Oct 3 2025
AMA: Reddit Marketing Veteran Shares What Works On The Platform via @sejournal, @brentcsutoras

Part of our work at OGS Media with Reddit is making it easier for brands to get on the platform the right way: transparent, authentic, and really connecting with your audience. Some of that happens through our partnership, working with various teams at Reddit, testing new features, and sharing insights from the brands we’re currently managing.

Another part of that is through hosting Ask Me Anything (AMAs) like the one I did last week on r/RedditForBusiness.

The questions that came in reminded me why this work matters. After nearly two decades on the platform and working with brands like TikTok, Purple, and Asurion, I see how brands are genuinely trying to figure out Reddit. The AMA drew questions from marketers across industries, from early-stage startups to enterprise brands, all working to understand how to show up authentically.

Let me walk you through the biggest themes that emerged and what actually works on Reddit.

The Biggest Mistake Brands Make (And Why It Happens)

Multiple people asked variations of the same question: “What’s the biggest mistake brands make when they first start marketing on Reddit?”

“Most brands find Reddit through their online marketing teams. They see that Reddit is showing up in Google search results or they see it in LLMs. But when looking at who should give Reddit a try, it still ends up landing in their online marketing teams. Online marketers have been held to ROI numbers for so long, it’s how they look at their engagement on Reddit.

There’s an interest in being on Reddit because it’s popular and important, but there’s not enough time spent understanding why Reddit is important and that’s what I think is the biggest mistake brands make.”

The root problem? Brands need to understand what makes Reddit so powerful in the online user’s journey, how subreddits operate as individual communities with their own rules, culture, and expectations. How the journey to learning and making decisions is as important as the outcome.

When one marketer asked how to avoid the anti-promotional backlash, I explained:

“As for the line between contribution and self-promotion, I think that’s often more of a feeling than a line. It takes understanding the community, what they expect and need, what they appreciate and what they despise. The best marketers know how to ‘read the room’ and know their audience, start with being helpful first, and wait for that moment when what they have to offer is what you’re asking for, so that they’re never selling you something, but rather helping you out with a solution they just happen to have.”

Why Traditional Social Media Strategy Fails On Reddit

A marketer with years of experience asked why traditional social media approaches don’t translate to Reddit success. The answer gets to the heart of what makes Reddit different:

“It really comes down to a large segment of the world wanting to engage in conversation, versus just watching streams for updates and entertainment.

It was long after social media really came out that marketers started really looking at it for the exposure and traffic it could drive. This created two avenues: a megaphone to share information and customer service.

Neither of these helps people who are on a journey to learn something, engage in conversations or discussions around a topic of interest, or to find a solution to a problem they need solved.

Traditional social media doesn’t work here because it is not about conversation, it is about promotion and marketing.”

The fundamental shift brands need to make? Stop thinking about Reddit like Facebook or LinkedIn with stricter rules. Instead:

“Start thinking about Reddit like a networking event, a cocktail party, a social event. How would you approach and engage with an actual event, versus posting content on a social media platform.

It simply comes down to the intent.”

Reddit operates more like walking into a conference where each subreddit is a different breakout session with its own culture, expectations, and unwritten rules. You can’t just grab the microphone and start pitching; you need to listen, contribute, and earn your place in the conversation.

This understanding leads directly to what actually works on Reddit.

The Do’s And Don’ts For Reddit Success

When asked for the top do’s and don’ts, I broke it down to the essentials:

Do:

“Really become a Redditor:

  • Find communities that you are a good fit to belong to (from the Redditor point of view).
  • Focus on engaging and helping Redditors through discussion.”

Don’t:

“Give this task to your marketing team (well, not only your marketing team).

  • Treat subreddits like categories.
  • Focus on KPIs outside Reddit.”

That first “don’t” surprises people, but it’s critical. Here’s the thing: Marketing teams are trained to chase quarterly numbers, to show immediate ROI, to justify every dollar spent. But Reddit operates on relationship timelines, not campaign cycles.

When you hand Reddit to someone who’s measured on conversion rates and cost-per-click, they’re going to treat it like another performance channel. They’ll miss what actually matters, the compound value of becoming part of the conversation, of genuinely helping solve problems, of building trust that turns your brand into the solution people recommend when someone asks for help six months from now.

The real ROI on Reddit isn’t in the traffic you drive this quarter; it’s in becoming the answer that shows up in Google searches and AI responses for years to come because you took the time to build authentic authority in your communities.

How Long Does Reddit Success Actually Take?

This came up multiple times, so here’s the realistic timeline:

“Some of our clients see Reddit become their primary funnel within three months. Some rank with their content prominently within 30 days. Some show up everywhere in LLMs inside six months. Some clients get information that changes their whole business within three months. One very large brand turned around its brand sentiment in about nine months. So it is just dependent on what impact means to you.”

But the general rule: Six to 12 months for meaningful impact, assuming you’re doing it right.

The Product Promotion Question Everyone Asks

One of the most practical questions was how to succeed without actually selling products. I responded:

“Overall, the premise is you don’t sell products on Reddit. You solve problems. Help people with their actual problems, and they’ll ask what you recommend. That’s when you mention your solution. However, some communities do want product posts, like fashion or deal subreddits. It depends on what you’re selling. But the smart move is be helpful first, then run ads where people need your product. You get conversions from ads plus trust from being genuinely useful.”

This is where a lot of brands get tripped up. They think “no selling” means they can never mention their product. That’s not it at all. It’s about context and timing.

What Startups And Enterprise Brands Both Need To Know

Interestingly, questions came from both ends of the spectrum, pre-launch startups and established enterprise companies. The answer was the same for both:

“I think that the pathway for every brand, early stage, prelaunch, or established, should be about understanding what their audience on Reddit really needs from them, what their customers journey through Reddit looks like, and what the opportunities are for the brand to connect with those customers at the right time, with the right conversations, and with the intent to help them move through their journey to completion.”

The process is the same regardless of company size. It takes time, it takes commitment, and it informs the brand what their customers actually need, what they think about the industry, the brand, and its competitors.

The Authenticity Challenge

When someone asked about responding to criticism, here’s the reality check:

“What I will say, is that arguing and getting defensive almost NEVER works. Remember you and the people you are talking with are humans, so what would you do in real life? I never think it hurts to give a quick and honest apology (through DM if needed). Something human. People soften when they realize they are talking to another person.”

This ties back to the networking event concept. If someone called you out at a conference, you wouldn’t start arguing with them in front of everyone. You’d handle it like a human being.

What Should Brands Do In Their First 90 Days On Reddit?

Another practical question that came up was what brands should actually focus on during their first three months on Reddit. Based on our work with enterprise clients, there’s a specific methodology that works.

The biggest temptation for new brands is to jump in and start posting immediately. That’s exactly backwards.

Month 1: Foundation And Discovery

The first month isn’t about your brand at all; it’s about becoming a genuine Redditor. We have our clients’ team members join communities related to their personal interests first. Love cooking? Join r/cooking. Into photography? Find your camera subreddit. This isn’t marketing; it’s learning how Reddit actually works.

Simultaneously, we’re conducting what we call “deep audience immersion.” Before posting a single thing, we spend weeks analyzing subreddit discussions to understand what your audience actually cares about. We map user journeys, identify pain points, and document the language and tone that resonates within each community.

During this phase, we also establish your brand subreddit as a “home base” and create one to two employee accounts for future engagement. But these accounts don’t engage with business topics yet. They’re building karma and credibility in personal interest areas.

Month 2: Authentic Engagement Begins

Month 2 is when we start engaging authentically within your industry communities, but still not promoting anything. Team members begin participating in discussions where their expertise adds genuine value. The key is engaging as knowledgeable individuals who happen to work at your company, not as company representatives.

We’re also developing content during this phase, but it’s all based on real user conversations we’ve observed. Every post, comment, and engagement has a purpose rooted in solving actual problems we’ve seen discussed.

Month 3: Strategic Content And Smart Timing

The third month is when content strategy kicks into high gear, but it’s informed by everything we’ve learned. We map high-traffic discussions and ensure your brand is present when it matters most, without being intrusive.

We call this “smart engagement timing,” appearing in conversations not because we’re pushing an agenda, but because we genuinely have something valuable to contribute.

The Results

This approach works. One client, Devicie, went from relative obscurity to authentic industry credibility within their first quarter. They saw a 2,000% increase in Reddit visibility, 528 total upvotes across community-driven posts, 271% growth in meaningful conversations, and enterprise leads sourced directly from Reddit engagement.

But more importantly, Reddit became an engine for their entire business strategy, informing everything from product development to sales conversations.

The 90-day approach isn’t about quick wins, but rather building the foundation for long-term success that compounds over time.

The Investment Question

Multiple people asked whether Reddit should replace other marketing channels. Here’s the perspective:

“I don’t know that I would ever put all my eggs in one basket, but I would say that for me, and for a lot of people I know in the SEO space, Reddit is a very important investment to make. The largest impact you can have to search right now in my opinion, as well as for LLM search, is to have high quality problem solving discussions that include your brand on Reddit.”

And when someone joked about trends we’ll cringe at in 10 years, the response was simple:

“Questioning whether Reddit is a good investment to make for your brand.”

What This All Means

The questions from this AMA reinforce what I’ve been seeing for years: Brands know Reddit is important, but they’re approaching it with the wrong frameworks. They’re trying to apply Facebook advertising logic to a platform that operates more like a collection of professional associations or hobby clubs.

The brands that succeed on Reddit understand this fundamental difference. They show up as humans first, experts second, and companies third. They solve problems instead of pushing products. They invest time in understanding communities instead of treating them as advertising categories.

Most importantly, they recognize that Reddit success isn’t about gaming the system; it’s about genuinely participating in it. That takes longer than running ads, requires more nuance than posting content, and demands more authenticity than most marketing teams are used to providing.

But for the brands that get it right? Reddit becomes more than a marketing channel. It becomes a competitive advantage that’s incredibly difficult for competitors to replicate.

If you have questions about Reddit marketing, feel free to jump into the original AMA thread or connect with me on LinkedIn, where I post most of my Reddit thoughts.

More Resources:

Featured Image: Courtesy of r/RedditforBusiness

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Oct 3 2025
Turning migration into modernization

In late 2023, a long-trusted virtualization staple became the biggest open question on the enterprise IT roadmap.

Amid concerns of VMware licensing changes and steeper support costs, analysts noticed an exodus mentality. Forrester predicted that one in five large VMware customers would begin moving away from the platform in 2024. A subsequent Gartner community poll found that 74% of respondents were rethinking their VMware relationship in light of recent changes. CIOs contending with pricing hikes and product roadmap opacity face a daunting choice: double‑down on a familiar but costlier stack, or use the disruption to rethink how—and where—critical workloads should run.

DOWNLOAD THE ARTICLE

“There’s still a lot of uncertainty in the marketplace around VMware,” explains Matt Crognale, senior director, migrations and modernization at cloud modernization firm Effectual, adding that the VMware portfolio has been streamlined and refocused over the past couple of years. “The portfolio has been trimmed down to a core offering focused on the technology versus disparate systems.”

Download the full article.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

This content was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

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Oct 3 2025
EV tax credits are dead in the US. Now what?

On Wednesday, federal EV tax credits in the US officially came to an end.

Those credits, expanded and extended in the 2022 Inflation Reduction Act, gave drivers up to $7,500 in credits toward the purchase of a new electric vehicle. They’ve been a major force in cutting the up-front costs of EVs, pushing more people toward purchasing them and giving automakers confidence that demand would be strong.

The tax credits’ demise comes at a time when battery-electric vehicles still make up a small percentage of new vehicle sales in the country. And transportation is a major contributor to US climate pollution, with cars, trucks, ships, trains, and planes together making up roughly 30% of total greenhouse-gas emissions.

To anticipate what’s next for the US EV market, we can look to countries like Germany, which have ended similar subsidy programs. (Spoiler alert: It’s probably going to be a rough end to the year.)

When you factor in fuel savings, the lifetime cost of an EV can already be lower than that of a gas-powered vehicle today. But EVs can have a higher up-front cost, which is why some governments offer a tax credit or rebate that can help boost adoption for the technology.

In 2016, Germany kicked off a national incentive program to encourage EV sales. While the program was active, drivers could get grants of up to about €6,000 toward the purchase of a new battery-electric or plug-in hybrid vehicle.

Eventually, the government began pulling back the credits. Support for plug-in hybrids ended in 2022, and commercial buyers lost eligibility in September 2023. Then the entire program came to a screeching halt in December 2023, when the government announced it would be ending the incentives with about one week’s notice.

Monthly sales data shows the fingerprints of those changes. In each case where there’s a contraction of public support, there’s a peak in sales just before a cutback, then a crash after. These short-term effects can be dramatic: There were about half as many battery-electric vehicles sold in Germany in January 2024 than there were in December 2023. 

We’re already seeing the first half of this sort of boom-bust cycle in the US: EV sales ticked up in August, making up about 10% of all new vehicle sales, and analysts say September will turn out to be a record-breaking month. People rushed to take advantage of the credits while they still could.

Next comes the crash—the next few months will probably be very slow for EVs. One analyst predicted to the Washington Post that the figure could plummet to the low single digits, “like 1 or 2%.”

Ultimately, it’s not terribly surprising that there are local effects around these policy changes. “The question is really how long this decline will last, and how slowly any recovery in the growth will be,” Robbie Andrew, a senior researcher at the CICERO Center for International Climate Research in Norway who collects EV sales data, said in an email. 

When I spoke to experts (including Andrew) for a story last year, several told me that Germany’s subsidies were ending too soon, and that they were concerned about what cutting off support early would mean for the long-term prospects of the technology in the country. And Germany was much further along than the US, with EVs making up 20% of new vehicle sales—twice the American proportion.

EV growth did see a longer-term backslide in Germany after the end of the subsidies. Battery-electric vehicles made up 13.5% of new registrations in 2024, down from 18.5% the year before, and the UK also passed Germany to become Europe’s largest EV market. 

Things have improved this year, with sales in the first half beating records set in 2023. But growth would need to pick up significantly for Germany to reach its goal of getting 15 million battery-electric vehicles registered in the country by 2030. As of January 2025, that number was just 1.65 million. 

According to early projections, the end of tax credits in the US could significantly slow progress on EVs and, by extension, on cutting emissions. Sales of battery-electric vehicles could be about 40% lower in 2030 without the credits than what we’d see with them, according to one analysis by Princeton University’s Zero Lab.

Some US states still have their own incentive programs for people looking to buy electric vehicles. But without federal support, the US is likely to continue lagging behind global EV leaders like China. 

As Andrew put it: “From a climate perspective, with road transport responsible for almost a quarter of US total emissions, leaving the low-hanging fruit on the tree is a significant setback.” 

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

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Oct 3 2025
The Download: RIP EV tax credits, and OpenAI’s new valuation

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

EV tax credits are dead in the US. Now what?

Federal EV tax credits in the US officially came to an end yesterday.

Those credits, expanded and extended in the 2022 Inflation Reduction Act, gave drivers up to $7,500 toward the purchase of a new electric vehicle. They’ve been a major force in cutting the up-front costs of EVs, pushing more people toward purchasing them and giving automakers confidence that demand would be strong.

The tax credits’ demise comes at a time when battery-electric vehicles still make up a small percentage of new vehicle sales in the country. So what’s next for the US EV market?

—Casey Crownhart

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

If you’re interested in reading more about EVs and clean energy, take a look at:

+ The US could really use an affordable electric truck. Ford recently announced plans for a $30,000 electric pickup, which could be the shot in the arm that the slowing US EV market needs. Read the full story.

+ What role should oil and gas companies play in climate tech, really?

+ China is an EV-building powerhouse. These three charts explain its energy dominance. Read the full story.

+ Supporting new technologies like EVs can be expensive, but deciding when to wean the public off incentives can be a difficult balancing act. Read the full story.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 OpenAI has become the world’s most valuable startup
Move aside, SpaceX. (Bloomberg $)
+ OpenAI is now valued at an eye-watering $500 billion. (FT $)
+ The valuation came after workers sold around $6.6 billion in shares. (Reuters)

2 Music labels are close to striking AI licensing deals
Universal and Warner are trying their best to avoid the mis-steps of the internet era. (FT $)
+ AI is coming for music, too. (MIT Technology Review)

3 Facebook’s political ads are full of spam and scams
And deepfake technology is making them more convincing than ever. (NYT $)
+ Meta will start using conversations with its chatbots to personalize ads. (WSJ $)

4 China is forging ahead with integrating AI tools into children’s lives
But educators worry they’ll harm youngsters’ learning and social skills. (Rest of World)
+ Chinese universities want students to use more AI, not less. (MIT Technology Review)

5 The batteries of the future could be created by AI 
Researchers including Microsoft are experimenting with materials suggested by models. (IEEE Spectrum)
+ This startup wants to use the Earth as a massive battery. (MIT Technology Review)

6 A historian claims to have used AI to identify an anonymous Nazi
Digital tools helped Jürgen Matthäus to pinpoint the person photographed beside a mass grave. (The Guardian)

7 The Pentagon is interested in AI-powered machine guns that shoot drones
Steven Simoni’s Allen Control Systems is part of Silicon Valley’s new military pivot. (Reuters)
+ We saw a demo of the new AI system powering Anduril’s vision for war. (MIT Technology Review)

8 One of Saturn’s moons may have once hosted life 🪐
Enceladus has all the necessary keystones to support life, and future missions could uncover it. (Scientific American $)
+ Meanwhile, Blue Origin has won a NASA rover contract. (Wired $)
+ The case against humans in space. (MIT Technology Review)

9 Chatbots exercise all sorts of tricks to keep you talking
They don’t want the conversation to end, a new study has found. (Wired $)

10 What it’s like to become a viral meme
Drew Scanlon, aka “Blinking Guy,” is leveraging his fame for a good cause. (SF Gate)

Quote of the day

“I cannot overstate how disgusting I find this kind of ‘AI’ dog shit in the first place, never mind under these circumstances.”

—Writer Luke O’Neil tells 404 Media his feelings about an AI-generated “biography” of journalist Kaleb Horton, who recently died.

One more thing

A day in the life of a Chinese robotaxi driver

When Liu Yang started his current job, he found it hard to go back to driving his own car: “I instinctively went for the passenger seat. Or when I was driving, I would expect the car to brake by itself,” says the 33-year-old Beijing native, who joined the Chinese tech giant Baidu in January 2021 as a robotaxi driver.

Liu is one of the hundreds of safety operators employed by Baidu, “driving” five days a week in Shougang Park. But despite having only worked for the company for 19 months, he already has to think about his next career move, as his job will likely be eliminated within a few years. Read the full story.

—Zeyi Yang

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)

+ Congratulations are in order for 32 Chunk, winner of this year’s highly prestigious Fat Bear Week competition 🐻
+ Here’s how 10 women artists got their days off to the best start possible.
+ This Instagram account documenting the worldly travels of a cassette player is fab.
+ Brb, I’m off to listen to Arctic Outpost Radio, spinning records from the very top of the world.

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Oct 3 2025
Microsoft says AI can create “zero day” threats in biology

A team at Microsoft says it used artificial intelligence to discover a “zero day” vulnerability in the biosecurity systems used to prevent the misuse of DNA.

These screening systems are designed to stop people from purchasing genetic sequences that could be used to create deadly toxins or pathogens. But now researchers led by Microsoft’s chief scientist, Eric Horvitz, says they have figured out how to bypass the protections in a way previously unknown to defenders. 

The team described its work today in the journal Science.

Horvitz and his team focused on generative AI algorithms that propose new protein shapes. These types of programs are already fueling the hunt for new drugs at well-funded startups like Generate Biomedicines and Isomorphic Labs, a spinout of Google. 

The problem is that such systems are potentially “dual use.” They can use their training sets to generate both beneficial molecules and harmful ones.

Microsoft says it began a “red-teaming” test of AI’s dual-use potential in 2023 in order to determine whether “adversarial AI protein design” could help bioterrorists manufacture harmful proteins. 

The safeguard that Microsoft attacked is what’s known as biosecurity screening software. To manufacture a protein, researchers typically need to order a corresponding DNA sequence from a commercial vendor, which they can then install in a cell. Those vendors use screening software to compare incoming orders with known toxins or pathogens. A close match will set off an alert.

To design its attack, Microsoft used several generative protein models (including its own, called EvoDiff) to redesign toxins—changing their structure in a way that let them slip past screening software but was predicted to keep their deadly function intact.

The researchers say the exercise was entirely digital and they never produced any toxic proteins. That was to avoid any perception that the company was developing bioweapons. 

Before publishing the results, Microsoft says, it alerted the US government and software makers, who’ve already patched their systems, although some AI-designed molecules can still escape detection. 

“The patch is incomplete, and the state of the art is changing. But this isn’t a one-and-done thing. It’s the start of even more testing,” says Adam Clore, director of technology R&D at Integrated DNA Technologies, a large manufacturer of DNA, who is a coauthor on the Microsoft report. “We’re in something of an arms race.”

To make sure nobody misuses the research, the researchers say, they’re not disclosing some of their code and didn’t reveal what toxic proteins they asked the AI to redesign. However, some dangerous proteins are well known, like ricin—a poison found in castor beans—and the infectious prions that are the cause of mad-cow disease.

“This finding, combined with rapid advances in AI-enabled biological modeling, demonstrates the clear and urgent need for enhanced nucleic acid synthesis screening procedures coupled with a reliable enforcement and verification mechanism,” says Dean Ball, a fellow at the Foundation for American Innovation, a think tank in San Francisco.

Ball notes that the US government already considers screening of DNA orders a key line of security. Last May, in an executive order on biological research safety, President Trump called for an overall revamp of that system, although so far the White House hasn’t released new recommendations.

Others doubt that commercial DNA synthesis is the best point of defense against bad actors. Michael Cohen, an AI-safety researcher at the University of California, Berkeley, believes there will always be ways to disguise sequences and that Microsoft could have made its test harder.

“The challenge appears weak, and their patched tools fail a lot,” says Cohen. “There seems to be an unwillingness to admit that sometime soon, we’re going to have to retreat from this supposed choke point, so we should start looking around for ground that we can actually hold.” 

Cohen says biosecurity should probably be built into the AI systems themselves—either directly or via controls over what information they give. 

But Clore says monitoring gene synthesis is still a practical approach to detecting biothreats, since the manufacture of DNA in the US is dominated by a few companies that work closely with the government. By contrast, the technology used to build and train AI models is more widespread. “You can’t put that genie back in the bottle,” says Clore. “If you have the resources to try to trick us into making a DNA sequence, you can probably train a large language model.”

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Oct 3 2025
Agentic Commerce Has Arrived

AI shopping agents, once a combination of novelty and hype, are becoming a viable ecommerce sales channel.

Last month, Google and Stripe announced new shopping and payment processing tools for AI-related purchases.

Standards

Google’s Agent Payments Protocol (AP2) and Stripe’s Agentic Commerce Protocol (ACP) offer a degree of transaction standards for agent-based commerce.

That standard addresses concerns about turning AI-driven discovery into sales while keeping payments safe and authorized.

For example, how does a merchant know if a human authorized an AI agent to make a purchase? Who is responsible if the buyer contests it?

A male and female shopping on a laptop computer

Once a novelty, AI shopping agents are becoming a reality for consumers.

Google’s AP2

AP2 seeks to answer those questions. The protocol provides a framework for authenticating and validating AI-led transactions, enabling banks, merchants, and consumers to trust the outcome.

The solution uses what Google called “tamper-proof, cryptographically-signed digital” mandates with verifiable credentials.

A mandate is a digital contract between the shopper and her AI agent. It proves what she asked the agent to do and under what conditions. That mandate then becomes the evidence that merchants and payment providers can rely on if she disputes the transaction.

AP2 documents the mandate when, for instance, a shopper tells an AI interface to buy a pair of blue, size 10 men’s running shoes. Thus AP2 could be a foundation for agentic commerce that payment networks, regulators, and retailers can accept as legitimate.

Stripe’s ACP

While AP2 focuses on trust and authorization, Stripe’s Agentic Commerce Protocol focuses on turning conversations into transactions. ACP provides merchants with a way to present products, pricing, and checkout information in a format usable by AI agents.

Behind the scenes, Stripe issues a Shared Payment Token that passes payment details from the AI agent to the merchant without exposing the shopper’s credentials. The order itself flows into the merchant’s backend via ACP to be accepted and fulfilled, like any other ecommerce order, which the buyer can return later.

Stripe launched ACP alongside its Instant Checkout in ChatGPT. U.S.-based Etsy sellers are the first participants, with Shopify merchants expected to follow. A shopper asks ChatGPT for recommendations, chooses a product, and completes payment through a Stripe-powered checkout without leaving the chat.

Implications

New technologies often create both opportunities and challenges. For merchants, agentic commerce is no exception.

A promising opportunity may lie in latent demand. Shoppers sometimes want to buy a product, but the item is out of stock, too expensive, or takes too long to ship. A simple search doesn’t result in a sale.

An AI shopping agent could scour dozens or even hundreds of merchant sites and feeds, identifying the proper product at the right price, which the consumer would have otherwise missed. This solves the latent demand.

Yet instantly comparing prices, shipping rates, and product availability across many merchants creates intense competition. That’s the challenge.

It could even lead to platform pressure, where merchants are present on multiple channels — Etsy, Shopify, Amazon, eBay, and others — to access the dozens of AI shopping portals.

Permission Marketing

Imagine a shopper prompting an AI agent to “look for noise-canceling headphones less than $200, and buy them if they go on sale during Black Friday.”

The agent monitors products, validates prices, and executes purchases automatically. The scenario — an AI agent shopping for a human — is futuristic, but is also familiar to those old enough.

In his 1999 book, “Permission Marketing: Turning Strangers into Friends, and Friends into Customers,” Seth Godin argued that interruption marketing — television commercials, display ads, email promos — was losing its effectiveness. Businesses needed consumer consent to build ongoing relationships. Permission, not promotion, was the key.

Shoppers who allowed merchants to execute purchases on their behalf were Godin’s ultimate example of trust.

Agentic Permission

In all likelihood, agentic commerce will depend on the same foundation Godin described a generation ago: trust and consent.

The key will be how ecommerce businesses react when algorithms programmatically select and buy products.

Permission marketing, such as opt-in email, forced merchants to rethink customer relationships. Similarly, agentic commerce could require merchants to prove reliability, value, and transparency.

Success may hinge less on who has the flashiest storefront and more on which merchants provide the cleanest data, fairest pricing, and the most dependable fulfillment for AI agents to recognize.

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Oct 2 2025
Perplexity Launches Comet Browser For Free Worldwide via @sejournal, @MattGSouthern

Perplexity released its Comet browser to everyone today, shifting from a waitlist to free desktop downloads worldwide.

Comet bakes an AI assistant into every new tab so you can ask questions, summarize pages, and navigate without jumping between search results and multiple tools.

Perplexity first introduced Comet in July in a limited release. Since then, the company says “millions” have joined the waitlist, and early users asked 6–18 times more questions on day one.

The move poses a challenge to traditional search engines and browsers by adopting an AI-first approach to web navigation, which reduces the need for multiple searches and the management of numerous tabs.

What Makes Comet Different

At the core of Comet’s functionality is the Comet Assistant, an AI-powered helper that browses alongside users and handles tasks such as research, meeting support, coding assistance, and e-commerce activities.

The assistant appears in every new tab, ready to answer questions or complete actions without requiring users to navigate away from their current workflow.

Unlike traditional browsers where users must open a separate search engine, copy information between tabs, or use multiple tools, Comet integrates assistance directly into the browsing experience. You can ask questions in natural language, and the assistant provides answers drawn from web sources.

Background Assistants

Perplexity also announced Background Assistants today. These assistants work simultaneously and asynchronously in the background, handling tasks without requiring active user supervision.

The Background Assistants join the recently announced Email Assistant, currently available to Max Subscribers. The Email Assistant can be cc’d on email threads to handle scheduling, draft replies, and manage inbox tasks without opening a separate application.

Mobile & Voice Coming Soon

While Comet has been desktop-only since its July launch, Perplexity recently previewed mobile versions for iPhone and Android.

The mobile version will include voice technology, allowing users to interact with Comet assistants through speech rather than typing.

Availability

Comet is now available for free download at perplexity.ai/comet for desktop users.

For tips on using the browser, see Perplexity’s resource hub.

Featured Image: Sidney van den Boogaard/Shutterstock

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Oct 2 2025
W3C Rolls Out A New Evocative Logo via @sejournal, @martinibuster

The World Wide Web Consortium (W3C) unveiled a new logo for the organization that is designed to transcend one language family and expresses abstract qualities like timelessness and reliability. The result is an abstract logo in the familiar blue and white colors, purposely designed to be evocative, to suggest but not concretely explain.

This evocative way of communication is called polysemy, where something can represent multiple related things, depending on the viewers personal experience and subjective interpretation. It’s a valid design choice for an organization that extends around the world and involves people with diverse backgrounds.

Transcending Language Family

The previous W3C logo emphasized the letters and numbers W3C. That works for English users but probably less so for users who speak other languages, especially those who use other kinds of letter scripts, and for people who are oriented to RTL (right-to-left) spelling.

The goal of creating a logo with a “style that transcends a single language family” makes sense for a global organization.

The W3C explains:

“We moved from using distinct letters and numerals in the logo to creating an abstract symbol to represent W3C. We chose a forward-looking style that transcends a single language family. This approach emphasizes W3C’s worldwide connection.”

What Does The Logo Symbol Mean?

What the symbol means requires multiple mixed metaphors. The explanation is that the circle depicts unity and forward motion. The symbol within the circle is a coil, which they explain is openly evocative of many things like a wave, a hand, or DNA. They also say that part of the coil is evocative of a heart.

Screenshot Of New W3C Logo

They essentially chose a symbol that does not represent anything but is evocative of whatever the individual sees in it.

Here’s how it’s explained:

“This circle depicts unity, constant motion, and moving forward. The symbol is a coil, inspired by the concepts of completion and progress reflected in our work. To some, the coil evokes waves — to others, a hand, or the spiral structure of a DNA helix. It has a curl that resembles a heart. This imagery communicates that W3C is the ‘DNA at the heart of the web’.”

W3C Video About The Logo

There is a video that accompanies the logo that helps explain how the logo reflects the mission of the W3C as a global non-profit entity that champions ideals of accessibility, internationalization and so on. Like the logo, it expresses ideas in the form of concepts, expressed in a poetic style.

Part of it explains:

From the very beginning, from a single dot to a complex system, we are open, we are human, we are innovative, we are inclusive, we are for you, we are for everyone.
We champion accessibility.  We champion internationalization.  We champion privacy. We champion security.”

What do you think? Does the new logo work for you?

Read more about the new logo at the W3C:
The World Wide Web Consortium (W3C) adopts a new logo to signal positive changes

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Oct 2 2025
How AI Is Redefining Search And What Leaders Must Do Now via @sejournal, @TaylorDanRW

Artificial intelligence is transforming how people search, discover, and act on information. For chief marketing officers and senior leaders, this is not a question of whether SEO is “dead” but of how to adapt to a new era where visibility spans AI-driven assistants, multimodal tools, and fragmented user journeys.

Two forces drive this disruption: rapid advances in technology and the accelerating adoption of new search behaviors by younger demographics.

As these forces converge, traditional measures of success such as rankings, traffic, and clicks are losing relevance.

What matters now is the ability to understand where visibility is shifting, how decisions are being shaped earlier in the funnel, and how to build adaptive strategies that secure brand presence across an expanding digital ecosystem.

The Disruption At Hand

The launch of ChatGPT marked a tipping point for digital marketing. Within months, generative AI became a mainstream tool, offering users new ways to answer questions, evaluate products, and plan decisions.

Industry debate has since centered on labels such as SEO, GEO (Generative Engine Optimization), and AIEO. But the label is secondary, the disruption is structural.

Gartner predicts that traditional search engine volumes will fall by roughly 25% as users increasingly turn to AI-powered platforms and assistants. While a 25% decline in a base as large as Google’s is still measured in trillions of searches, the shift is enough to destabilize established traffic models.

This does not spell the end of SEO. Instead, it signals a transformation of the internet itself. The way users seek and consume information is changing at the same pace as the technologies that enable it.

Why Visibility Is Changing Shape

Technology Drivers

Search is no longer confined to a search box. Google has introduced Circle to Search, Lens, AI Overviews and AI Mode. Perplexity and ChatGPT are establishing themselves as discovery platforms. Each of these represents a new entry point for user journeys, many of which bypass the traditional search results page altogether.

User Drivers

Younger demographics are accelerating the shift. At Google’s Search Central Live event in Bangkok, new data showed that Gen Z is not abandoning Google entirely in favor of TikTok or other alternatives, as commonly assumed. Instead, they are adopting AI-enabled features inside Google at a higher rate than any other age group. 1 in 10 Gen Z searches already begins with Circle or Lens, and one in five of those searches are commercial in nature.

The implication is clear: The next generation of consumers is interacting with the internet in ways that blend image recognition, voice, video, and AI assistance. Traditional keyword-driven search journeys are being replaced by multimodal, non-linear exploration.

The New Buyer Journey Dark Funnel

For years, marketers described the “funnel” as a linear path: awareness, consideration, decision. Today, that funnel is breaking apart.

AI intermediaries such as ChatGPT, Perplexity, or Google’s AI Overviews are now summarizing, curating, and interpreting information before users ever reach a brand-owned website. In many cases, research and decision-making occur entirely within these intermediaries.

At the same time, peer-generated content plays an outsized role. Reddit threads, product comparison lists, and third-party case studies are being pulled into AI-generated responses.

This ecosystem expands the number of sources that shape perception while reducing the likelihood that users visit a brand directly.

The result is a “dark funnel.” Purchase decisions are being made through fragmented, often opaque pathways that evade traditional tracking tools. For leaders, this means brand influence must extend beyond owned assets to encompass the broader ecosystem where AI models source their information.

Rethinking Organic Success Metrics

For nearly two decades, SEO success was measured through a narrow set of metrics such as keyword rankings, organic traffic, and click-through rates. In the AI-driven search environment, those measures are no longer sufficient.

Three shifts stand out:

  1. Cross-Channel Lift: SEO is often the first point of exposure, even if it does not capture the last click. Google Analytics 4 now makes it possible to measure this by analyzing how many users first encounter a brand through organic search before returning directly, via social, or through paid channels. This reframes SEO as a driver of brand lift across the marketing mix.
  2. Visibility In AI-Generated Citations: Being referenced in AI summaries does not always translate into immediate clicks, but it does influence perception and consideration. Success must account for brand presence within these outputs, even when user journeys bypass the website.
  3. Topic-Level Visibility: AI search retrieves information at a thematic level rather than matching individual keywords. Tracking topic visibility, breadth of coverage, and the quality of source material is becoming more valuable than measuring a single keyword position.

Traditional measures such as “average position” in Google Search Console are increasingly unreliable. AI citations are often recorded as position one, regardless of context, creating a distorted picture of performance.

Strategic Imperatives For Leaders

The changes unfolding in AI-driven search are structural, not cyclical. Leaders cannot treat them as temporary turbulence. Instead, the task is to create resilience and adaptability in marketing organizations by pursuing five imperatives:

1. Audit AI-Driven Traffic And Visibility

Leaders must first establish a baseline of how AI is already affecting their businesses. While AI referrals are still a small share of overall traffic, they represent an emerging channel with unique characteristics.

  • Practical Step: Use GA4 or Looker Studio to segment traffic from platforms such as ChatGPT, Gemini, and Copilot. These sources typically appear under “referral” in analytics, but regex filters can separate them cleanly.
  • Why It Matters: Treating AI traffic as a distinct channel allows organizations to analyze landing pages, conversions, and revenue, rather than dismissing it as “miscellaneous.”
  • Leadership Lens: Framing AI traffic as a channel elevates its importance in boardroom discussions and positions the organization to justify future investments in tooling, content, or partnerships.

2. Track The Market, Not Just Internal Performance

A common misinterpretation is to view every decline in traffic as a failure of execution. In reality, shrinking demand in traditional search is often the root cause.

  • Practical Step: Compare organic and paid impressions for the same set of keywords. If both decline, the issue is demand-side, not execution-side. Layer this with Google Trends to visualize whether volumes are falling market-wide.
  • Why It Matters: This approach reframes the narrative from “our SEO team is underperforming” to “our market is shifting.” This distinction is crucial for maintaining stakeholder confidence.
  • Leadership Lens: CMOs who can separate market-driven shifts from operational gaps will have sharper conversations with the C-suite about resource allocation and risk.

3. Invest In Top-Of-Funnel Presence Across The Ecosystem

AI models increasingly draw from third-party sites, reviews, and community forums when generating responses. This widens the playing field for visibility beyond a brand’s own domain.

  • Practical Step: Build a program to secure mentions in authoritative third-party contexts such as industry directories, product comparison lists, peer forums, and niche communities.
  • Why It Matters: Being present in these external ecosystems ensures that when AI models summarize options, your brand is more likely to appear in the conversation even if the user never reaches your website.
  • Example: For a travel brand, this might mean appearing not only in “best hotel” lists on major sites, but also in Reddit threads, YouTube reviews, and AI-cited blogs.
  • Leadership Lens: Leaders must expand their definition of SEO from domain optimization to ecosystem visibility. This is not an incremental task but a fundamental shift in scope.

4. Rethink The Funnel And Customer Journey

The traditional linear funnel is breaking apart. Users now move through fragmented journeys that blend passive discovery (social, video, peer reviews) with AI-assisted evaluation.

  • Practical Step: Map how AI intermediaries are reshaping specific stages of your funnel. Identify which queries are being absorbed into AI summaries and where direct interaction with your brand is reduced.
  • Why It Matters: In some cases, entire query categories may be “lost” to AI intermediaries. Recognizing these blind spots early allows marketers to find alternative pathways such as social amplification, partnerships, or paid distribution.
  • Example: A B2B software vendor may find that “best CRM for mid-size companies” is increasingly answered by AI summaries citing analyst reports and third-party reviews. To remain visible, the vendor must prioritize those external references rather than relying solely on owned content.
  • Leadership Lens: CMOs must lead organizations to think less about protecting a single funnel and more about orchestrating presence across a patchwork of fragmented pathways.

5. Measure Indirect Value And Cross-Channel Lift

SEO has always influenced channels beyond the last click, but AI disruption makes quantifying that influence more important than ever.

  • Practical Step: Use GA4’s Explore feature to track first-touch organic sessions that later convert through direct, social, or paid channels. Create custom segments that isolate cross-channel lift.
  • Why It Matters: This evidence shows how SEO fuels the broader marketing mix, even if conversions are attributed elsewhere. It strengthens the business case for continued investment in visibility.
  • Example: A retailer may find that 40% of “direct” purchases were first initiated by an organic search session weeks earlier. Without quantifying this, the value of SEO would be understated.
  • Leadership Lens: Demonstrating indirect value reframes SEO from a cost center to a growth driver, positioning CMOs to argue for resources with greater authority.

Closing Note On Execution

These imperatives are not one-time actions. They are ongoing disciplines that must evolve alongside user behavior and technological change. Leaders who embed them into their operating rhythm will be better prepared to adapt strategies, justify investments, and maintain visibility in an AI-led digital economy.

The Leadership Agenda

Understand Your Risk Exposure

Your audience determines your level of risk. Organizations serving younger, consumer-facing segments are already seeing accelerated adoption of AI search tools. For B2B businesses with locked-down environments, the shift may be slower, but it is coming.

Scrutinize Vendor Claims

Acronyms proliferate in times of disruption. What matters is not whether a vendor calls their practice SEO, GEO, or another label, but whether they can demonstrate measurable strategies for sustaining visibility in AI-led ecosystems.

Be Ready To Be Agile

A 12-month static plan is no longer viable. AI search strategies must be adaptive, continuously informed by data, and responsive to new entrants and technologies.

Visibility Beyond Search Requires New Metrics

SEO is not dead. It is evolving into a broader discipline of experience visibility, where brand presence must extend across AI models, multimodal search tools, and fragmented user journeys.

For leaders, the challenge is not to hold onto the old metrics or frameworks, but to recognize how the internet is reshaping itself and to understand we’re starting to tread new ground, and with new ground comes uncertainty and risk.

Those who measure differently, broaden their presence, and align with user-driven change will not only withstand the disruption but also secure competitive advantage in the AI-led future.

More Resources:

Featured Image: SvetaZi/Shutterstock

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Oct 2 2025
Vector Index Hygiene: A New Layer Of Technical SEO via @sejournal, @DuaneForrester

For years, technical SEO has been about crawlability, structured data, canonical tags, sitemaps, and speed. All the plumbing that makes pages accessible and indexable. That work still matters. But in the retrieval era, there’s another layer you can’t ignore: vector index hygiene. And while I’d like to claim my usage of vector index hygiene is unique, similar concepts exist in machine learning (ML) circles already. It is unique when applied specifically to our work with content embedding, chunk pollution, and retrieval in SEO/AI pipelines, however.

This isn’t a replacement for crawlability and schema. It’s an addition. If you want visibility in AI-driven answer engines, you now need to understand how your content is dismantled, embedded, and stored in vector indexes and what can go wrong if it isn’t clean.

Traditional Indexing: How Search Engines Break Pages Apart

Google has never stored your page as one giant file. From the beginning, search has dismantled webpages into discrete elements and stored them in separate indexes.

  • Text is broken into tokens and stored in inverted indexes, which map terms to the documents they appear in. Here, tokenization means traditional IR terms, not LLM sub-word units. This is the backbone of keyword retrieval at scale. (See: Google’s How Search Works overview.)
  • Images are indexed separately, using filenames, alt text, captions, structured data, and machine-learned visual features. (See: Google Images documentation.)
  • Video is split into transcripts, thumbnails, and structured data, all stored in a video index. (See: Google’s video indexing docs.)

When you type a query into Google, it queries these indexes in parallel (web, images, video, news) and blends the results into one SERP. This separation exists because handling “an internet’s worth” of text is not the same as handling an internet’s worth of images or video.

For SEOs, the important point is this: you never really ranked “the page.” You ranked the parts of it that were indexed and retrievable.

GenAI Retrieval: From Inverted Indexes To Vector Indexes

AI-driven answer engines like ChatGPT, Gemini, Claude, and Perplexity push this model further. Instead of inverted indexes that map terms to documents, they use vector indexes that store embeddings, essentially mathematical fingerprints of meaning.

  • Chunks, not pages. Content is split into small blocks. Each block is embedded into a vector. Retrieval happens by finding semantically similar vectors in response to a query. (See: Google Vertex AI Vector Search overview.)
  • Hybrid retrieval is common. Dense vector search captures semantics. Sparse keyword search (BM25) captures exact matches. Fusion methods like reciprocal rank fusion (RRF) combine both. (See: Weaviate hybrid search explained and RRF primer.)
  • Paraphrased answers replace ranked lists. Instead of showing a SERP, the model paraphrases retrieved chunks into a single answer.

Sometimes, these systems still lean on traditional search as a backstop. Recent reporting showed ChatGPT quietly pulling Google results through SerpApi when it lacked confidence in its own retrieval. (See: Report)

For SEOs, the shift is stark. Retrieval replaces ranking. If your blocks aren’t retrieved, you’re invisible.

What Vector Index Hygiene Means

Vector index hygiene is the discipline of preparing, structuring, embedding, and maintaining content so it remains clean, deduplicated, and easy to retrieve in vector space. Think of it as canonicalization for the retrieval era.

Without hygiene, your content pollutes indexes:

  • Bloated blocks: If a chunk spans multiple topics, the resulting embedding is muddy and weak.
  • Boilerplate duplication: Repeated intros or promos create identical vectors that may drown out unique content.
  • Noise leakage: Sidebars, CTAs, or footers can get chunked and embedded, then retrieved as if they were main content.
  • Mismatched content types: FAQs, glossaries, blogs, and specs each need different chunk strategies. Treat them the same and you lose precision.
  • Stale embeddings: Models evolve. If you never re-embed after upgrades, your index contains inconsistencies.

Independent research backs this up. LLMs lose salience on long, messy inputs (“Lost in the Middle”). Chunking strategies show measurable trade-offs in retrieval quality (See: “Improving Retrieval for RAG-based Question Answering Models on Financial Documents“). Best practices now include regular re-embedding and index refreshes (See: Milvus guidance.).

For SEOs, this means hygiene work is no longer optional. It decides whether your content gets surfaced at all.

SEOs can begin treating hygiene the way we once treated crawlability audits. The steps are tactical and measurable.

1. Prep Before Embedding

Strip navigation, boilerplate, CTAs, cookie banners, and repeated blocks. Normalize headings, lists, and code so each block is clean. (Do I need to explain that you still need to keep things human-friendly, too?)

2. Chunking Discipline

Break content into coherent, self-contained units. Right-size chunks by content type. FAQs can be short, guides need more context. Overlap chunks sparingly to avoid duplication.

3. Deduplication

Vary intros and summaries across articles. Don’t let identical blocks generate nearly identical embeddings.

4. Metadata Tagging

Attach content type, language, date, and source URL to every block. Use metadata filters during retrieval to exclude noise. (See: Pinecone research on metadata filtering.)

5. Versioning And Refresh

Track embedding model versions. Re-embed after upgrades. Refresh indexes on a cadence aligned to content changes. (See: Milvus versioning guidance.)

6. Retrieval Tuning

Use hybrid retrieval (dense + sparse) with RRF. Add re-ranking to prioritize stronger chunks. (See: Weaviate hybrid search best practices.)

A Note On Cookie Banners (Illustration Of Pollution In Theory)

Cookie consent banners are legally required across much of the web. You’ve seen the text: “We use cookies to improve your experience.” It’s boilerplate, and it repeats across every page of a site.

In large systems like ChatGPT or Gemini, you don’t see this text popping up in answers. That’s almost certainly because they filter it out before embedding. A simple rule like “if text contains ‘we use cookies,’ don’t vectorize it” is enough to prevent most of that noise.

But despite this, cookie banners a still a useful illustration of theory meeting practice. If you’re:

  • Building your own RAG stack, or
  • Using third-party SEO tools where you don’t control the preprocessing,

Then cookie banners (or any repeated boilerplate) can slip into embeddings and pollute your index. The result is duplicate, low-value vectors spread across your content, which weakens retrieval. This, in turn, messes with the data you’re collecting, and potentially the decisions you’re about to make from that data.

The banner itself isn’t the problem. It’s a stand-in for how any repeated, non-semantic text can degrade your retrieval if you don’t filter it. Cookie banners just make the concept visible. And if the systems ignore your cookie banner content, etc., is the volume of that content needing to be ignored simply teaching the system that your overall utility is lower than a competitor without similar patterns? Is there enough of that content that the system gets “lost in the middle” trying to reach your useful content?

Old Technical SEO Still Matters

Vector index hygiene doesn’t erase crawlability or schema. It sits beside them.

  • Canonicalization prevents duplicate URLs from wasting crawl budget. Hygiene prevents duplicate vectors from wasting retrieval opportunities. (See: Google’s canonicalization troubleshooting.)
  • Structured data still helps models interpret your content correctly.
  • Sitemaps still improve discovery.
  • Page speed still influences rankings where rankings exist.

Think of hygiene as a new pillar, not a replacement. Traditional technical SEO makes content findable. Hygiene makes it retrievable in AI-driven systems.

You don’t need to boil the ocean. Start with one content type and expand.

  • Audit your FAQs for duplication and block size (chunk size).
  • Strip noise and re-chunk.
  • Track retrieval frequency and attribution in AI outputs.
  • Expand to more content types.
  • Build a hygiene checklist into your publishing workflow.

Over time, hygiene becomes as routine as schema markup or canonical tags.

Your content is already being chunked, embedded, and retrieved, whether you’ve thought about it or not.

The only question is whether those embeddings are clean and useful, or polluted and ignored.

Vector index hygiene is not THE new technical SEO. But it is A new layer of technical SEO. If crawlability was part of the technical SEO of 2010, hygiene is part of the technical SEO of 2025.

SEOs who treat it that way will still be visible when answer engines, not SERPs, decide what gets seen.

More Resources:

This post was originally published on Duane Forrester Decodes.

Featured Image: Collagery/Shutterstock

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