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Tag: AI

Unlock AI Insights with Google’s New Ads DevCast for Developers

I’ve been eagerly following the latest developments from Google, and their new Ads DevCast is truly a groundbreaking resource for developers like me. This initiative offers technical insights into Google Ads and highlights how AI-driven changes are transforming ad APIs.

The new show is hosted bi-weekly by Cory Liseno, as part of the Google’s Advertising and Measurement Developer Relations team. Ads DevCast focuses on deep technical dives across key tools like Google Ads, Google Analytics, and Display & Video 360. It feels like a direct line to the experts who are constantly innovating in our field.

What’s interesting here is that Ads DevCast complements Ads Decoded, which is more about campaign strategy, hosted by Ginny Marvin. It’s specifically designed with us developers in mind, highlighting the need for a specialized approach to understanding these platforms.

The first episode, intriguingly titled “MCPs, Agents, and Ads. Oh My!”, delves into the “agentic shift” that Google is observing. With AI agents becoming the main users of ad APIs, this shift is something we’re all keenly interested in.

For those of us deeply involved with Google’s ad tools, Ads DevCast is an invaluable resource. It helps us stay ahead of technical evolutions, discover new capabilities quickly, and build efficient integrations in a landscape increasingly dominated by AI.

I see Google broadening the horizon from a niche “Ads Developer Community” to a wider “Ads Technical Community.” This change allows marketers to carry out technical tasks without needing exhaustive development cycles.

As a pilot project, Ads DevCast is still very much in development, and Google is actively seeking feedback from us to refine future episodes. It’s exciting to know we can influence its direction.

This initiative reinforces Google’s commitment to keeping us in the loop with their latest innovations, enabling us to adapt quickly and effectively in an AI-first world. Check out Ads DevCast if you haven’t already!

Inspired by this post on Search Engine Land.

March 20, 2026
Boost Your Google Business Profile with AI-Driven Review Replies
I’ve been intrigued by Google’s latest test in the Google Business Profile: AI-generated responses to customer reviews. This innovative tool offers businesses the ability to create suggested replies to reviews, which I can then review, tweak, and manually submit.

Why It Matters to Me. Engaging with customer reviews significantly impacts conversions and trust. However, I’m aware of the risks associated with generic AI replies, especially for negative reviews where sincerity is crucial. Personalized, quality responses are more influential than merely replying for the sake of it.

What I Saw. Here’s a sneak peek of how the feature appears:

The Details I’ve Discovered. It seems Google is conducting a limited roll-out of this ‘Reply to reviews with AI’ feature within the Google Business Profile.
- It generates proposed responses to customer reviews.
- I can review and modify these suggestions before submitting.
- The availability fluctuates across different accounts and reviews.
- The feature is spotted in the U.S., Brazil, and India, but not yet widely in Europe.
Initial Impressions. Some users, like me, noticed prompts targeting older, unanswered negative reviews.
- In one test I observed, it’s possible to generate AI responses in bulk.
- I’ve read mixed reports on automation—some claim bulk responses still need a review, while others experienced fully automated replies that require no edits.
How I First Learned About It. This feature caught my attention first through LinkedIn, thanks to Chandan Mishra, a freelance local SEO specialist, and it was further amplified by Darren Shaw, founder of Whitespark.

Inspired by this post on Search Engine Land.
March 20, 2026
AI Bots Could Dominate Internet Usage by 2027

I recently heard Cloudflare CEO Matthew Prince predict a fascinating future where AI bots might outnumber us humans on the web by 2027. The surge of agent-driven browsing, paired with the rise of generative AI, could really shake things up online.

During his talk at SXSW, Prince warned us that bots are already transforming how we use and monetize the internet. This got me thinking about the big shift in search as more people rely on AI-generated answers instead of traditional clicks.

Why this matters to me. With the prospect of bots becoming the main users of the web, I’ll need to adapt my strategy. Ensuring AI systems can access and trust my content will be crucial for staying relevant.

Details from Prince. According to Prince, AI agents collect far more information than we do because of their unique browsing habits. While I might visit five sites for a purchase, an AI could browse thousands, generating significant traffic and load.

Prince also pointed out the rapid changes in the internet’s baseline.

He said that, for a long time, about 20% of web traffic was from bots, but by 2027, this could surpass human traffic.

This isn’t a sudden spike, like during COVID-19; it’s a steady increase with no signs of slowing down.

The broader implications. Prince compared this shift to other digital transformations, like mobile and social media. However, the difference here is profound: users may stop visiting websites directly, relying instead on AI interfaces for aggregated answers.

The traditional business model of attracting traffic and selling through ads is under threat. After all, bots don’t click on ads, and customers are more likely to trust an AI’s output without further clicks.

AI sandboxes. I found Prince’s vision of “AI sandboxes” particularly intriguing. These temporary environments for AI agents could appear and disappear millions of times per second, impacting how computing works behind the scenes.

Such changes will undoubtedly put sustained pressure on our internet infrastructure as traffic continues to grow.

Business ramifications. Companies are already debating how to adapt to AI’s influence, and there’s no clear consensus yet. Prince highlighted how the nature of bots might sever the direct relationship between businesses and their customers, as bots don’t prioritize brands.

For content creators like me. AI can be both a challenge and an opportunity. It might reduce direct traffic, challenging ad-based models, but it also creates demand for unique, original data, which AI companies may pay for.

Local media could thrive by licensing specific content to AI companies, potentially earning more than through digital ads.

For small businesses. Prince put it wisely: AI agents prioritize price, quality, and efficiency over brand loyalty. This means traditional trust shortcuts might not hold any longer, driving towards relentless aggregation.

Future considerations. The next era hinges on finding ways to balance control and compensation for content producers and providers. In Prince’s words, “There has to be some exchange of value.”

The fundamental question remains unanswered: what will be the future business model of the internet?

For more insights, check out the SXSW interview: The Internet After Search.

Inspired by this post on Search Engine Land.

March 20, 2026
Harness Google Search Console Data with Profound Agents

I’m excited to share that I can now effortlessly integrate Google Search Console data directly into any of my Profound Agents. This powerful combination, uniting Search Console insights with Profound’s answer engine data, is transforming how I handle reporting, content creation, monitoring, and optimization.

Staying on the Profound platform makes the entire process seamless, allowing me to focus on what truly matters—building and optimizing my digital strategies without the hassle of platform switching.

Inspired by this post on Try Profound Blog.

March 20, 2026
Why Walmart’s ChatGPT Checkout Fell Short: Key Insights

When I first heard about Walmart’s experiment with ChatGPT’s Instant Checkout, I was intrigued. But after testing 200,000 items, Walmart discovered that conversions through this method were three times lower compared to their website.

Why This Matters: This experiment highlights an important point: traditional shopping environments still hold the crown when it comes to conversions. Even in a world dominated by AI, guiding users to owned environments proves more effective.

The Experiment Details: Starting last November, Walmart introduced around 200,000 products available for purchase directly inside ChatGPT through OpenAI’s Instant Checkout. The goal was to let users buy items without ever leaving ChatGPT.

Daniel Danker, Walmart’s EVP of Product and Design, revealed that these purchases had a conversion rate one-third lower than similar transactions on their website. He described the experience as “unsatisfying,” which prompted Walmart to reconsider their approach.

Farewell to Instant Checkout: Originally, Instant Checkout aimed to complete transactions within ChatGPT. However, OpenAI recently confirmed plans to phase it out, leaning towards merchant-handled app checkouts.

Changes on the Horizon: Walmart plans to integrate its own chatbot, Sparky, within ChatGPT. This will allow users to log into Walmart’s system, sync their carts across platforms, and finalize purchases seamlessly.

A similar integration with Google Gemini is expected next month, broadening Walmart’s technological reach.

The WIRED Report: For those interested in the comprehensive story, WIRED provides further insights into how Walmart and OpenAI are revolutionizing agentic shopping (subscription required).

Inspired by this post on Search Engine Land.

March 19, 2026
Discover iOS Comet Browser: Blending Google Search & AI Excellence

I’ve recently discovered Perplexity’s innovative Comet browser for iOS, which defaults to Google Search. It makes perfect sense, given that mobile users typically focus on navigating, finding local results, and completing transactions. As Perplexity CEO Aravind Srinivas points out, “Google does a much better job … than anyone else … including Perplexity.”

Comet for iOS. This browser integrates Perplexity’s AI assistant directly, providing a seamless experience. It cleverly merges AI-generated answers with standard search outcomes, so for numerous queries, you won’t miss the familiar results page.

While browsing, I can query using my voice, which is incredibly convenient. The assistant’s capabilities include summarizing entire pages, answering questions, and even drafting emails on my behalf.

One feature I find particularly useful is Deep Research, which generates cited summaries and prepares materials tailored for serious inquiry.

What Comet does. The assistant can take action on my behalf. Among other things, it excels at summarizing articles and sharing outputs, researching people or topics across tabs, and assisting with bookings or filling out forms. It’s like having a digital personal assistant ready at all times.

What Perplexity is saying.

“The search experience in Comet iOS provides traditional search result pages for fast, local, and high-intent queries that are more common on mobile. Meanwhile, the Comet Assistant easily allows for more advanced knowledge and intelligence powered by the Perplexity answer engine. The intention is for users to have the smoothest browsing experience possible for the real use cases of iOS.”

Why we care. As search continues to evolve towards hybrid models, optimizing for both traditional Google results and AI-generated responses becomes crucial. This shift underscores Google’s stronghold in commercial and local search, while driving the competition into the AI domain.

The announcement. Comet is Now available on iOS

Inspired by this post on Search Engine Land.

March 19, 2026
Google Revolutionizes Shopping with AI-Powered Protocol Updates

As I delve into the latest updates from Google, it’s clear that the company is advancing its Universal Commerce Protocol (UCP) to revolutionize AI-driven shopping experiences.

The UCP update is not just about ads anymore; it’s about the rich product data that will shape visibility and drive sales.

Google is making significant strides in supporting ‘agentic commerce’ by enhancing its infrastructure with new UCP capabilities. These updates will simplify retailers’ integration processes.

Google highlights how the UCP, an open standard aimed at connecting retailers to AI-driven shopping experiences, is evolving. This transformation seeks to emulate the feel of traditional storefronts even when purchases are done through automated agents.

What’s New: The focus is on creating more functional and flexible shopping experiences via AI agents.

The new cart feature allows AI agents to compile multiple products from a single retailer into one basket, making it resemble the typical shopping experience.

Additionally, the catalog capability enables agents to access real-time data about products, including pricing, inventory, and variants, ensuring accuracy and responsiveness in shopping interactions.

Significantly, the identity linking feature preserves benefits such as member pricing and free shipping across platforms linked by UCP, enhancing the shopper’s experience beyond the retailer’s native site.

Why I Care: With this update, the shift toward AI-driven, agent-led shopping becomes more pronounced. Services like Search and the Google Gemini app might choose and purchase products on users’ behalf, making the quality of product data critical for visibility. Simplified onboarding and support from major platforms could mean quick adoption and an advantage for early adopters.

Zooming Out: UCP is a modular system, allowing retailers and platforms to adopt capabilities selectively rather than all at once, offering flexibility as the industry gauges the extent of control to cede to AI shopping.

Google’s Strategy: Google is set to integrate these capabilities into its ecosystem, including AI-enhanced experiences in Search and the Google Gemini app. To encourage wider adoption, Google plans to simplify the onboarding process within Merchant Center soon.

The Bottom Line: Google’s UCP is evolving from a concept into a broad ecosystem, enhancing capabilities while easing adoption. By doing so, Google is positioning agent-driven commerce as a compelling choice.

Inspired by this post on Search Engine Land.

March 19, 2026
Discover Google’s Personal AI Now in Search, Gemini & Chrome
I’ve got some exciting news to share about Google’s latest developments! They’re expanding their innovative Personal Intelligence feature across AI Mode in Search, the Gemini app, and in Chrome—specifically for U.S. users.
Google’s Personal Intelligence now moves beyond its beta phase, reaching more everyday users. It’s an exhilarating step toward a truly personalized search experience, thanks to clever use of first-party data like Gmail and Photos. This shift makes search outcomes more personalized and unique, especially in AI Mode, where results adapt to individual user behaviors, previous purchases, and search histories.
Why I care
Google’s push into personalized search fascinates me. It’s creating a landscape where search results become increasingly individualized, but consequently harder to predict or replicate.
The details
Personal Intelligence will now function across:
- AI Mode in Google Search (available now in the U.S.)
- Gemini app (currently rolling out to free users)
- Gemini integrated in Chrome (ongoing rollout)
How it works
I can connect applications such as Gmail and Google Photos, allowing Google to give me personalized responses. Some of the cool examples I’ve come across include:
- Shopping suggestions rooted in my buying habits and favorite brands.
- Tech troubleshooting aided by receipt details for the exact devices.
- Travel tips tailored to my flight schedules and past getaways.
- Custom itineraries and local recommendations.
- Hobby proposals based on my interests.
Availability
It’s worth noting that these features are reserved for personal Google accounts and won’t extend to Workspace users—for now, at least.
Want to know more?
You can check out the details on the ad-free promise Google made for AI Mode users here.
Catch-up quick
Originally, Google introduced Personal Intelligence for Gemini subscribers in January with limited access to AI Pro and Ultra users. At that point, it hadn’t been integrated with Search—something they’ve since rectified.
- Initially, the feature was optional and off by default.
- New updates deliver on Google’s plan by making it part of Search AI Mode.
- They’re rapidly expanding access to more users, even for free accounts.
- Plus, it’s now merging into Chrome.
Privacy and control
Google emphasizes user choice:
- Opt-in is required to connect apps like Gmail.
- Users can enable or disable connections whenever they choose.
- Importantly, Gmail and Photos content isn’t directly used to train AI models.
- However, Google may use limited data like prompts and responses to enhance their systems.
For further reading, check out Google’s blog post on this impressive expansion of Personal Intelligence here.

Inspired by this post on Search Engine Land.
March 17, 2026
How Google’s Universal Commerce Protocol Transforms Search

When I learned about Google’s latest protocol, I realized how significant this new development could be for those of us in ecommerce. Google’s Universal Commerce Protocol (UCP) is here to revolutionize how purchases are made within the Gemini and AI search environments. It allows users to make purchases without ever leaving Google’s interfaces, which changes the game for search conversions.

As Google introduces AI Overviews, AI Mode in Search, and the Gemini ecosystem, a new challenge presents itself: how do users get answers and complete purchases seamlessly within Google’s spaces? That’s where UCP comes in, currently in its beta phase.

UCP is a tool designed to help brands reach customers directly within the Gemini or Language Learning Model (LLM) environments. It allows consumers to finalize transactions, earning reward points, and completing checkouts, all within the LLM. Imagine telling Gemini, “Find me a highly rated, waterproof hiking boot in size 10 under $200 and buy it,” and watching as UCP makes that transaction happen smoothly.

At its heart, UCP standardizes the communication between consumer AI interfaces and merchant checkout systems. Although Google’s developer documentation might mention terms like “Model Context Protocol (MCP)” and “Agent2Agent (A2A) interoperability,” the process is actually user-friendly:

UCP leverages your existing Google Merchant Center shopping feeds. It ensures you remain the merchant of record, thus preserving your customer relationships and data. Plus, by integrating checkout within Google’s AI ecosystem, it minimizes cart abandonment and boosts conversions.

Explore further: How Google’s Universal Commerce Protocol changes ecommerce SEO

Implementing UCP involves enhancing your shopping feed management and staying updated on best practices. Google’s guidelines suggest focusing on feed data hygiene, conveying trust signals, and upgrading your technical infrastructure.

To excel in this new system, it’s crucial to detail your product listings accurately and ensure comprehensive descriptions. Trust and convenience become paramount as AI-driven decisions heighten consumer’s purchasing confidence. Providing data on free shipping, return policies, and reliable pricing can make a difference.

Finally, preparing for UCP means keeping pace with technological updates and future tools. Venture into Google’s pilot programs and explore features like Business Agents or Direct Offers to stay ahead in this evolving landscape.

The evolution of search into a transactional engine within LLMs is undeniable. UCP offers a clearer path from search discovery to purchase conversion, and it’s up to us to adapt and thrive in this shift by ensuring our product data is impeccable.

Inspired by this post on Search Engine Land.

March 17, 2026
LinkedIn’s LLM-Powered Algorithm: Transforming Your Feed Experience
When I think about how often I scroll through LinkedIn, I’m excited to share that the platform is launching a cutting-edge AI-powered feed ranking system. It’s designed to analyze what we post, read, and engage with, thanks to large language models and advanced GPUs. This innovation aims to provide more personalized content updates for its vast user base of 1.3 billion.
Why this matters to me. Understanding LinkedIn’s content surfacing process can be a game-changer for anyone wanting their posts—or their brand’s—to gain visibility. The focus is on what’s relevant and engaging within our network. As LinkedIn Tweaked their system, posts that show expertise and contribute to trending professional topics have a better chance to go viral, regardless of our existing connections.
What’s under the hood. LinkedIn has revamped its feed recommendation mechanism using large language models and sophisticated transformer models, all powered by GPU infrastructure. The overhaul targets two key functions: the retrieval and ranking of relevant posts in our feeds.
Unified retrieval system. One of the most intriguing aspects for me is how LinkedIn has consolidated its discovery processes into a single model powered by LLMs (large language models). Previously, posts could come from various sources such as network activity and trending topics. Now, LinkedIn uses LLM-generated embeddings to interpret post content and align it with our professional interests.
For instance, by engaging with posts about small modular reactors, I might see content linked to renewable energy or other related fields, even if they use different terminology.
Ranked by your interests. Once posts are retrieved, LinkedIn ranks them utilizing a transformer-based sequential model. Instead of looking at posts individually, the model examines patterns in my past interactions, including likes, comments, and the time I spent viewing content.
This helps LinkedIn adapt to my evolving professional interests and recommend content that aligns with these shifts.
System performance and architecture. Powered by a GPU infrastructure that processes millions of posts, this system keeps our feeds fresh.
LinkedIn reports that this system can refresh content embeddings in mere minutes and retrieve suitable candidates in under 50 milliseconds.
Enhancing feed quality and authenticity. LinkedIn has also announced updates aimed at boosting content quality:
- Addressing automated engagement. They’ve started cracking down on tools that automate comments or use engagement pods to fake discussions. LinkedIn clarifies these violate platform policies and devalue genuine interactions.
- Cutting down on engagement bait and generic content. The platform will deprioritize content designed solely to provoke comments or clicks—such as posts begging for comments to inflate reach, irrelevant video-text pairings, and regurgitated thought-leadership content.
- Helping newcomers customize their feeds faster. New users can now utilize the “Interest Picker” during signup to select topics of interest, whether it be leadership, career growth, or job-seeking skills, ensuring relevance from day one.
Inspired by this post on Search Engine Land.
March 16, 2026

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