Kevin's Take
The Big Vendors Are Losing Their Grip
I've been noticing a difference in the way our customers are beginning to talk about their marketing technology stacks. The complaints about Adobe Experience Cloud and Salesforce Marketing Cloud aren't new. But the intensity definitely is. These leaders are frustrated in a way I haven't seen before.
They've spent a lot of time and money on these platforms but adoption numbers are best lukewarm (especially their AI features). The part that really hurts is that these tools that were supposed to make marketing faster are making everything slower. One CMO told me she has three people whose full-time job is "making Salesforce/Pardot work." Not good.
Several people I've talked to aren't just complaining anymore. They're actually doing something about it. We're also seeing the signs in the market. SaaS company valuations in the first week of February 2026 saw a massive sell-off. In seven days, over $1 trillion in market capitalization was erased from software stocks. Times have changed.
The Math Changed in 2026
The difference in 2026 is that leaders are starting to realize that you can build custom tools that do exactly what you need in days, not months. We're doing this at Mighty & True right now. We have a process: intake frustrations from the team, build briefs quickly using AI, then build experiments in AI coding tools to replace what we're paying for.
We've successfully replaced several tools this way. Not Frankenstein workarounds. Actual functioning tools that our team prefers to use. The development time? Usually a few days. The cost? A fraction of what we were spending on subscriptions.
I'm not saying every company should fire their entire marketing stack tomorrow. But if you're paying six or seven figures annually for platforms your team actively avoids using, you need to at least run the numbers on building your own.
What This Means for Your Vendor Relationships
The big vendors built their business models on lock-in. Long implementations. Complex integrations. Training programs. Consulting fees. The switching costs were supposed to keep you trapped even when the product disappointed.
But AI coding tools are breaking that model. The switching costs dropped dramatically. Your mid-level developer can now build in a weekend what used to require a six-month professional services engagement. And because you're building exactly what you need, not configuring someone else's bloated platform, your team actually uses it.
We're actively helping that play out across multiple marketing organizations right now. The vendors sense it too. Notice how aggressive the contract renewal conversations have gotten? They know their leverage is evaporating.
Where to Start
The Signal
Gartner: 67% of B2B Buyers Prefer a Rep-Free Experience — Gartner
New research from Gartner surveying nearly 650 B2B buyers reveals that two-thirds prefer buying without talking to a sales rep, and 45% are already using AI during their purchase process. This isn't buyer preference data from 2019 that's just getting published. This is current behavior.
Why it matters: If you're still building your GTM motion around sales development reps and discovery calls, you're designing for a buyer that doesn't exist anymore. This should immediately reshape how you allocate budget between traditional sales headcount and self-serve buying experiences. The buyers who do want to talk to reps are probably the minority who need the most hand-holding, not your best customers.
How Much of the Software Slowdown Is Just Budgets Flowing to Anthropic and OpenAI? Maybe As Much As 70%
Every major public software company has printed lower growth rates every single year since 2021. Not occasionally. Every year, without exception. Salesforce dropped from 25% to 8%. Snowflake from 106% to 24%. HubSpot from 47% to 17%. Jason Lemkin's thesis: up to 70% of this slowdown is budget that used to go to traditional software now going to Anthropic, OpenAI, and other AI infrastructure.
Why it matters:This isn't a temporary spending freeze your board keeps asking about. This is permanent budget reallocation. If you're a CMO at a traditional B2B software company, your customers aren't cutting spend because times are tough. They're cutting your product because they found something better. Your Q3 pipeline problem isn't a marketing execution issue. It's an existential product question.
On Our Radar
AI is becoming the starting point for everyday consumer activity online, according to PYMNTS Intelligence research surveying 2,100 US adults. If you're still optimizing for Google search behavior from 2023, you're designing for ghosts.
Your analytics can't see the AI searches driving your leads, and that blind spot is making your attribution and lead quality metrics increasingly meaningless. This piece explains why traditional demand gen measurement is breaking.
Metricool analyzed 39 million social media posts across 10 platforms to figure out what actually works in 2026. Worth skimming if you're tired of algorithm rumors and growth hack garbage.
Butler/Till ran early tests on agentic media buying and cut both media costs and supply chain costs. Limited sample size, but directionally interesting if you're running significant programmatic spend.
FROM THE TRENCHES
Your Website Has Two Audiences Now. Most Teams Are Only Serving One.
Last wee, we had a conversation on the podcast recently with Guy Yalif, Chief Evangelist at Webflow.
He said: "Websites need to create visually stunning, emotionally evocative storytelling for humans. And they need to efficiently communicate similar information to machines."
He's right. And most marketing teams we work with haven't fully internalized what that second part actually requires.
Here's what's changing:
Guy co-hosted AEOConf earlier this year, a first-of-its-kind event that drew 1,200 CMOs onto a waitlist, because the interest in Answer Engine Optimization is that high right now. The premise: as LLMs become a primary research tool for buyers, showing up in AI-generated answers is quickly becoming as important as showing up in Google.
AEO isn't a new discipline. It's good SEO done more intentionally. The same team that runs your organic search program should own this. The content, technical, authority, and measurement frameworks largely carry over. The difference is mostly in what you optimize for. Some highlights:
Queries are getting longer and more conversational. The average search query used to be four words. In LLM interactions, it's closer to 23, and growing. That means your content needs to answer real buyer questions, not rank for keywords. If you're not mining your sales calls, support tickets, and "People Also Ask" data for those questions, someone else is.
Structure is the new backlink.The single highest-leverage technical move right now is making your content easy for LLMs to ingest: clean semantic HTML, structured schema markup, descriptive headlines, FAQs that mirror real buyer questions. Webflow's AEO team added FAQs and schema to six product pages and saw those pages capture 57% of their incremental LLM citations in just two weeks — out of a site with 250,000 pages. That's not an edge case. That's a signal.
Earned media is your AEO strategy.Brand recommendations from LLMs come overwhelmingly from earned sources, Reddit threads, G2 reviews, press coverage, analyst mentions. Not your homepage. Your content team and your comms team need to be working from the same playbook right now.
Why this matters for your team:
The CMOs moving fastest on this aren't spinning up new headcount or buying new tools. They're redirecting existing SEO resources toward a slightly different set of outcomes and beginning to measure share of voice, message pull-through, and citation accuracy alongside traditional traffic metrics.
What we're helping clients do is map this to their actual content infrastructure, identifying the gaps between how their site is currently structured and what LLMs want to see, then building a prioritized roadmap to close it. It's one of the most tractable wins we're seeing in early 2026.
Guy goes deep on all of this... the AI maturity model for CMOs, how to think about the engineer-marketer divide, and where agent-to-agent web traffic is headed next. Worth the full listen.