Google AI Overviews Hit 2B Monthly Users 😱 Threads Adds More Metrics For Creators 🥳 New YouTube Shorts Creation Tool 🛠️

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Google’s AI Overviews Have 2B Monthly Users, AI Mode 100M In The US And India [3 min read]

The company also demonstrated strong adoption of AI tools across its ecosystem, including over 9 million developers building with Gemini, 70 million videos created with Veo 3 since May, nearly 1 million monthly users for Google Vids, and over 50 million people using AI-powered meeting notes in Google Meet. To support this unprecedented demand, Google has doubled its monthly token processing from 480 trillion to 980 trillion tokens since May, though investors reacted negatively to the company's plans to increase capital expenditure spending to maintain competitiveness in the AI race.

Threads Adds Improved Content Performance Metrics For Creators [2 min read]

Threads is adding better analytics tools that let creators see detailed information about how their posts are performing, including engagement breakdowns, follower demographics, and where their content is being discovered across Instagram and Facebook. The new features include charts showing content trends over time and geographic data about followers, helping creators understand what type of content works best with their audience. This update comes as Threads is rapidly growing with 115 million daily users (up 128% from last year) while competing with X, which has 132 million users but is actually losing users.

New YouTube Shorts Creation Tools [2 min read]

YouTube is rolling out new AI-powered creation tools for Shorts, starting with a photo-to-video feature that transforms still images from your camera roll into animated videos using creative suggestions, available free in the US, Canada, Australia, and New Zealand. The platform is also introducing constantly updating generative AI effects that can turn doodles into images and create unique video transformations like underwater scenes, accessible through the Effects icon in the Shorts camera. Also, YouTube has launched AI playground, a centralized hub where creators can access all the latest generative AI tools, browse inspirational examples, and use pre-filled prompts to generate videos, images, and music.

Introducing GitHub Spark [10 min read]

GitHub Spark is an AI-powered platform that enables anyone to create personalized micro apps called "sparks" using natural language descriptions, solving the problem that while we have powerful computers, they aren't personalized because creating custom software is traditionally too complex. The platform seamlessly integrates three core components: an NL-based editor with interactive previews and revision variants, a managed runtime environment that automatically handles hosting, data storage, and theming, and a PWA-enabled dashboard for managing and launching sparks across devices. Following a "Unix philosophy for apps," these micro applications are designed to do one specific thing well for personal needs, can be easily shared with others who can use them directly or remix them for their own preferences, and range from practical tools like allowance trackers to creative projects like animated worlds built by children.

How Claude Is Building A Unique Growth Engine Out Of User-Created Apps [14 min read]

Claude's AI-powered apps create a unique growth loop where users build and share functional applications directly within Claude using natural language, and when others want to use these shared apps, they must authenticate with Claude accounts, driving new user acquisition in a self-reinforcing cycle where new users often become creators themselves. Unlike other platforms, Claude's strategic constraints offer creators free hosting, no API costs (since usage counts against end users' Claude subscriptions), and built-in authentication, but they give up user ownership and platform independence, targeting less technical users who prioritize simplicity over control. This represents a new AI-enabled growth model that transforms code into shareable content for distribution, demonstrates how constraints can become opportunities rather than limitations, and shows the importance of aligning incentives across creators, end users, and the platform to create sustainable growth loops that weren't possible before generative AI.

AI Comes Up With Bizarre Physics Experiments. But They Work. [10 min read]

AI is helping physicists design better experiments, including improving LIGO's gravitational wave detector by 10-15% and creating simpler quantum entanglement setups that work better than human-designed versions. The AI comes up with strange, alien-looking designs that initially seem wrong to human physicists, but when tested, they actually work and use clever physics principles that humans hadn't thought to implement. While AI is great at finding patterns in physics data and designing experiments, human physicists still need to figure out why the AI's solutions work and what they mean.

7 Years Of Google Ads Experience In 12 High Impact Lessons [7 min read]

Mastering Google Ads fundamentals (like crafting irresistible offers and implementing clear conversion tracking) is far more effective than chasing advanced tactics. Looking beyond the platform itself—by improving landing pages, unit economics, and developing broader business skills—is where specialists can make their biggest impact as Google Ads becomes increasingly automated. Rather than fighting against Google's algorithms, successful specialists now need to embrace and leverage automation strategically, recognizing that while new features may underperform initially, they typically improve over time.

The Anatomy Of A Breakthrough "Service As A Software" Business [8 min read]

Chargeflow exemplifies a new "Service-as-a-Software" business model, using AI to handle chargebacks on autopilot with success-based pricing of 25% on recoveries only, which has attracted 15,000 merchants since 2022. The company took an unorthodox "GTM-first" approach by focusing on marketing and customer acquisition before building their technology, initially operating with humans-in-the-loop while developing their AI capabilities. Their success was largely driven by strategic distribution through the Shopify and Stripe App Stores combined with an extremely streamlined three-click onboarding process, demonstrating how marketplace presence and ease of use can drive rapid scaling.

Influencer Marketing Campaigns Favor Long Term Partnerships Over One Time Engagements [4 min read]

This shift coincides with brands expanding their influencer networks while specifically targeting nano influencers who have 1,000-10,000 followers, as 62.4% of brands now work with more than 10 influencers. The industry is also seeing a transformation in how success is measured, with views, reach, and impressions becoming the primary metrics for 54.3% of brands, while 80% now track sales from influencer campaigns, all within a market that has grown to $24 billion and sees TikTok leading platform usage at 68.8%.

Why Startup Founders Struggle With Adaptability (And How To Overcome The Challenge) [7 min read]

Despite needing to navigate constant change, many startup founders appear adaptable but are actually rigid and closed-minded, becoming dictatorial, mistrustful, and resistant to feedback while sticking to familiar methods, creating a significant disconnect between their self-perception and how their teams actually view them. This rigidity creates a destructive cycle where founders become anxious, secretive, and controlling, leading to poor team building, inability to delegate, and siloed decision-making, which only increases their stress and reinforces their inflexible behavior patterns. Overcoming these adaptability challenges requires intentional ego management and behavior change, including asking questions instead of making statements, developing comfort with ambiguity, focusing on key priorities, encouraging others to challenge assumptions, delegating more effectively, and addressing underlying stress through self-care and potentially professional help.

Ten AI Safety Project Someone Should Work On [14 min read]

The proposed projects address critical gaps in AI safety infrastructure and oversight, including AI security talent development, technical governance research, real-world monitoring of AI agent behavior, communications support for safety organizations, and independent lab monitoring to track safety practices and hold companies accountable. Beyond technical safety research, practical implementation and societal preparedness are essential through concrete tools like fact-checking technology for better decision-making, economic impact tracking to understand AI's real-world effects, compliance auditing systems, and detailed funding plans to deploy resources effectively when needed.

Beyond The Hype: How AI Is Reshaping The Media Agency Model [7 min read]

While nine out of ten ad agencies claim to be using AI and everyone at Cannes Lions showcased AI-powered demos, there's a significant gap between hype and actual functionality, with many tools failing to work in real-time or provide genuine connectivity between systems, often being mere click-through presentations rather than functional products. Successful AI implementation requires measurable business outcomes like faster campaign setup and improved media performance rather than flashy demos, with the key test being whether tools can seamlessly connect processes without manual intervention like copy-pasting between systems. Leading agencies are finding AI most effective when it handles operational tasks like campaign automation and audience analysis while humans provide oversight and creativity, as the human element remains important for strategic thinking, creative refinement, and adding the unique insights that differentiate brands in the marketplace.

Marketing Mix Modeling: A statistical analysis technique that measures the impact of various marketing activities on sales. It helps determine which marketing efforts provide the best return on investment. This modeling enables better budget allocation across marketing channels.

Example: A retail company uses modeling to determine how much TV advertising versus social media spending contributed to their holiday sales increase.

Growth Hacking: A marketing approach focused on rapid experimentation across different channels to find the most efficient ways to grow a business. It combines marketing, data, and technology to achieve quick results. Growth hacking prioritizes speed and scalability in marketing strategies.

Example: Dropbox grew rapidly by offering extra storage space to users who referred friends, creating a viral growth loop.

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