Unilever Drops $1B on Grüns (A 3-Year-Old Gummy Brand!)

Pranav: I still can’t believe this one. Have you heard of Grüns? The founder, Chad, started this green gummy supplement company in a Stanford dorm room, and just three years later, Unilever acquired them for $1 billion. They rapidly hit over 1 million customers and 10 million daily gummy shipments by early 2026. What blew my mind is that they didn’t just stick to DTC—they nailed retail distribution early on, getting into Target, Walmart, and Sam’s Club. It’s a masterclass in strong, disciplined marketing and distribution.

Austin: It really is wild. To put it in perspective, they hit $20 million in revenue with just two employees at one point. We’re living in an era where sweeping, multi-million dollar businesses run by a handful of people are just waiting to be activated by a greater power. If you’re a scrappy marketer with a good instinct, what a fantastic time to be alive!

OpenAI’s $150 Billion Ad Engine & Self-Serve Launch

We can’t let you leave without talking about the wildest slide leaked from OpenAI’s recent pitch deck. They are projecting $100 billion in advertising revenue by 2029, and a staggering $150 billion by 2030. To get there, they are officially rolling out their self-service ad platform for ChatGPT this week. Austin and I are definitely going to spend this weekend testing out the self-serve platform for GTMN to see what it can do.

It’s absolutely wild when you consider they might already be pulling in $30 billion in revenue this year. If you’re a marketer, you need to carve out some “experimental” budget for this immediately. OpenAI just ran a six-week ad pilot that generated $1 million, and the craziest part is that users reported fewer than 7% of the ads as “low relevance”. That’s a vastly better sentiment score than we see on traditional social media. Just be prepared for some potential underspending right now, as OpenAI is still carefully calibrating their ad density.

HubSpot’s “Outcome-Based” Pricing for Breeze AI

HubSpot officially launched a new billing model for its Breeze AI agents. Instead of traditional “SaaS-by-the-seat” pricing, they are moving to “Agent-by-the-Outcome,” meaning you only pay when the agent successfully completes a task, like qualifying a lead or resolving a support ticket. I’ve really thought about this—qualifying a lead is arguably more of a usage-based action than a true outcome (like closing a sale), but it’s an incredibly fascinating shift.

It creates a new performance standard for AI vendors. If the agent fails to deliver a tangible result, the software cost is zero. RevOps leaders definitely need to audit their seat-based licenses to see if this new model is a more efficient path for their teams.

Google’s “AI Max” is the End of Exact Match Copy

If you run search ads, listen up. Google’s “AI Max” for Search has moved from beta to universal availability. This suite uses LLMs to autonomously generate and customize text ad copy in real-time based on user queries and historical behavior, instead of just rotating fixed assets. The craziest part? Google is reporting a 14% average conversion lift for accounts transitioning to AI Max.

It’s signaling the end of exact match copy strategies. Moving forward, the competitive edge isn’t going to be about writing the copy itself; it’s going to be about prompt governance. If you’re not good at defining the guardrails and brand voice that the AI Max engine follows, you’re not going to have an edge in the auction.

Amazon & Samsung Launch One-Click TV Ads

The “living room” is officially a direct point of sale. Amazon Ads partnered with Samsung to bring remote-purchasable, one-click video ads to Samsung TV Plus starting this summer. You can literally click “Add to Cart” directly on your TV remote during an ad, and it goes straight to your Amazon account. I’m genuinely stoked for this—especially if it knows I’m out of toilet paper while I’m eating dinner on the couch.

It totally collapses the funnel from awareness to conversion in a single session. Plus, the measurement loop will be incredible since advertisers can track the exact transaction.

The Cutting Room Floor (What Didn’t Make the Pod)

We also had a few massive stories this week that we didn’t have time to cover on the show. Here’s a quick summary of the other AdTech news making waves:

• Meta Launches “Muse Spark”: To fight “AI Hallucinations” and “Creative Fatigue” in automated campaigns, Meta debuted Muse Spark. It’s a purpose-built model designed to integrate human-centric creative feedback into the AI ad generation loop, ensuring ads resonate with actual cultural nuances.

• The 2026 AI Governance Gap: A new industry study revealed that while 99% of marketers are using AI, a shockingly low 14% of organizations are actually “AI-Ready” to run autonomous agents at scale. Expect 2026 to be the year of the “AI Audit” as teams shift budgets from buying new tools to fixing their data infrastructure to prevent “shadow AI” security risks.

That’s a wrap for this week! Keep testing your offers, refining your prompts, and we’ll see you on the next episode of GTMN.

From landmark platform addiction lawsuits to the realization that 5% “stat sig” is a myth, we’ve got a massive week of Go-To-Market and Marketing news to cover.

The CMO of Meta Drops the Playbook

We kicked off the show discussing Alex Schultz, the VP of Analytics and CMO at Meta, who recently shared his seven golden rules for marketers on LinkedIn. His advice? Prioritize behavioral targeting over demographic targeting, personalize every ad, invest in data quality, and ruthlessly use exclusion lists.

See the full post here.

“Do you know how many companies I have talked to where like they could be saving millions of dollars and doing a lot better if all they did was point an audience targeting list at Meta or Google as an exclusion... setting up an exclusion list is very easy to do now with Claude.” — Austin

The Breaking Point for Platform Addiction

Meta and Google were just hit with a $6 million jury award in Los Angeles in a landmark case alleging they intentionally built addictive platforms. While $6M is couch change for them, it follows a $375M verdict in New Mexico. Expect platforms to proactively tone down aggressive notifications and infinite scroll features in 2026 to mitigate massive class-action risks. To combat this screen addiction for the next generation, we’re actually keeping our eyes on startups like Tincan” which is literally reinventing the wall-mounted landline for kids.

Google’s SpamBrain AI & The Rise of “IRL Content”

Google just concluded its March 2026 Spam Update in a record-breaking 20 hours. The target? Mass-produced AI text and scaled content abuse. Sites hit by SpamBrain no longer have a “recovery window”; they have to demonstrate months of compliance before regaining search visibility. As search engines get better at detecting AI slop, the most valuable strategy is slowing down and prioritizing real-world, human interactions.

“If you’re not recording all of your conversations and thinking about ways to turn it into content you’re just like leaving free stuff on the table... The inspiration for that is coming from a real interaction and that itself is valuable because that stuff is not reproducible by an AI.” — Pranav

OpenAI’s Hyper-Local Threat to Google

OpenAI has quietly added opt-in location sharing to ChatGPT. This is a massive step toward challenging Google in “Near Me” Local Search. Generative Engine Optimization (GEO) is no longer just for global brands; local businesses must ensure their schema and citations are being picked up by GPT’s local crawler.

The AI Infrastructure Debt Reality Check

While 70% of e-commerce brands prioritize optimizing spend, only 8% are actually using AI for campaign optimization, revealing a massive “AI Adoption Gap”. Furthermore, nearly 45% of MarTech AI agents are currently failing to meet performance marks. The issue isn’t the AI itself; it’s that most stacks weren’t built for the “Decision Speed” that autonomous agents require, and data pipelines are still too siloed or slow.

Unilever’s Hiring Freeze & Q2 Ad Spend

CPG giant Unilever announced a three-month global hiring freeze citing regional conflicts in the Middle East and economic uncertainty. As one of the world’s largest advertisers, this signals a potential tightening of ad budgets for Q2 2026, which may lead to lower CPMs across social platforms. For those with capital in Q2, this could be a prime opportunity for arbitrage.

The Big Lie: Why 5% Stat Sig is Arbitrary

We had to laugh at a recent realization making the rounds on X: the 5% threshold for Statistical Significance is basically a 100-year-old arbitrary convention made up by a guy named Ronald Fisher in the 1920s. Business leaders use “stat sig” as an absolute truth, but in reality, it’s just a social compromise.

“Think about all the times in our careers when we’ve heard the term stats sig and people just like using that as a rubric to make decisions... all business leaders that static [stat sig] has just made up and please use your brains.” — Pranav & Austin

We couldn’t fit everything into the podcast this week. Here are other critical items that GTM professionals need to know:

• Meta Debuts “Catalog-to-Video” AI Tools: Meta is expanding “Reels Trending Ads” to specific cultural moments (like Formula 1) and launching AI tools that automatically transform static product catalog images into high-performing video ads. They are directly challenging YouTube by offering guaranteed event-based reach.

• Google Ads Expands Loyalty Program Integration: Google is now allowing retailers to surface member-only pricing directly in search ads. First-party loyalty data is now a primary AdTech signal, and brands that fail to integrate their rewards programs into Google Merchant Center will lose high-intent conversions.

• Google Ads “AI Mode” Officially Opens: Google has transitioned its conversational “AI Mode” into a monetized shopping environment. Sponsored listings will now appear below organic conversational suggestions. Advertisers must align their product feeds with Google’s new multi-channel product ID consistency standards to participate, officially moving search from a “list of links” to a “guided conversation”.

That’s it for this week. Make sure your data pipelines are clean, your exclusion lists are updated, and we’ll see you next week!

Here is what we are tracking this week.

The Local AI Workflow Revolution (Austin’s Corner)

We are moving so fast that people are missing the obvious superpowers right in front of them. Case in point: Claude Code. Austin has been using the -rc (remote connection) command to start local Claude sessions on his Mac that are accessible via the Claude mobile app over the internet.

Instead of paying thousands of dollars for API tokens via cloud services, you can just set your Mac to never sleep and run a local server. You can write out PRDs in a Linear board on a Saturday, feed them to your local “Claudebot,” and let it direct Claude to act as an autonomous worker overnight. The barrier to creating your own personal, 24/7 autonomous dev team is basically zero.

Agents, E-Commerce, and the Law

There has been massive whiplash regarding Perplexity’s shopping agents. A federal judge initially banned Perplexity from placing Amazon orders, protecting Amazon’s ad-supported discovery layer, but an appeals court just reversed that ban, declaring temporary “open season” on agentic shopping.

Will AI agents just buy things for us seamlessly? Pranav notes that while it’s tempting to let Gemini or Claude just execute an order directly, we will likely see a “human-in-the-loop” approval button for the foreseeable future. Until trust is absolute, users will want a push notification or 2FA prompt before an agent spends their money. And trust is an issue—we’ve already seen bad actors inject malicious code into Python libraries recommended by AI coding tools to steal AWS keys. Guardrails are still mandatory.

AdTech Goes Full Autonomous

The major platforms are stripping away manual controls at breakneck speed:

• Google’s Mandatory AI Voice-Overs: Starting March 20th, Google Ads is automatically layering AI-generated voiceovers onto Performance Max video ads. Advertisers were given a mere 10-day window to opt out before Google defaults to synthesizing audio from your headlines.

• Amazon’s Creative Agent: Amazon launched an autonomous tool that scans product reviews and features to instantly generate creative briefs and video storyboards for Prime Video.

• WPP’s Outcome Pricing: The traditional agency “billable hours” model is dying. Holding giant WPP is shifting to an “Outcome-Pricing” model for its AI services, offering fixed-cost performance guarantees based on actual sales or leads generated using its WPP Open AI platform.

Webflow vs. Claude Code: The CMS Debate

Webflow just acquired Vidoso (an AI video company) to help users generate SEO-optimized video assets, which perfectly times with Google’s global rollout of “Multimodal Indexing”—meaning Google now indexes video and audio at the same depth as text.

But it brings up a larger debate: do solo founders and marketers even need Webflow or Framer anymore? Austin argues that writing code with Claude is now easier than navigating the bloated interfaces of modern CMS platforms. Pranav pushes back, noting that for larger teams dealing with complex staging-to-production environments and caching issues, a proper CMS foundation is still required to prevent breaking live workflows.

Will AI Replace Marketers?

Salesforce and HubSpot are now forcing agency partners to specialize in AI deployment. But does knowing how to use AI actually make a great marketer?

Pranav’s take: AI tools are making marketers incredibly efficient at tasks they were already doing, but efficiency doesn’t automatically equal growth. The true drivers of growth—understanding unit economics, TAM, and high-level strategy—cannot be automated yet. AI won’t replace the top 5% of marketers who possess intellectual curiosity and “taste”. Instead, it will widen the gap: the top tier will leverage AI to crush it and increase their value, while non-strategic marketers will be left behind.

The Cutting Room Floor: What You Missed

There was simply too much happening in GTM tech this week to fit into the podcast. Here are the top items from our research doc that didn’t make it to the airwaves:

1. OpenAI’s Ad Ecosystem Takes Shape While we discussed ChatGPT’s basic $250k ad commits on the pod, the backend infrastructure is moving fast. OpenAI has entered early talks with The Trade Desk (TTD) to leverage its programmatic rails rather than building a walled garden, sending TTD’s stock surging 21%. Additionally, Criteo was named the first third-party AdTech partner for the ChatGPT Free and Go pilot, officially giving birth to “Conversational Retail Media”.

2. Google “Nano Banana 2” Brings 4K AI to PMax Google officially rolled out “Nano Banana 2,” a high-speed AI image model natively outputting 4K resolution directly into the Performance Max hub. Its biggest feature? “Consistent characters,” allowing brands to maintain a uniform visual spokesperson across thousands of automated ad variations while incorporating real-time web trends.

3. Meta Rewires Attribution and Strategy Meta is aggressively revamping its ad measurement. By June 2026, it is killing the legacy “Reach” metric in favor of a new “Page Viewer” metric to focus on unique people rather than raw impressions. Meta also introduced “Engaged-Through Attribution” to credit non-click engagements (saves, shares, comments) as high-intent signals, challenging Google’s “Last-Click” dominance. Finally, Meta embedded “Manus AI” into Ads Manager—an autonomous tool that focuses on strategic research and audience saturation insights rather than just bidding.

4. The “Self-Driving CRM” Arrives Klaviyo announced an expansion of its “Task-Specialized AI Agents,” allowing them to autonomously A/B test their own creative variations and deploy the winners across SMS and email. Marketers don’t even need to approve the send; they just define the “Brand Guardrails”.

The Deep Take: A 3-Alarm Fire in the Economy

We started the episode with a sobering reality check on the macro environment. Top media buyer David Herrmann recently posted a stark warning for DTC and e-commerce brands: “The economy is not good, sentiment in America is not good, all of this stuff reverberates through your ad accounts”.

Consumers are strapped by rising gas and energy costs, leading to eroding conversion rates and higher customer acquisition costs. Unless you are selling an essential “need-to-have” product, you need to get extremely strict on your offer testing immediately. Austin highlighted the sheer sticker shock everyday consumers are facing, noting, “I remember a Chipotle burrito being $14 and now it’s like $38”. While high-earners continue to spend, brands targeting the middle class need to get crisp on their value propositions and consider pricing strategies that undercut luxury comparables.

Platform Power Plays: Amazon, Meta, and Google

Amazon’s Advertising Hegemony Amazon has officially surpassed Walmart as the world’s revenue leader, posting $717 billion in 2025 sales. But the real story for marketers is their ad infrastructure. Amazon recently pulled off a massive power shift by opening its DSP to third-party inventory. Pranav put it bluntly:

“Amazon just pulled off the biggest power shift in advertising and I don’t think most people have realized that.”

You can now buy ads on Netflix, Spotify, and Roku utilizing Amazon’s first-party conversion data.

Meta’s AI Agent and the Ban Hammer Meta has rolled out “Manus AI” into its Ads Manager suite to automate strategic research and tactical tasks. However, there is a catch: Meta is permanently banning ad accounts for using non-Manus automated tools to manipulate their ad platforms. Pranav highlighted the panic:

Meta’s being very cagey about letting other non-Manus services do manipulation within the Meta Ads account which is kind of wild... lots of ecom people just freaking out like ‘Hey my 15-year-old you know Meta account just got banned.’”

Meta also introduced a massive update to its attribution model, shifting to “Engaged-Through Attribution”. The platform is no longer conflating soft engagements (like a save, bookmark, or “see more” click) with hard link clicks. Finally, Meta launched an AI performance predictor in its Creator Marketplace to forecast campaign ROI before you even sign a creator.

Google Lowers the Barrier to Premium Creative Google released Nano Banana 2, a state-of-the-art AI image model that generates 4K ad creatives with consistent character rendering. Paired with this is the launch of Pomelli’s “Photoshoot” tool, which allows SMBs to generate professional-grade product images via Gemini. The barrier to premium creative has officially hit zero.

The capabilities of these native AI tools are even beginning to threaten established design platforms. As Pranav noted after trying to replicate a Gemini workflow in Figma: “It didn’t work in Figma but it worked straight like singleshot in general... there’s something concerning here about you know their business and maybe even Adobe’s business.”

The AI Commerce Pivot: OpenAI Abandons Native Checkouts

OpenAI is officially scaling back its highly anticipated plan to introduce native shopping and checkouts directly inside ChatGPT. Instead, they are pivoting to a traditional advertising distribution play, partnering with The Trade Desk and Criteo.

Why use third-party platforms instead of building a native ads manager? Austin argues it comes down to time and resources:

“Integrating an API with structured documentation is pretty easy and pretty fast building a brand new advertising platform is a lot harder... it’s a distribution play it’s to test the waters.”

Following the news of this partnership, The Trade Desk’s stock surged by 21%.

Rapid Insights & The Pulse

• The X “Everything App” is Happening: Elon Musk has officially begun beta testing X Money and X Chat, featuring peer-to-peer payments and debit cards. But does the market actually want this? Austin is skeptical: “I don’t know how many more ways do we need to know how to pay for things there’s PayPal there’s Venmo there’s Cash App now there’s X... as an aging millennial I’m like I don’t want 10 ways to do things I just want like two.”

• HubSpot’s Media Engine Grows: HubSpot acquired Starter Story, a massive database of over 5,000 case studies, to fuel its media-led growth strategy. Following their acquisition of The Hustle, HubSpot is bypassing traditional ad spend by outright owning its audience and content channels.

• Microdramas Eat Mobile Attention: Short-form, vertical scripted shows (Microdramas) are now generating higher daily viewing times on mobile devices than traditional streamers like Netflix and Disney+. The sheer addictiveness of the format had Pranav questioning the broader cultural impact: “This is not good for humanity man, between this and my little bot Gary in my basement I’m really wondering where my life is going right now.”

• Meta is Deprecating the “Reach” Metric: By June 2026, Meta will replace its legacy “Reach” metric with a new Page Viewer Metric via Graph API v25. This shift focuses on “Quality over Quantity” by counting unique people who saw content rather than raw impressions, which requires third-party analytics tools to update their API tracking.

• Delivery Hero’s AdTech Growth: Delivery Hero reported that its high-margin AdTech business was a primary driver of its Q4 profitability. This highlights a broader industry trend where retail media networks are expanding beyond traditional stores into “Delivery Media” for local performance marketing.

If you missed the live show, we went deep on the viral “Something Big Is Happening” post, dissected the Super Bowl’s $8M commercials (and the leaked ones that didn’t air), and looked at why independent ad-tech is having a panic attack while AppLovin prints money.

Here’s the recap of the conversation, plus a few massive headlines that we didn’t have time to cover live.

1. “Something big is happening”

We started with Matt Shumer’s viral post claiming that since early February, AI has crossed a threshold where it’s no longer just a chatbot—it’s an agent capable of doing real work. Austin validated this with his own experience shifting from Cursor to Claude Code. He built an entire SaaS application in a few days by prompting teams of agents.

The Takeaway: The gap is widening between those using ChatGPT in a browser and those using agents in their terminal. Austin put it perfectly: if you understand the “grammar” of the web (APIs, HTML), you can now act as a senior engineer or data analyst. If you don’t, you risk being left behind.

2. The Super Bowl: 25% AI and a “sexy Raspberry Pi”

The stats are in: Viewership was down slightly (avg 124.9M) but hit an all-time peak of 137.8M during the halftime show. But the real story was the tech. 25% of all commercials involved AI in some capacity, up 400% from last year.

We talked about the weirdness of the OpenAI “Codex” ad, but the internet was obsessed with the leaked OpenAI hardware ad that never aired. It showed a Alexander Skarsgård using a mysterious device—which Austin hilariously described as a “sexy Raspberry Pi”. OpenAI claims its a fake ad!

The Glitch: Despite the hype, I looked at Google Trends for Gemini, ChatGPT, and Claude during the game. Result? Flatline. Zero movement. It’s a reminder that “brand awareness” doesn’t always equal immediate search intent. The winner? Instacart. Their “Bananas” ad actually moved metrics because it tied directly to a product feature (ripeness selection) in the app.

I wonder if this was a distraction tactic from one of their competitors. So strange!

3. Top news that we discussed live

We covered a lot of other items live and skipped a few which I’ve summarized below. Here is what you need to know:

YouTube Overtakes Reddit

We mentioned this briefly, but the data is official: YouTube has surpassed Reddit as the most cited source in AI answers. Video SEO is now critical for AI visibility. If your product isn’t explained in a transcript on YouTube, the models might not know you exist.

AdTech Valuation Chaos: Liftoff vs. AppLovin

We touched on Liftoff Mobile shelving their IPO due to “AI valuation uncertainty”. It’s a stark contrast to AppLovin, which is now valued at $150B. The market is effectively saying that if you don’t have a defensible AI moat or a platform-level advantage, the exit window is closed.

Databricks Genie

Databricks hit a $5.4B revenue run-rate, driven largely by “Lakehouse Genie”—a natural language interface for data. This is exactly what Austin and I were doing manually with Claude Code: asking plain English questions of complex datasets. The difference? Databricks is productizing it for the enterprise.

MarTech Budgets are Back

According to the Stensul Report released this week, 79% of marketers plan to increase MarTech budgets in 2026. The focus isn’t on buying more tools, but on “AI reskilling” (57% of teams). This aligns perfectly with our conversation about the need for non-technical marketers to learn how to wield these new agentic tools.

If everybody can create anything with AI apps then your advantage is your distribution... if you have no ability to distribute you can make whatever you want but how does it get found? — Austin

This week was packed. We covered the chaos of desktop agents, the “Mad Men” style advertising wars between Claude and ChatGPT, and the absolute monster earnings from Big Tech.

Here is the breakdown.

The Rise of “OpenClaw” (fka Moltbot)

If your feed was anything like ours this weekend, you saw Moltbot (or Claudebot, or now “OpenClaw” after a likely cease and desist) everywhere.

This isn’t just another chatbot in a browser tab. This is an open-source agent that installs locally on your computer and has “hands.” It can move your mouse, type for you, and read your files. It’s proactive, meaning it doesn’t just wait for a prompt—it can ping you on WhatsApp to tell you you’re late for a meeting.

The creator, Peter Steinberger, is embracing the chaos.

The guy’s just arrived... he’s like ‘Oh yeah I’ve made my money... this is pure open source go nuts.’ It’s just complete anarchy. — Pranav

While the security implications of giving an AI full access to your local machine are terrifying to some (Austin included), the potential for a centralized context that connects your files, apps, and preferences is the holy grail we’ve been waiting for.

The Ad Wars: Claude vs. Everyone

We watched a fascinating ad from Claude that positions privacy as their killer feature. The premise? A guy asking AI for advice on talking to his mom, only to get served a hyper-targeted ad for “mature dating” based on his private query.

It was hilarious, but it sparked a debate between us.

Austin loved the execution:

It captures... that GPT is pretty lazy... and the ad at the end was just the cherry on top... telling you that you’re sharing private information which could be utilized to advertise for something that’s completely unrelated.

But Pranav played devil’s advocate. Does the average person actually care about privacy? Google is a $3 trillion company built on our data.

Do people really care about their privacy... to the degree that Claude is like... saying? ... I mean the numbers say otherwise

Follow the Money: Google, Meta, and Accenture

Speaking of Google, their earnings were absurd. They hit $400 billion in annual revenue for the first time. YouTube ads alone are generating $60 billion.

The most interesting stat? 50% of YouTube viewership is now happening on TV screens. The lines between “digital video” and “television” are completely gone.

Meta is also making moves for 2026. They are going all-in on Reels. They are surfacing 25% more same-day Reels, and they are pushing the “TikTok-ification” of their algorithm hard.

Then there is Accenture. They reported that AI revenue jumped 100%. They are shifting from “projects” to “end-to-end solutions.” Essentially, they are becoming the “human layer” for managing AI agents for the Fortune 500.

The “SaaS Crash” & Vibe Coding

There was panic on X this week about SaaS stocks crashing (Figma, etc.) with people claiming AI “vibe coding” will replace software subscriptions.

Austin’s take? If it’s a simple wrapper or a utility, you should probably just build it yourself.

There’s almost no SaaS application that you can’t build with enough time... so the question is like is the value that you’re paying worth the value received from not having to go build it with an agent.

However, complex systems like CRMs or two-sided marketplaces (like Day AI raising $20M for autonomous CRM) aren’t going anywhere. You pay them for the network effect and the maintenance, not just the code.

Other News (The Pulse)

We didn’t get to everything live, but here is what else is happening in GTM and Tech:

Publicis Targeting LiveRamp: Rumors are swirling that Publicis Groupe is looking to acquire LiveRamp. This would be a massive move for a holding company to own the “Identity Layer” of the internet.

Amazon’s Agentic Advertising: Amazon launched a Model Context Protocol (MCP) server. This is “plumbing” that allows AI agents to buy and manage ads directly, moving us toward machine-to-machine marketing.

The Trade Desk Plummets: TTD stock dropped significantly, signaling a potential “AdTech Reset” where performance is judged by business outcomes rather than just programmatic scale.

LinkedIn Video is Booming: Video ad revenue on LinkedIn is up 30%. If you aren’t doing B2B video, you are falling behind.

Shoppable YouTube on CTV: YouTube officially rolled out shoppable formats for TV. You can now buy products directly from your television screen via QR codes, bridging the gap between awareness and performance.

Google Ads API v23: A nerdy but huge update—channel-level reporting is finally available for Performance Max. We can finally see where the money is actually going (Search vs. YouTube vs. Display).

See you next week. Go build your distribution.

Lucky number 13 was a spicy one. We dove deep into OpenAI’s aggressive ad pricing, the blurring line between reality and AI video, and why “Kevin” from The Office is the ultimate B2B influencer. Here is the download.

1. The OpenAI Gold Rush: $60 CPM

The biggest news hitting the feed is OpenAI officially releasing details on their advertising platform. The headline? They are charging a $60 CPM.

For context, that is roughly 3x what Meta charges. It’s premium, it’s expensive, and right now, it’s purely impression-based. No conversion optimization, no fancy pixel tracking—just “pay us $60, and we’ll show your ad to 1,000 people.”

Pranav’s Take: It’s a gold rush. Even without the sophisticated tracking, they are going to print money. I’m making a bold prediction: OpenAI will generate $10 to $20 billion in revenue off ads this year alone, potentially wiping out their burn rate entirely,.

Austin’s Napkin Math: Let’s look at the numbers. OpenAI reportedly has 200 million daily active users.

• If every user sees just one ad per day...

• At a $60 CPM...

• That’s roughly $4-5 billion in annual revenue.

That is the floor. If they show four ads a day? Or if the user count is higher? You get to Pranav’s $20B number very quickly.

While OpenAI is taking the high road with “high-intent” ads, Google is going the opposite direction. Google is now allowing links and contextual ad citations directly inside their AI Overviews. We are entering an era where technically literate users will mentally filter out the “garbage” in AI answers, while the mass market will consume it—just like the early days of internet display ads.

2. The Turing Test for Ads

We played a game this week. Pranav pulled up a Breaking Bad “Popcorners” commercial.

The Question: Was this AI-generated or real?

We both struggled. Pranav thought it was AI; Austin thought it was real but admitted AI could have done it. The verdict? It was a real Super Bowl ad from 2023.

But the fact that we had to pause and debate it proves we are at the tipping point. Our brains can no longer distinguish between high-end CGI/filming and high-end AI generation.

It’s getting weirder. “Khaby Lame” (the guy famous on TikTok for his silent hand gestures) recently sold his likeness rights to be used in AI videos. Disney is launching an AI ad agent for vertical video, and Amazon launched a creative agent at CES.

The Takeaway: The “mass market” of content creation is moving to AI tools. While Adobe and Figma will remain the domain of true professionals requiring granular control, the rest of the world is moving toward “one-shot” prompting.

3. The Great Tool Consolidation

Speaking of tools, we are both seeing a massive consolidation in our personal tech stacks. We’ve both largely moved away from ChatGPT.

• Austin: Down to Gemini for daily tasks (email, Drive integration) and Claude for coding.

• Pranav: All in on Claude. Gemini as backup. Still paying for GhatGPT but likely to churn at some point.

The Killer Use Case: Pranav had to deal with a finance spreadsheet entirely in Japanese this week. He dropped it into Claude, asked for a translation, and boom—perfect English, zero friction. Austin’s wife did the same thing traveling in Japan, photographing signs and menus and translating them instantly. We are effectively global from day one now.

4. Ramp, The Super Bowl, and Millennial Nostalgia

Finally, we looked at the new Super Bowl ad from Ramp, featuring Brian Baumgartner (Kevin Malone from The Office).

Is a Super Bowl ad worth it for B2B?

Surprisingly, yes. When you look at the cost, Super Bowl ads often run around a 60−70 CPM—the exact same price OpenAI is charging.

If you are a mass-market B2B player like Ramp (where everyone from a 3-person startup to a Fortune 500 needs expense management), the math works.

Why it worked: They nailed the casting. Brian Baumgartner plays an accountant/finance guy. But more importantly, he appeals specifically to the 30-to-40-year-old demographic—the exact generation that grew up on The Office and is now sitting in operating roles making purchasing decisions.

It’s a brilliant strategy: Use TV and nostalgia as a source of creative trust.

One last thing

We mentioned StackAdapt raising $235M to build an AI bidding engine. As ad spend on Meta and Google hits a point of diminishing returns, brands have to look elsewhere—CTV, audio, and programmatic are the next frontier.

If you rewind to 2017, there was a fairly discrete playbook for marketing. You bought ads, the pixel fired, the deterministic data matched up, and you knew exactly where your money was going.

Fast forward to 2026, and that playbook is gone.

In this week’s episode of GTMN, we’re doing something a little different. Austin is stepping into new fractional roles as CMO at AtoB and working with Replit, and he’s facing a massive question that keeps coming up with founders: How do we actually track performance when the old tools are broken?

We dove deep into the state of attribution for companies spending $20M+ on web and mobile, the “telemetry bias” that is killing brand strategy, the “poor man’s” version of incrementality, and the new ad inventory hitting Google’s and OpenAI’s AI surfaces.

The Death of Deterministic Attribution?

Austin kicked off the conversation with the question on every growth marketer’s mind: Is deterministic attribution (knowing exactly who clicked an ad via device ID or cookie) dead, alive, or on life support?

According to Pranav, it’s not dead—but it is dangerously misunderstood.

The industry has conflated “telemetry” (tracking events) with “causation” (what made the user buy). We are living in a world of fractional data. If you do things right today, you might get 70% visibility on web, but perhaps only 15% on iOS and 10% on desktop.

The problem isn’t that we can’t track people; it’s that executives are living with 2017 expectations, wanting to know exactly how every specific dollar printed money.

“It [deterministic attribution] is overtrusted by people... even the best of marketers might think that it implies causation or it implies that you can use it to do budget allocation but those assumptions are extremely flawed.”

Deterministic attribution tells you what you can observe. Not what caused the outcome. It’s telemetry. Useful telemetry. Necessary telemetry. But still partial.

In an idealized world, deterministic attribution would neatly stitch together every touchpoint from impression → click → conversion. In the real world, it doesn’t even come close.

The “Telemetry Bias” Trap

One of the most insightful parts of the discussion centered on why companies over-index on Google and Meta while ignoring video, podcasts, or Out-of-Home (OOH) advertising.

Pranav coined this “Telemetry Bias.” We gravitate toward the channels that are easiest to measure because they look fantastic in a spreadsheet.

“The things that are easiest to measure will show that they’re working... This is why 70% or 80% of businesses are investing... [in] direct response on LinkedIn and Meta. But when was the last time you clicked on a podcast ad? You can’t.” — Pranav

If you rely solely on deterministic data, you will optimize your marketing mix for trackability rather than growth. You’ll cut the brand-building channels that actually drive demand simply because a pixel didn’t fire.

Why? Browser-level blocking, Cookie consent banners, GDPR / CCPA, iOS ATT + SKAdNetwork, Platform-level obfuscation.

In practice, the amount of deterministic data being captured correctly is dwindling:

• Web: ~60–70% in best cases

• iOS app install attach rates: ~15-30%

That’s not a rounding error. That’s a fundamentally incomplete picture.

And when vendors claim “perfect matching,” they’re usually leaning on fingerprinting—which is probabilistic by definition and increasingly shut down by platforms.

The Solution: Incrementality and “Eyeballing It”

So, if the data is broken, what’s the fix?

For early-stage companies (and even Series B), you don’t always need expensive software. You need a scientific mindset. Pranav suggests a return to “eyeballing” big changes. If you double your spend on podcasts ($100k/month) and your total installs go up by 5% over that period, there is your answer.

At Paramark, the team is stripping away the vanity metrics (MQLs/SQLs) and focusing on a simple dashboard:

1. Total Ad Spend

2. Impressions/Engagements

3. Website Traffic & Search Query Volume

4. Demos (High intent hand-raisers).

If you pull a big lever (like launching a campaign in New York) and you don’t see a lift in traffic or search volume from that geography, the campaign didn’t work. It doesn’t matter what the attribution software says.

Larger businesses that have the scale and spend should probably invest in incrementality testing and Marketing Mix Modeling.

Setting up your team for success

In addition to all this, there are three more things you should consider doing.

Respect time horizons

Some effects show up fast. Others don’t. If you judge every campaign on a 2-week window, you’ll systematically kill your marketing engine. Some tests need to be 4 weeks or even 12 weeks depending on the channel, the type of ad inventory, and your buying journey. Use leading indicators and lagging indicators. And know which is which.

Don’t over-test at low volume

Incrementality testing is powerful—but only when you have scale, enough time, and limited overlap. Running five overlapping tests on tiny budgets just manufactures false confidence.

Hire for a scientific mindset

This one’s uncomfortable but true. Many marketing teams lack someone who can think clearly about hypotheses, controls, bias, and causality vs correlation. That gap matters more than your tooling. You need to hire the right team to fill this gap.

News: Ads in the AI Era

Finally, we touched on Google’s major update: Direct Offers in AI Overviews.

Google is now allowing advertisers to place price-promotion ads directly inside AI-generated answers for high-intent queries. While this opens up new inventory, there is a catch: it is currently focused on price discounts.

As Pranav noted, “It encourages the wrong behavior in my opinion which is discounting,” but marketers are inevitably going to flock to it to capture that high-intent traffic.

The Rise (and Reality) of Agentic Commerce

My feed has been absolutely flooded with talk about agentic commerce. The IAB (Internet Advertising Board) recently released an agentic roadmap, providing technical recommendations for how the adtech and martech industries can move toward AI-driven commerce.

However, we’re skeptical of the “single-shot” AI world where an agent just books a whole holiday for you without input. As Rory Sutherland pointed out on the Knowledge Project podcast, humans generally can’t choose in the absence of comparison. We want a menu of options, not a single dictated choice.

“A majority of purchases are still going to require choice and selection and preference and research on the part of human beings.” — Pranav

Austin notes that while agents are great for things you don’t care about—like finding a specific L-bracket for a home project—for things you do care about, like running shoes for a half marathon, you’re always going to want to apply your own preferences.

The Brand Measurement Trap

We also took a look at a new benchmarking report from Carilu (former CMO at Atlassian) and other former marketing leaders. The data shows that while demand generation still eats most of the budget, measurement remains the biggest blocker for brand investment. Only 28% of companies feel confident tying brand spend directly to pipeline.

“The reason why you don’t over invest in brand is not because you don’t believe in it; it’s because you don’t want to get fired by your co-founder or by your leader.” — Austin

We’re seeing a shift, though. Many B2C and B2B brands are moving away from hyper-targeted and direct response ads only to focusing on awareness and reach, letting the creative do the heavy lifting of finding the audience. With the proliferation of incrementality measurement tools and platforms, brand investments no longer have to be second class citizens for GTM teams.

Reddit Joins the “Max” Race: Automating the Historically Un-Targetable

If you’ve spent any time in media buying, you know that Reddit has historically been a difficult-to-target ad environment. It’s a land of niche communities and very specific subreddits where, in the past, you had to manually hunt down where your audience lived. But Reddit is finally following in the footsteps of Google and Meta by entering the “fully automated” race with the launch of Reddit Max campaigns.

What are Max Campaigns?

Think of this as Reddit’s version of Performance Max or Meta Advantage. Instead of you making a deterministic choice—like “I want to show up in r/marketing and r/growth”—you’re handing the keys to Reddit’s Community Intelligence. The system uses AI to automatically predict the connection between your campaign and various subreddits or conversation placements, determining where your impressions will have the most value.

Big Moves: AppsFlyer and PayPal

One of the biggest stories over the break was AppsFlyer passing $500M in ARR. There’s talk of a potential $3B to $4B acquisition by a private equity firm. It’s an impressive feat for a company in the attribution space, showing that despite the rise of probabilistic models, the “habit” of real-time, deterministic reporting isn’t going anywhere.

“I never predicted that they would get close to a billion dollars—certainly not the attribution space because it’s such a narrow piece of technology—but here they are, as big as Braze.” — Austin

Meanwhile, PayPal is turning into a closed-loop media network.

They are leveraging their transaction data so merchants can target users across other platforms like Meta or TikTok based on what they’ve actually bought. We expect to see others like Stripe or Square follow suit as first-party transaction data becomes the ultimate targeting mechanism.

Looking Ahead: Our 2026 Predictions

We wrapped up the episode by placing some bets on where we’ll be by the end of 2026.

• The Buyer Journey: Austin thinks 50% of the B2C journey will be handled by agents, while I’m betting lower on the B2B side—closer to 10% for enterprise buying cycles.

• SEO vs. AEO: Will Answer Engine Optimization replace SEO? Austin thinks AEO is just “hypercharged SEO” (doing the same thing, just faster), but I bet 90% of CMOs will claim they’ve made the switch just for the branding of it.

• Creative Workflow: We disagree here, too. Austin is at a 50% “coin flip” for AI-driven creative workflows, while I think the reality will be closer to 20-30% due to tool fatigue and a lack of standardized “easy buttons” for the whole process.

“In marketing, you should actually lead with the story and use the data to back up your gut. It’s not all science, as much as I would like to believe that.” — Austin

The Campaign Agent Opportunity

We ended with a call to action: in large companies like Walmart, the hard part of marketing isn’t the idea—it’s the 15 approval steps, legal compliance, and tool management. If someone builds an “Agentic Campaign Manager” that keeps marketers organized across their growing tech stack, call us. We’ll find you the investors.

Here’s the breakdown of what went down.

The TikTok Deal: It’s Official

The big breaking news is that TikTok’s US entity is being sold to a joint venture controlled by American investors. According to a memo from CEO Shou Zi Chew, this new venture will operate as an independent entity with full authority over U.S. data protection, content moderation, and—crucially—algorithm security.

While it seems like they are keeping the core algorithm, the “security” of it will now be overseen by this US entity. We’re still a bit skeptical about how much the product will actually change, but for multinational advertisers, life is about to get a lot more complicated with potentially separate ad managers for the U.S. and the rest of the world.

"Just a way for a handful of investors to get really rich" - Austin!

Consolidation Season: Salesforce, Cvent, and Pinterest

The acquisition market is heating up, especially in the AI and event space:

• Salesforce acquired Qualified: On December 17, 2025, Salesforce signed a deal to buy Qualified, the AI sales engagement platform. Their core product, Piper (an AI SDR agent), is designed to automate the early funnel by engaging visitors and booking meetings. It makes sense given Salesforce’s aggressive AI strategy; they’ve already made ten acquisitions this year as they try to package AI “jobs to be done” across their suite.

"I think if you're not building—if you haven't started in the last few years—it's pretty hard to argue that you're like actually AI native" - Brendan

• Cvent acquired Goldcast: Cvent, the heavyweight in event marketing, picked up the AI-video platform Goldcast. While terms weren’t official, reports suggest Cvent paid just under $300M in cash—an incredible outcome for a team that only raised about $40M.

• Pinterest acquired tvScientific: This isn’t about “Pinterest TV” as a streaming service; it’s a performance ad tech play. Pinterest is using tvScientific’s engine to connect its intent-rich first-party signals to real business outcomes like site visits and purchases, allowing advertisers to run outcome-based TV campaigns.

The Lawsuit: ZoomInfo vs. Apollo

In a move that’s definitely providing some B2B tea, ZoomInfo is suing Apollo. ZoomInfo claims they own the patents on the “core mechanics” of how modern sales platforms operate. The patents in question cover everything from web crawling for B2B data and using ML classifiers to categorize pages to generating lookalike account recommendations based on intent signals.

Apollo tried to get the case thrown out, arguing that you can’t patent “collecting and analyzing data on a computer,” but the judge ruled that because ZoomInfo claims a “novel technical improvement,” the case is headed to trial. Honestly, it’s hard to see how a “feature matrix” can be proprietary, and if ZoomInfo wins, it might mean IP law has gone completely off the rails.

"It makes no sense... you can’t have patents on this stuff. If ZoomInfo wins, it shows IP law has gone completely haywire" - Pranav

Key Takeaways from the AI GTM Summit

Brendan joined us fresh off hosting the AI GTM Summit, which had over 600 registrants and 300 live attendees. Two big trends emerged:

1. CRM Sorting: The “no-brainer” move right now is sorting the world into your CRM using AI. Instead of using virtual assistants for research, teams are building AI workflows to enrich accounts with specific data points—like how many products an e-commerce site sells—and automatically tiering them as high or low fit.

2. In-House Agents: The “bleeding edge” is teams building their own in-house agents using tools like Claude Code or Cursor. As data becomes commoditized, the “secret sauce” shifts to what you do with that data and how you orchestrate custom tool calls.

"As we get into this world where like data becomes more and more commoditized, what you do with the data actually becomes the secret sauce" - Brendan

The Rise of ChatGPT Apps

The feed was absolutely full of “app” announcements from the likes of Clay, Hex, Figma, and Adobe. Adobe’s ad was slick, showing how you can use Photoshop Express inside ChatPT, but we’re questioning if users actually want to do manual edits there.

The real “bull case” for these apps is context. ChatGPT has a “memory” of who you are and what you’re working on. When you use a Clay app inside ChatGPT, it can marry your global business context with a specific tool call—something a standard Google Sheet just can’t do.

The big lesson from Episode 10? In this new era, the most powerful tool isn’t just the AI itself—it’s the operator who knows how to point it. As Austin put it, the number one thing you can do for your career is “go take a programming class... because you can literally just like talk to Cursor and it will code for you”.

Think of AI like a universal remote for your business; the remote is powerful, but it’s only as effective as the person who knows which buttons to press to make the whole house come alive.

Happy holidays everyone, and we’ll see you in January!

A quick word from our favorites

Before diving deeper, we had to celebrate a personal milestone—our first sponsorship! I got to tell the story of how I met Mitchell, the founder of Kondo, a tool I describe as “superhuman for LinkedIn”. If you’re looking to control the chaos of your LinkedIn DMs, you’ve got to try Kondo. Austin and I were both early subscribers because we needed a way to manage the DM noise and its a tool we can’t live without now!

The streaming wars get serious (and AI Gets IP)

We kicked off with a huge piece of breaking news: Disney is investing a billion dollars in OpenAI in a deal to bring characters like Mickey Mouse and Luke Skywalker to Sora’s AI video tool. This is fascinating and definitely confirms our earlier prediction that major IP holders would want to be integrated into Sora AI. This shift might just shape what content deals with OpenAI look like over the next couple of years, essentially turning valuable IP into something akin to “game characters” that users can interact with through the AI.

“...will actors become just like game characters and you’re you’re playing with these with this IP that’s basically what’s happening in Sora...”

Right alongside that, the streaming landscape saw a tectonic shift: Netflix made a bid for Warner Bros. for $72 billion. As Austin noted, streaming is definitely eating linear media. If this acquisition goes through, the combined entity could generate U.S. ad revenue of roughly $2.3 billion. Critically, this consolidation is expected to strengthen Netflix’s negotiating hand due to their combined inventory and audience. Experts predict this would put upward pressure on CPMs and stall some of the advertiser-friendly pricing trends we’ve seen recently, which is a key side effect of consolidation in the media buying market.

The AI slop backlash and the power of creators

We had to spend some time on the dangers of using AI for the sake of AI, particularly concerning the infamous McDonald’s Christmas ad in the Netherlands. McDonald’s released a 45-second commercial created entirely with generative AI that suggested escaping holiday chaos—like family stress, burnt cookies, and shopping disasters—by hiding out at their restaurants.

The ad was met with massive backlash and widely mocked as depressing, creepy, or “AI slop”. The execution hit a backlash threshold because consumers rejected the work they saw as soulless or cynical, especially during a culturally resonant time like Christmas. The visuals were found to be uncanny, glitchy, and emotionally hollow, lacking the warmth people expect from holiday work. Marketers, the lesson here is clear: don’t use AI just to use AI.

I think people are afraid to be creative like there’s been so much washing of what is acceptable and appropriate in today’s kind of political and socioeconomic landscape that people are afraid to take risks...

This need for authenticity is backed by new data from TikTok confirming that creator-led ads generate significantly higher engagement than non-creator ads. The data shows creator ads have a 70% higher click-through rate (CTR) and 159% higher engagement rates compared with non-creator ads purchased at the same cost per thousand impressions (CPM). This performance gap exists because of the creators’ cultural fluency and the trust they build with their audiences, making their content far more compelling and actionable.

This authenticity shift is impacting B2B, too. The old-school automated outbound campaigns—the “spam 100,000 people” motion—is failing because the channels are saturated. A lot of companies are now going back to the roots of high-quality, high-touch outreach. For B2B, we’re seeing startup founders moving budget from paid ads into influencer ads on LinkedIn, where paying a creator to talk about a product converts leads highly effectively.

The end of the “Agency as Agent” era?

The juiciest industry news came from Forrester, which predicted a 15% agency job loss in 2026, following an estimated 8% cut in 2025. This decline is driven by AI, automation, consolidation, and structural pressure on the traditional labor-based agency model. However, the global advertising market is more resilient than expected, with WPP raising its guidance, forecasting global ad revenue will grow 8.8% this year (totaling $1.14 trillion) and another 7.1% in 2026. This shows a significant juxtaposition: spending is increasing, but agency headcount are dropping.

..when you have an agency whose goal is percent of spend like that is a f$%#$ waste of money like because their job is to spend money not to be efficient.

The classic agency model, where they act solely as client advocates selling hours and talent, is being redefined. Agencies are pivoting away from being pure “agents” and are instead evolving into hybrid enterprise vendors that sell products, platforms, inventory, and outcomes. This means they are becoming “principals as well as agents”. The economic forces driving this include eroding retainers, marketing insourcing, procurement squeezing margins, and AI cutting out repetitive roles. For agencies to thrive, they must pivot to productized offerings and own IP, while talent needs to embrace deep strategy, technology fluency, and creator ecosystem skills over execution-heavy roles.

I think you’re going to spend more money behind bad money bad data bad creative and the reduction in the human force is actually going to make this worse not better...

Regulation and ad tech updates

We wrapped up with two pieces of important news:

1. Australia enacted the world’s first nationwide ban on social media accounts for anyone under 16. Platforms like TikTok, Facebook, Instagram, YouTube, and X must take “reasonable steps” to block these users and implement age-verification systems, such as document uploads or camera/biometric checks. Critically, the law doesn’t punish children or parents who bypass it; instead, enforcement targets the platforms themselves, which face fines of up to A$49.5 million for non-compliance.

2. Google has launched the Data Manager API. This is a new centralized ingestion API that gives advertisers a simpler, unified way to feed first-party data—such as customer lists, offline conversions, and event data—securely into all of Google’s advertising systems (including Google Ads and Display & Video 360) using a single programmatic endpoint. This move consolidates what previously required multiple custom tools, custom pipelines, or manual uploads. If you like Meta’s Conversion API (CAPI), this is Google’s comprehensive answer.

The Bizarre World of Ultra Runs and Cinnamon Dust

I (Austin) had to start the show by sharing the ridiculous journey that was the DC Taco Bell Ultra, a 30-mile run where you stop to eat tacos. I had quite a spread, including a chalupa, a cold burrito, and the worst decision of my life: a Crunch Wrap Supreme at mile 22 in an underground Taco Bell.

But the wildest moment came from another runner. We were at Taco Bell number four when a serious guy walked in, crushed a bag of cinnamon twists into dust, poured water into the bag, drank the whole mixture, and left. It was an incredible display of an “extreme strategy of drinking cinnamon twists”.

That whole ordeal sounded like a next-level endurance challenge to Pranav, who committed to making a bold goal for next year. He plans to “start training for it from from January” for a half marathon. I promised him that not only will we offer running guidance on the podcast, but I’m going to come and do a show together at his next half marathon.

The Truth Behind Holiday Growth

Turning to the market, Black Friday and Cyber Monday were in the books, and the initial numbers showed a consensus of 7% to 9% year-over-year growth. However, once we dug into the data, the picture became clearer: almost all of that growth came from price increases, not unit increases. Unit sales were actually “flat or down and prices were up”.

We also noted the growing disparity in spending. The rest of the metrics were quite flat if you removed upper-income households and luxury goods. The vast majority of growth in spending right now is being driven by the “upper 10 to 15% of household incomes”.

AI Reshapes Agency Land and Sales Strategy

The agency world continues to consolidate. IPG merged with Omnicom, making the combined entity the largest advertising holding company globally. They are shedding 4,000 jobs, explicitly driven by the need to compete with “AI-driven creative production data integration and global scale”.

Despite the big players struggling, I (Austin) argued that “there’s never been a better moment in history to build a marketing agency” for enterprising folks, as the technical sophistication required in marketing today means there is no universal playbook for every business.

This return to thoughtful, human-centric GTM is mirrored in the sales world. Ramp announced they are shutting down their automated outbounding team, declaring, “we think that the that game is done”. The shift is back to equipping humans to do a great job. At our own company, we’re implementing a GTM engineer role focused on thoughtful engagement, because “if everybody else is doing the same thing how are we going to stand out”.

Sky-High Marketing Bets

Marketers are trying increasingly wild things to break through the noise. We discussed Heli D, a company planning a 400 square-foot LED billboard suspended by helicopters, timed for the 2026 Super Bowl.

We also covered Swedka, a vodka brand that announced their Super Bowl commercial was being produced primarily using AI. We questioned the PR strategy behind revealing this. I (Pranav) believe that if you choose to use AI, you should own it, stating,

“I think there is zero value in telling people that you’re doing it with AI”.

OpenAI’s Code Red Moment

Perhaps the biggest news of the week was the report that Sam Altman told OpenAI employees that he was declaring a “code red” to improve ChatGPT and delay other initiatives, seemingly spooked by the competition from Gemini.

I (Pranav) confirmed that I’ve seen my own usage of Gemini go up 10x in the last two weeks. I was “an avid like chat GPT fanboy for like the last you know two years,” but I was hooked when I created a fully functioning React app inside the Gemini chat environment.

I (Austin) find the Google integration most compelling. As a consultant with eight years of data stored in Drive, Gemini makes it easy to add existing knowledge to your chat environment by simply clicking “add from drive”. Pranav agreed, noting he used Gemini to create a three-phased running preparation plan and “schedule this on my calendar for the next like 9 months”. I also highlighted how the AI formula inside Google Sheets could potentially replace tools like Clay for enrichment and data structuring. We concluded that Google is truly fighting for mind share by figuring out how to make their tools the default repository for your brain.

Holiday Marketing and Black Friday Strategies

The conversation begins by noting that Black Friday and Cyber Monday deals seem to start earlier every year. A key point of discussion centered on Swiss sneaker company On, which recently raised its guidance and stated it would not offer Black Friday deals. This approach, focusing on premium full-price sales, innovation, and the intersection between performance and design, was praised as a model where the business doesn’t need to worry about sales pressure.

“If you’re a B2B brand please don’t do anything for Black Friday don’t do it”. — Pranav

We debated creative, “in the wild” viral marketing tactics for the Black Friday period, suggesting that brands should send people into the fray to convince consumers about their software, citing Ramp.com as a partial example. Pranav mused on the idea of a viral, though economically bad, Black Friday deal where a lifetime annual subscription was offered for 99 cents.

“Can you imagine being the market the head of marketing for that It’s beautiful No pressure on like trying to hit some madeup number just because it’s Black Friday season”. — Austin

The discussion also included news about Austin doing the “Taco Bell Ultra,” a 50K ultra-marathon involving nine Taco Bell items eaten over 30 miles, though it is not sponsored by the brand and is considered a “fat ass” community run.

Adobe’s Acquisition of SEM Rush and the SEO Evolution

Adobe has acquired SEM Rush for $1.9 billion. We discussed this major M&A move, with Adobe positioning the acquisition as a natural way to keep growing in a space important to existing customers, especially regarding AI search responses. The strategy is to integrate SEM Rush to boost Adobe’s analytics suite for brand monitoring and visibility for LLMs, defending against modern SEO/AEO players.

A key concern raised was Adobe’s historical struggle with integrating acquired products, a challenge faced by other major companies like Twilio (with SendGrid and Segment).

“I mean I guess my first question is like how good is SEM Rush on AEO compared to some of these new tools like Airops and Profound”. — Austin

The conversation highlighted that the legacy SEO tools (like SEM Rush and its alternative Ahrefs) are rapidly adapting to the new world of AEO (Answer Engine Optimization). Competitors like Airops and Profound are approaching content creation and visibility from different angles. Ahrefs, for example, is expanding beyond SEO/AEO into content workflows, recently introducing social posting and calendaring tools.

Alembic, Causal AI, and the Agency Model Renaissance

AI firm Alembic (a competitor to Paramark, Haus, and Recast) secured $145 million from Accenture and others. Alembic brands itself around “causal AI,” seeking to replace traditional probabilistic measurement in marketing effectiveness and measurement. They have a strategic partnership with Accenture to deploy this causal AI within the Fortune 500.

The efficacy of “causal AI” was debated, with skepticism that adding the word “causal” makes it so, as true cause and effect can only be determined through experimentation.

“The only way to get to cause and effect is experimentation”. — Pranav

This funding round signals a return to the services-as-a-product model, proving that as AI features become more complex, there is more room for agency-style or solution-style companies. AI makes building SaaS products easier, but it is hard to build a team that can weaponize AI to solve problems. Companies like Palantir (market cap $400 billion, P/E ratio 370-390) exemplify this model: deploying smart people equipped with AI/software engineering skills to build bespoke applications for clients after intellectually understanding the problem.

“A team of really smart people who can weaponize AI to solve problems”. — Austin

The Influencer Economy and the Dystopia of AI Likeness

The influencer and creator space is also seeing major shifts. Agentio raised $40 million for creator ads, starting with YouTube and expanding to other channels. They offer an AI-powered content review feature that checks creator drafts against the brand brief for compliance and safety.

We noted that the influencer space is currently messy, relying heavily on spreadsheets. However, AI presents a terrifying prospect: the potential for influencers to automate their work entirely by licensing their likeness and voice to brands for promotion. This shift means the brand is paying primarily for the audience, not the manual content creation.

This development is akin to a Black Mirror episode, raising concerns that if this happens at scale, culture could become controlled, turning everyone into a “mouthpiece for something else”. The current trend among YC companies is moving away from focusing on scaling email marketing to programmatically figuring out how to achieve video and social fame through AI tooling, signaling where the arbitrage has moved.

This pressure has led to two diverging marketing strategies:

1. AI Slop: Leaning into scaled AI usage (e.g., posting every day, mass emails), resulting in diminishing returns.

2. Hyper-Targeted ABM: Abandoning mass outbound strategies in favor of highly concentrated, multi-channel attacks on small, niche segments of users (Account-Based Marketing or ABM).

“Abandon the mass outbound strategy Doesn’t mean you won’t use tools like Unify but actually focus on a really small subset of users”. — Austin

AI Transparency and New Ad Platform Bidding Strategies

TikTok is taking the lead on AI transparency. They launched a blog post announcing new ways to spot, shape, and understand AI-generated content. TikTok is building transparency tools to automatically detect AI content, giving users the ability to tag content as AI or real, and giving creators the ability to claim original content. Furthermore, TikTok launched a $2 million educational fund for experts to create content about responsible AI. This contrasts with the strategy of Sora (which consciously made the decision to have all videos be AI-generated to maintain a completely virtual experience).

We discussed new ad platform features:

1. Google’s Journey Aware Bidding: Google launched an advanced bidding strategy that uses all conversion actions (e.g., lead, MQL, SQL, purchase, repeat purchase) to optimize bidding choices along the customer journey, similar to Meta’s “GEM” concept. A major challenge is the quality and formatting of CRM data required for this feature to work effectively.

2. Self-Serve Incrementality Testing: Google launched a feature making its native incrementality testing (similar to Meta’s Conversion Lift) self-serve. Previously requiring a dedicated Google Ads representative and high spend, tests can now be set up for as little as $5,000.

An incrementality test works by splitting a possible audience in half (test and control). The test group sees the new campaign (e.g., Journey Aware Bidding ads), while the control group does not. The difference in conversion rates between the two groups provides the measurable “lift”.

The value of testing was emphasized, especially against deterministic modeling. The conclusion was that probabilistic modeling is often more effective, and experimentation must be continuous and reproducible.

“If a test is successful is usually pretty obvious”. — Pranav

We concluded by noting the importance of basic measurement tools like the HDYHAU (a simple question asking users where they found the product or “how did you hear about us”) for early-stage companies to validate assumptions quickly, overriding concerns about pipeline slowdown.