matt Wolfe (YouTube)

design presentations communication

Productivity & Automation

Every Enterprise Is About to Have a 100,000 Agent Problem | Oren Michaels of Barndoor AI

As AI agents gain access to your business tools, the critical challenge isn't connectivity—it's control. Enterprises face a governance crisis where agents can misinterpret instructions and act across multiple systems simultaneously, creating risks that traditional security systems weren't designed to handle. The solution requires granular permission frameworks that specify exactly what each agent can do in each context.

Key Takeaways

• Treat AI agents like enthusiastic interns: they'll execute tasks when asked, but may misunderstand instructions with far-reaching consequences across connected systems
• Prepare for governance at scale: each discrete agent task requires its own permission rules, quickly scaling beyond manual oversight capacity
• Recognize the new threat model: the risk isn't unauthorized access, but authorized users with agents that execute unintended actions

Source: Eye on AI

email communication planning documents

Productivity & Automation

AI News: Microsoft Finally Reveals Their Plan!

Microsoft unveiled a comprehensive AI strategy including seven new MAI models, Scout (an always-on personal agent), and GitHub Copilot desktop app, alongside major partnerships with NVIDIA and Mayo Clinic. The announcements signal a shift toward persistent AI agents that work across applications rather than isolated tools. Professionals should prepare for AI assistants that maintain context across work sessions and integrate more deeply into Windows and Microsoft 365 workflows.

Key Takeaways

• Explore Microsoft Scout when available—it promises to act as an always-on personal agent that maintains context across your work sessions and applications
• Download the GitHub Copilot desktop app to access AI coding assistance outside your browser and IDE, enabling more flexible development workflows
• Monitor NVIDIA's RTX Spark integration for Windows PCs, which will bring local AI agent capabilities to your desktop without cloud dependency

Source: Matt Wolfe (YouTube)

code documents planning communication

Productivity & Automation

Zapier Formatter: Automatically format text the way you want

Zapier's Formatter tool automates text formatting when connecting different applications, eliminating manual data cleanup tasks like splitting names, reformatting dates, or adjusting phone numbers. This addresses a common workflow friction point where data exports from one tool don't match the import requirements of another, saving time on repetitive formatting work.

Key Takeaways

• Use Zapier Formatter to automatically standardize data formats between apps instead of manual editing
• Automate common formatting tasks like splitting full names into first/last fields or converting date formats
• Eliminate data preparation bottlenecks when integrating tools in your workflow

Source: Zapier AI Blog

spreadsheets documents email planning

Productivity & Automation

ChatGPT Dreaming V3 (7 minute read)

OpenAI's new memory synthesis system for ChatGPT enables the AI to maintain better context and continuity across extended conversations, particularly valuable for professionals managing long-term projects or recurring workflows. The feature is rolling out to Plus and Pro subscribers in the US, allowing ChatGPT to better remember and reference past interactions for more relevant responses over time.

Key Takeaways

• Evaluate upgrading to ChatGPT Plus or Pro if you regularly return to the same projects or topics, as improved memory will reduce repetitive context-setting
• Leverage enhanced continuity for ongoing client work, project management, or iterative document creation where ChatGPT needs to recall previous decisions and preferences
• Test the memory system with recurring workflows like weekly reports or client communications to see if it reduces setup time

Source: TLDR AI

documents communication planning research

Productivity & Automation

OpenAI Help: Lockdown Mode

OpenAI has launched Lockdown Mode for ChatGPT users to prevent data theft through prompt injection attacks by blocking unauthorized outbound network requests. This security feature is now available across Free, Plus, Pro, and Business accounts, but its existence confirms that ChatGPT's default settings don't fully protect against determined data exfiltration attempts.

Key Takeaways

• Enable Lockdown Mode in your ChatGPT account settings if you regularly process sensitive business data or confidential documents
• Understand that Lockdown Mode prevents data theft but doesn't stop prompt injections from appearing in uploaded files or web content
• Avoid uploading highly sensitive information to ChatGPT in default mode, as it lacks robust protection against sophisticated data exfiltration attacks

Source: Simon Willison's Blog

documents research email

Productivity & Automation

AI is rewriting the logic of management

AI automation of routine reporting and analysis tasks is fundamentally changing management roles, shifting focus from data collection to strategic decision-making and team development. This transition creates an opportunity for managers to reclaim time for high-value activities like coaching, relationship-building, and complex problem-solving that AI cannot replicate.

Key Takeaways

• Delegate routine reporting and data analysis tasks to AI tools to free up management time for strategic work
• Redirect reclaimed time toward coaching team members and developing talent rather than processing information
• Focus on relationship-building and cross-functional collaboration that requires human judgment and emotional intelligence

Source: Fast Company

planning meetings spreadsheets

Productivity & Automation

Power Automate pricing and plans for 2026

Power Automate's pricing structure can catch Microsoft 365 users off-guard, with essential connectors often requiring paid plans beyond the free tier. Understanding the pricing tiers before building critical workflows is essential, as costs can escalate quickly—including a $5,000/month enterprise add-on. For professionals already invested in Microsoft's ecosystem, reviewing your automation needs against actual plan costs prevents budget surprises.

Key Takeaways

• Audit your current Power Automate workflows to identify which connectors you're using and verify they're included in your plan tier
• Review pricing before building new automations to avoid discovering mid-project that required connectors need plan upgrades
• Budget for Power Automate costs separately from your Microsoft 365 subscription, as automation features layer on top of existing licenses

Source: Zapier AI Blog

email documents spreadsheets planning

Productivity & Automation

Rubrik CEO's Big AI Warning

Rubrik's CEO warns that AI agents introduce dramatically higher cybersecurity risks—up to 100 times greater than traditional systems. For professionals deploying AI tools in their workflows, this signals a critical shift: focus less on preventing breaches and more on ensuring rapid recovery capabilities when incidents occur.

Key Takeaways

• Evaluate your organization's data backup and recovery protocols before expanding AI agent usage across workflows
• Prioritize AI tools and vendors that offer clear incident response and data recovery features
• Document which AI agents have access to sensitive business data and establish recovery procedures for each

Source: Bloomberg Technology

planning communication

Productivity & Automation

Track Stripe payments to Facebook Conversions events with AI

Zapier now enables automated tracking of Stripe payment data to Facebook Conversions API, allowing businesses to measure actual revenue from Meta ads rather than relying on surface metrics. This AI-powered integration eliminates manual data reconciliation between payment systems and advertising platforms, providing clearer ROI insights for ad spend decisions.

Key Takeaways

• Connect your Stripe payment data directly to Facebook Conversions to track which ads generate actual revenue, not just clicks
• Automate the attribution process between payment transactions and ad campaigns to eliminate manual spreadsheet reconciliation
• Use conversion data to optimize Meta ad targeting by feeding the platform real purchase behavior instead of proxy metrics

Source: Zapier AI Blog

planning spreadsheets

Productivity & Automation

The 6 best electronic signature apps to sign documents online in 2026

Electronic signature apps have become essential for legally binding document workflows, eliminating the need for physical paperwork while meeting legal and regulatory requirements. For professionals managing contracts, agreements, and approvals, dedicated eSignature tools ensure digital signatures hold up in court and comply with various regulatory bodies. This guide evaluates the top platforms for integrating electronic signatures into business workflows.

Key Takeaways

• Implement a dedicated eSignature app rather than informal digital signatures to ensure legal compliance and regulatory acceptance
• Evaluate eSignature platforms based on integration capabilities with your existing document workflow and business tools
• Consider the legal requirements specific to your industry when selecting an electronic signature solution

Source: Zapier AI Blog

documents communication

Productivity & Automation

Local AI you own (Sponsor)

QVAC is an open-source platform that runs AI models (language, speech, translation, and image processing) entirely on your local device without cloud dependencies or subscriptions. This offers professionals complete data privacy and independence from API costs, though it requires sufficient local computing resources to run effectively.

Key Takeaways

• Evaluate QVAC if data privacy is critical—all processing happens on your device with no cloud transmission
• Consider this for cost control since there are no API fees or subscription charges after initial setup
• Assess your hardware capabilities before implementing, as local AI models require significant computing power

Source: TLDR AI

documents communication research

Productivity & Automation

The Download: AI hacking beyond Mythos, and chatbots’ impact on our brains

Attackers exploited Meta's AI customer support agent to hijack Instagram accounts, demonstrating that AI security vulnerabilities extend beyond traditional systems like Mythos. This incident highlights critical risks for businesses deploying AI chatbots and automated support tools, particularly around authentication and access control.

Key Takeaways

• Review security protocols for any AI chatbots or automated support systems your organization uses, especially those with account access capabilities
• Implement additional authentication layers when AI agents interact with sensitive customer data or account management functions
• Monitor AI agent interactions for unusual patterns that could indicate exploitation attempts

Source: MIT Technology Review

communication planning

Productivity & Automation

Thousand Token Wood: shipping a multi-agent economy on a 3B model

Hugging Face demonstrates a multi-agent system running on a compact 3B parameter model, proving that sophisticated AI workflows don't require massive computing resources. This breakthrough suggests businesses can deploy autonomous agent systems on standard hardware without cloud dependencies or high API costs, making advanced AI automation accessible to smaller organizations.

Key Takeaways

• Consider deploying multi-agent workflows on local hardware using smaller models (3B parameters) instead of relying on expensive cloud-based LLMs for routine automation tasks
• Evaluate cost savings by running agent-based systems on-premise, particularly for tasks requiring multiple AI interactions like data processing pipelines or customer service workflows
• Test lightweight models for coordinating multiple AI agents in your workflow, especially if you're currently avoiding agent systems due to API costs

Source: Hugging Face Blog

planning code

Productivity & Automation

DocuSign Shares Drop After Full-Year Guidance Disappoints Investors

DocuSign's AI-powered intelligent agreement management platform now serves 40,000 customers, demonstrating significant enterprise adoption of AI-enhanced contract and document workflows. Despite stock market concerns about growth guidance, the platform's traction signals maturity in AI-assisted agreement management tools that professionals increasingly rely on for contract processing and signature workflows.

Key Takeaways

• Evaluate DocuSign's AI agreement management platform if your workflow involves frequent contract reviews, approvals, or signature processes across teams
• Monitor the 40,000-customer adoption milestone as validation that AI-enhanced document management tools have moved beyond early adoption into mainstream business use
• Consider how intelligent agreement platforms can automate contract analysis and workflow routing in your organization's approval processes

Source: Bloomberg Technology

documents communication

Productivity & Automation

We’ve changed what it means to be a manager

This article highlights a critical gap in organizational support: managers face expanded responsibilities without corresponding training or resources. For professionals using AI, this signals an opportunity to leverage AI tools to bridge support gaps in management tasks like communication, delegation, and team coordination.

Key Takeaways

• Evaluate AI tools that can streamline management tasks like meeting summaries, status updates, and team communication to compensate for lack of organizational support
• Consider using AI assistants to automate routine managerial workflows such as performance feedback drafting, project tracking, and scheduling
• Advocate for AI-powered training and development resources if you're in a management role facing expanded responsibilities

Source: Fast Company

meetings communication planning documents

Productivity & Automation

What to expect from Apple at WWDC 26 on Monday: Siri AI, iOS 27, refined Liquid Glass, John Ternus, and more

Apple's WWDC on June 8 will preview iOS 27 and Siri AI enhancements coming this fall. For professionals relying on Apple devices for work, this event signals potential improvements to voice-based productivity tools and native AI capabilities that could streamline daily workflows. The announcements may influence decisions about AI tool integration on Apple platforms.

Key Takeaways

• Monitor WWDC announcements for Siri AI upgrades that could enhance voice-based task management and device control in your workflow
• Evaluate how iOS 27 features might integrate with your current productivity tools before the fall release
• Consider timing any Apple device purchases or workflow changes around the fall software release cycle

Source: Fast Company

communication planning

Productivity & Automation

Apple's Messages app on iPhone now has a third-party AI agent (2 minute read)

Apple has approved Poke, a third-party AI assistant, for integration directly into iPhone's Messages app, marking a significant shift in Apple's traditionally closed ecosystem. This opens the door for professionals to access AI capabilities within iMessage for task management and queries, though early users report performance issues due to high demand. The approval signals Apple's growing acceptance of third-party AI tools in core applications.

Key Takeaways

• Monitor Poke's development as an alternative to switching between apps for AI assistance on iPhone
• Consider the implications of Apple opening Messages to third-party AI for future workflow integration possibilities
• Watch for similar AI integrations in other Apple apps as the company expands third-party AI access

Source: TLDR AI

communication planning

Industry News

The token bill comes due: Inside the industry scramble to manage AI’s runaway costs

AI costs are spiraling beyond initial expectations, forcing companies to shift from rapid adoption to implementing strict usage controls and budget guardrails. The industry is moving away from unlimited AI access toward measured deployment, which means professionals should expect more restrictions on their AI tool usage and may need to justify ROI more carefully.

Key Takeaways

• Monitor your team's AI spending now before leadership imposes sudden restrictions—track which tools and features consume the most tokens
• Prepare cost-benefit justifications for your AI tool usage as finance teams increasingly scrutinize these expenses
• Consider switching to fixed-price AI tools or plans where possible to avoid unpredictable token-based billing

Source: TechCrunch - AI

planning documents code

Industry News

BOE’s Bailey Warns of Possible AI Rationing on Capacity Limits

Bank of England Governor Andrew Bailey warns that energy capacity constraints may force rationing of AI access across economic sectors. This suggests businesses may face limitations in scaling AI deployments, potentially affecting availability and costs of AI tools professionals rely on daily. Organizations should prepare for possible service restrictions or prioritization systems.

Key Takeaways

• Evaluate your current AI tool dependencies and identify critical versus non-essential use cases to prepare for potential access limitations
• Consider diversifying across multiple AI providers to reduce risk if capacity constraints lead to service restrictions
• Monitor your AI service costs and usage patterns as energy constraints could drive price increases or usage caps

Source: Bloomberg Technology

planning

Industry News

The ‘AI boomerang’: Why some companies are rehiring employees they laid off due to AI

Companies that rushed to replace employees with AI are now rehiring workers, revealing that current AI tools cannot fully replace human judgment and expertise. This trend suggests that AI works best as an augmentation tool rather than a complete replacement for skilled professionals. The pattern indicates that organizations need to carefully evaluate which tasks AI can truly handle independently versus where human oversight remains essential.

Key Takeaways

• Position yourself as an AI-augmented professional rather than someone replaceable by AI—focus on tasks requiring judgment, context, and human oversight
• Document the limitations you encounter when using AI tools in your workflow to demonstrate where human expertise remains critical
• Advocate for hybrid approaches in your organization where AI handles routine tasks while you focus on complex decision-making and quality control

Source: Fast Company

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Industry News

AI Is Rewriting the Economics of Outsourcing

AI is fundamentally changing the build-versus-buy decision for business functions. As AI tools become more capable and accessible, companies can now automate or handle in-house what they previously outsourced, while also creating new opportunities to outsource AI-enhanced work. This shift requires professionals to reassess which tasks should remain internal versus external based on new AI capabilities.

Key Takeaways

• Evaluate current outsourcing arrangements against available AI tools that could handle similar tasks in-house more efficiently
• Consider bringing previously outsourced functions back internally if AI tools can now make them manageable with existing staff
• Identify new outsourcing opportunities where external providers using AI can deliver better results than your current internal processes

Source: Harvard Business Review

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Industry News

Has Microsoft Lost Its Mojo (Again)?

Microsoft's AI products are facing adoption challenges, with slower-than-expected sales and ongoing issues at GitHub. For professionals currently invested in Microsoft's AI ecosystem, this signals potential uncertainty around product roadmaps and feature development, though the company remains a major player with significant resources to course-correct.

Key Takeaways

• Monitor your Microsoft AI tool investments closely and maintain backup alternatives, especially if you're heavily dependent on GitHub Copilot or Azure AI services for critical workflows
• Evaluate whether current Microsoft AI products are meeting your ROI expectations before committing to expanded licenses or enterprise agreements
• Consider diversifying your AI tool stack rather than relying solely on Microsoft's ecosystem, given the reported adoption challenges

Source: Wired - AI

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Industry News

Apollo Wraps Up $35 Billion Debt to Buy AI Chips for Anthropic

Anthropic has secured $35 billion in financing from Apollo and Blackstone to expand its AI infrastructure and chip capacity. This substantial investment signals continued development and scaling of Claude, which could mean improved performance, reduced wait times, and potentially new features for professionals already using the platform in their workflows.

Key Takeaways

• Expect improved Claude performance and availability as Anthropic scales infrastructure with this funding
• Monitor for new Claude features or tier offerings that may emerge from expanded capacity
• Consider Anthropic's strengthened financial position when evaluating long-term AI tool commitments

Source: Bloomberg Technology

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Industry News

Nemotron 3.5 Content Safety (9 minute read)

NVIDIA's Nemotron 3.5 Content Safety offers enterprises a production-ready moderation system that works across multiple content types and languages with explainable decision-making. This tool enables businesses to implement consistent safety controls across their AI applications, from chatbots to content generation systems, with audit trails that support compliance requirements.

Key Takeaways

• Evaluate Nemotron 3.5 if your organization needs to moderate AI-generated content across multiple languages or content types (text, images) in a single system
• Consider implementing this for customer-facing AI applications where you need documented reasoning for content moderation decisions to meet compliance requirements
• Assess whether the unified approach reduces complexity compared to managing separate moderation tools for different content types in your current workflow

Source: TLDR AI

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Industry News

A new "claude-oceanus-v1-p" has been made available to Red Teams (1 minute read)

Anthropic is preparing to launch an upgraded version of its Claude model (codenamed Oceanus) that surpasses the current Mythos Preview. The model is currently in red team testing, which typically occurs one week before public release, though a security incident involving unauthorized resale may affect the timeline. Professionals should anticipate access to enhanced Claude capabilities in the near future.

Key Takeaways

• Monitor Anthropic's announcements for the official Oceanus/Mythos launch to evaluate whether upgrading your Claude subscription tier makes sense for your workflows
• Prepare to test the new model against your current Claude use cases once available, as performance improvements could enhance document analysis, coding assistance, and research tasks
• Consider the security implications highlighted by the resale incident when evaluating API access controls and usage policies in your organization

Source: TLDR AI

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Industry News

This Week in AI: Production Viability

Industry experts discuss current challenges in deploying AI systems for production use, including OpenAI's expansion into personal finance applications. The conversation addresses practical concerns professionals face when moving AI tools from testing to real-world business implementation.

Key Takeaways

• Monitor OpenAI's personal finance initiatives as they may signal new integration opportunities for business financial workflows
• Evaluate your current AI tools for production readiness before scaling beyond pilot projects
• Consider the gap between AI experimentation and reliable deployment when planning workflow automation

Source: O'Reilly Radar

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Industry News

K-pop Fans Are Calling Out Creepy Deepfakes of Idols

K-pop fans are confronting the creation of non-consensual deepfake content of celebrities, highlighting growing concerns about AI-generated imagery misuse. This incident underscores the reputational and legal risks organizations face when AI tools are used to create unauthorized content of real people. Professionals should understand that accessible generative AI technology requires clear usage policies and ethical guidelines.

Key Takeaways

• Establish clear policies prohibiting the creation of non-consensual AI-generated images of real individuals in your organization
• Review your AI tool usage guidelines to address deepfake creation and ensure compliance with emerging regulations
• Consider implementing content verification processes if your work involves publishing AI-generated media

Source: 404 Media

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Industry News

Tech Leaders Mull the Next Phase of AI as Top Labs Plan IPOs

Major AI labs are preparing for IPOs while industry leaders acknowledge entering uncharted territory with AI development. This signals potential shifts in how AI tools are funded, developed, and priced, which could affect the stability and pricing of the AI tools you currently use in your workflow.

Key Takeaways

• Monitor your current AI tool providers for potential pricing changes or service adjustments as companies prepare for public markets
• Diversify your AI tool stack to avoid over-reliance on any single provider facing potential business model shifts
• Watch for new enterprise-focused features as companies seek to demonstrate stable revenue streams to investors

Source: Bloomberg Technology

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Industry News

Wall Street Week | AI-era Internet, Spaceport Investment, Bolivia’s Investability

AI-powered search is fundamentally changing how online content reaches audiences, reducing traditional web traffic to publishers and forcing businesses to reconsider their digital content strategies. This shift affects how professionals should think about content distribution, SEO strategies, and audience engagement in an AI-mediated internet. The broader economic and geopolitical topics covered have minimal direct impact on daily AI workflows.

Key Takeaways

• Reassess your content distribution strategy as AI search tools increasingly surface answers directly rather than driving traffic to your website
• Consider diversifying audience engagement channels beyond traditional SEO, including direct subscriptions, newsletters, and AI-native content formats
• Monitor how your target audience discovers content as AI-powered search changes user behavior and information consumption patterns

Source: Bloomberg Technology

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Industry News

SAG-AFTRA actor’s union strikes 4-year deal with studios to protect performers against AI

SAG-AFTRA's new four-year contract with studios establishes precedent-setting protections against AI-generated synthetic actors, signaling growing industry pushback against unauthorized AI replication of human work. This labor agreement provides a framework that other industries may follow when negotiating AI usage rights and compensation, particularly relevant for professionals whose work could be replicated by generative AI tools.

Key Takeaways

• Monitor how AI usage rights are being negotiated in your industry, as entertainment unions are setting precedents for protecting human work from AI replication
• Consider documenting consent and compensation terms before allowing AI tools to train on your creative work or professional output
• Watch for similar labor agreements in other sectors that may affect how AI tools can legally use professional content without explicit permission

Source: Fast Company

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Industry News

Enterprise AI is in 1991. Where’s its web?

Enterprise AI in 2024 mirrors the internet in 1991—powerful infrastructure exists, but we're still waiting for the breakthrough applications that will make it truly transformative for business workflows. While AI models demonstrate impressive capabilities across writing, coding, and analysis, the 'killer apps' that will define how professionals actually use AI daily haven't emerged yet.

Key Takeaways

• Recognize that current AI tools are foundational—expect significant evolution in how they're packaged and integrated into workflows over the next few years
• Experiment with existing capabilities now (writing, coding, analysis) to build familiarity before the next wave of applications arrives
• Prepare for a shift from standalone AI tools to deeply integrated AI-native workflows, similar to how the web transformed from basic pages to full applications

Source: Fast Company

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Industry News

Millions of people could be affected by this lawsuit against Amazon’s Ring cameras

A lawsuit against Amazon's Ring cameras alleges unauthorized facial recognition data collection from non-customers, raising critical privacy concerns for businesses deploying surveillance or AI-powered camera systems. This case highlights the legal and reputational risks companies face when implementing AI technologies that capture biometric data without explicit consent, particularly in shared or public spaces.

Key Takeaways

• Review your organization's use of AI-powered cameras or surveillance systems to ensure compliance with biometric data collection laws and obtain proper consent
• Consider the privacy implications before deploying facial recognition or similar AI technologies that may capture data from employees, visitors, or the public
• Document clear policies about what AI systems collect, how data is stored, and who has access to protect against similar legal exposure

Source: Fast Company

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Industry News

AI is in nearly every classroom

While 84% of high school students now use AI for schoolwork, Gen Z's enthusiasm has dropped 14% in the past year, with nearly half of working Gen Zers viewing AI's workplace risks as outweighing benefits. This generational shift in AI perception signals potential challenges for organizations in adoption, training, and managing expectations as these workers enter the professional workforce.

Key Takeaways

• Prepare for incoming employees who may be skeptical of AI despite being familiar with it—focus training on practical benefits and risk mitigation
• Consider that widespread student AI use doesn't guarantee workplace proficiency—evaluate actual skills rather than assuming AI literacy
• Monitor team sentiment about AI tools regularly, as enthusiasm can decline quickly even among frequent users

Source: Fast Company

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Industry News

AI is eliminating entry-level jobs. Education needs to fill the gap

AI automation is eliminating 35% of entry-level positions since 2023, creating a talent pipeline challenge for businesses. Companies using AI to replace junior roles may face difficulties finding experienced mid-level talent in the future, as traditional career development pathways disappear. This shift requires businesses to reconsider how they develop internal talent and structure their teams.

Key Takeaways

• Evaluate your team's talent pipeline to identify gaps created by reduced entry-level hiring and plan alternative training pathways
• Consider implementing structured mentorship or apprenticeship programs to develop skills that junior employees traditionally gained on the job
• Review which entry-level tasks you've automated with AI and assess whether eliminating these roles impacts your future talent development

Source: Fast Company

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Industry News

Webinar: The New Monetization Playbook for Data Infrastructure with Aiven and Metronome (Sponsor)

Data infrastructure companies are restructuring their pricing models to accommodate AI agents and new deployment patterns, moving away from traditional billing approaches. This webinar addresses how changing unit economics and AI-driven usage patterns are forcing infrastructure providers to treat pricing as a continuously iterable product feature rather than a static business decision.

Key Takeaways

• Monitor your AI tool costs as providers shift pricing models to accommodate agent-based usage patterns that differ from traditional human usage
• Evaluate how your organization's deployment choices (cloud vs. on-premise) affect who bears infrastructure costs under evolving pricing structures
• Prepare for potential pricing changes from your data and AI infrastructure vendors as they adapt billing models for continuous iteration

Source: TLDR AI

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Industry News

Review: AMD's Radeon RX 9070 GRE is a disappointing way to spend $549

AMD's new Radeon RX 9070 GRE graphics card, priced at $549, underperforms compared to the superior RX 9070 that launched at the same price point over a year ago. For professionals running local AI models or using GPU-accelerated workflows, this represents poor value and suggests waiting for better options or considering the original RX 9070 if still available.

Key Takeaways

• Avoid purchasing the RX 9070 GRE at $549 as it offers worse performance than last year's RX 9070 at the same price
• Consider alternative GPU options or wait for price adjustments if upgrading hardware for local AI model inference
• Evaluate whether your current GPU setup remains adequate rather than upgrading to underwhelming new releases

Source: Ars Technica

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Industry News

"We pissed off a lot of people": Giant data center plan cut 50% amid protests

A major data center project was cut by 50% following community protests, highlighting growing infrastructure constraints for AI services. This signals potential capacity limitations that could affect cloud AI service availability and pricing for business users. The pushback against data center expansion may lead to increased competition for computing resources among AI providers.

Key Takeaways

• Monitor your AI service providers for potential capacity constraints or price increases as data center expansion faces community resistance
• Consider diversifying across multiple AI platforms to reduce dependency on any single provider's infrastructure
• Evaluate on-premise or hybrid AI solutions for critical workflows if cloud capacity becomes constrained

Source: Ars Technica

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Industry News

How a USB-connected speaker can infect a PC without ever being touched

A USB-connected speaker can automatically install software on Windows PCs without user interaction, highlighting a broader security concern for any USB device. This attack vector is particularly relevant for professionals who regularly connect peripherals to work computers that may contain sensitive AI models, proprietary data, or client information. The manufacturer doesn't consider this a vulnerability, underscoring the need for organizational USB device policies.

Key Takeaways

• Review your organization's USB device policy and consider restricting auto-installation of drivers from unknown peripherals
• Disable automatic driver installation in Windows settings if you frequently work with sensitive AI models or proprietary data
• Verify the source and legitimacy of any new USB devices before connecting them to machines with access to confidential information

Source: Ars Technica

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Industry News

OpenAI and Anthropic May Be Rivals, but Investors Aren’t Picking Sides

Major investors are backing both OpenAI and Anthropic simultaneously, treating AI model competition like consumer brands rather than winner-take-all markets. This signals that multiple AI platforms will likely coexist long-term, meaning professionals should expect to work across different AI tools rather than committing to a single provider.

Key Takeaways

• Diversify your AI tool stack across providers rather than betting on a single platform, as investors expect multiple winners in the AI space
• Prepare workflows that can adapt to different AI models, since vendor lock-in appears less critical than previously thought
• Monitor pricing and feature developments across both OpenAI and Anthropic, as competition should drive better value for business users

Source: Wired - AI

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Industry News

Google will pay SpaceX $920M per month for compute

Google's $920M monthly payment to SpaceX for compute infrastructure signals unprecedented demand for its AI products, indicating potential capacity constraints across major AI providers. This massive infrastructure investment suggests Google is scaling aggressively to meet enterprise and consumer AI demand, which may affect service availability and pricing for business users relying on Google's AI tools.

Key Takeaways

• Monitor Google AI service performance and availability, as this infrastructure expansion suggests current capacity may be strained during peak usage
• Evaluate backup AI providers for critical workflows to mitigate potential service disruptions during high-demand periods
• Anticipate potential pricing adjustments for Google AI services as the company invests heavily in infrastructure to meet demand

Source: TechCrunch - AI

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Industry News

New York lawmakers pass one-year ban on new data centers

New York State has passed a one-year moratorium on new large data centers to assess environmental and energy impacts. If signed into law, this could signal the start of regulatory constraints on AI infrastructure expansion, potentially affecting cloud service availability and pricing for businesses relying on AI tools hosted in affected regions.

Key Takeaways

• Monitor your AI service providers' data center locations and expansion plans, as regional restrictions could affect service reliability or costs
• Consider diversifying across multiple cloud providers or regions to mitigate potential infrastructure constraints
• Watch for similar legislation in other states that could create a precedent for AI infrastructure regulation

Source: The Verge - AI

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Industry News

This is your laptop… on AI

Tech leaders at recent developer conferences are signaling a fundamental shift in how we'll interact with laptops through AI integration. Nvidia's CEO Jensen Huang outlined a vision where AI transforms the basic computing experience, suggesting professionals should prepare for significant changes in how they use their primary work devices in the near future.

Key Takeaways

• Monitor upcoming laptop releases for native AI capabilities that could streamline your current workflows
• Evaluate whether your current hardware will support emerging AI features or if upgrades may be necessary
• Prepare for a shift from traditional application-based computing to AI-mediated interactions with your device

Source: The Verge - AI

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