AI has made that approach dangerous. AI-native SaaS companies are running gross margins of 55-70% due to compute-heavy inference costs, well below the 75%+ traditional SaaS benchmark, according to SaaSRise’s 2026 SaaS Benchmarks Report.

Usage-based pricing is all the rage (e.g., charging based on API calls, records process, or outputs generated), but without guardrails it’s painful for everyone; reps are selling something that changes all the time, and enterprise buyers are bracing for bills they can’t predict.

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It’s messy. But luckily, there are people who know how to fix it, like Fynn Glover, CEO & Co-founder of Schematic, and Peter Giordano, EIR at Scale Venture Partners.

Fynn Glover wants you to treat pricing right

Fynn Glover learned from his own pricing mistakes on the way to becoming an expert. He founded and ran his first startup, RootsRatedMedia, in 2011. By his own admission, he “made a mess of pricing that ultimately cost us a lot of enterprise value at the sale of the business.”

Now as the co-founder & CEO of Schematic, a monetization platform for high-growth software and AI companies, Fynn’s built a business on helping founders and operators approach pricing like the strategic practice it should be.

We’re going to follow Fynn’s expertise to determine whether your pricing is setting you up for failure and what you can do to get it back on track:

1. Why most “pricing problems” are actually product-strategy problems

2. The principles to set before you touch a pricing model

3. How to turn pricing into an ongoing practice

4. The six questions to ask customers before you set a number

Pricing problems are usually product problems

If you think you have a pricing problem, take two steps back before touching anything. It could be deeper than that.

Pete Giordano has spent his career leading growth at companies like VMWare and Google. Now he advises our portfolio companies, helping them navigate GTM and pricing.

Across dozens of conversations with founders, Pete discovered that, “Most of the time, what looks like a pricing challenge is actually a product strategy problem in disguise.”

Product strategy should be derived from the problem you solve, and that value (and the subsequent pricing) can shift based on your customer. Here’s an example:

The problem you solve shapes three things:

1. The pricing model (seat vs. usage vs. outcome)

2. The value metric (what you charge for)

3. The price ceiling (the economic size of the problem sets willingness to pay)

Then you need to fit it to the buyer: how they budget, how procurement approves, and what they compare you to.

Get this connection right. Otherwise, pricing will keep sending you down a spiral of second-guessing. Are we too expensive? Too cheap? Too transparent? Should we revise the pricing model?

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Here’s a quick exercise. Try to complete this sentence:

If you have to rack your brain to complete it, go back to the drawing board and fix your product strategy.

Set your company’s pricing principles before you set the strategy

Now you’re clear on product strategy. We’re still not ready to touch the pricing numbers (sorry).

You need to set pricing principles. Without them, every pricing discussion turns into a tug-of-war. The CRO is pushing discounts to hit the quarter. The CPO wants usage-based pricing. Growth wants fewer paywalls. Principles are decision rules that help you avoid this impasse.

Fynn runs Schematic’s pricing on these four core principles:

1. Be affordable early on.

2. Land and expand.

3. Share in the upside as you help customers grow and push usage-based charges later.

4. Avoid opaque coverage. Be extremely predictable for customers.

Principle #4 matters even more in the AI era. The margin squeeze and the unpredictable bills we started with usually have the same fix: hybrid pricing.

Charge a predictable base fee, add a variable component tied to the value customers get, and put guardrails around it (usage bands, caps, or prepaid drawdowns). Margins stay protected, and the buyer’s finance team knows what they’ll pay. Start predictable, then layer in usage-based charges as customers trust the value, which is exactly what Fynn’s principle #3 describes.

They work for Schematic, given its stage of growth. Yours might look completely different depending on your specific product or stage. The point is to have a set of principles every department can get behind without making life harder for customers.

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Build a pricing practice that evolves with the product

Pricing is just part of the revenue equation, yet companies put the majority of their effort into quantity. There’s one question Fynn likes to ask orgs: Is pricing as fleshed out as engineering or sales? Majority of the time, orgs don’t even have a dedicated pricing function, let alone one on par with other core functions.

Now that AI costs and customer value shift faster, pricing and packaging need to change more often than a once-every-few-years overhaul.

Imagine the downstream effects on revenue if you focused just 10% more on pricing. Here’s how you turn pricing into a practice that enables you to do that:

1. Find your “pricing czar”: Product teams can end up nickel-and-diming every feature because every PM thinks their baby is special. Pricing should only be owned by people who are trained in monetization, packaging, customer value, and the tradeoffs between them. Have one person on the team own pricing unilaterally. They’re the one taking the shots and making the calls, with a mandate from the CEO. The czar owns the decision; the monthly cross-functional meeting supplies the inputs and checks the bias..

2. Ownership by stage: According to Fynn, pricing ownership should evolve with the company.

   • Below $10M ARR, the CEO should own it, full stop.

   • From $10M to $50M ARR, hand it to product. They should be accountable to a roadmap that makes the company money.

   • Past $50M ARR, hire someone whose full-time job is pricing, reporting to product with a dotted line to finance and the CEO.

3. Split pricing work into two speeds: The big, infrequent stuff (a pricing overhaul twice a year) and the small, constant stuff (tweaking trial limits or testing a model in a single enterprise deal).

4. The mechanism: Every month (yes, monthly, not quarterly), pull together reps from sales, product, engineering, customer success, marketing, and the pricing czar. (If you don’t have all those departments yet, do your best to speak to each of those areas distinctly, even if they’re owned by a single person.) Give pricing two hours on the calendar. Pick 1-3 experiments to run over the next 30 days, assign owners, and come back with results at the next meeting.

Build your pricing research kit

Pricing research, AKA willingness-to-pay conversations, is necessary, ideally before you build the feature. Get your prospects or customers in a room and ask these six questions to gauge how valuable they believe your product is. Failing to do so makes it difficult to prioritize what to build, and you only learn whether customers will pay after launch. To set the conversation up for success:

Below is a list of questions to ask your customers about pricing:

1. Value proposition: What specific challenge could this solve for you? Which features stood out? On a scale of 1 to 5, how likely are you to buy this at a fair price? Don’t mention the price. The goal is to understand perceived value, assuming you’re fairly priced. A two means back to the drawing board. A five is a great sign.

2. Relative value: How valuable is [product] relative to tools you’re already paying for? What budget would this come from? Have them summarize what they spend on other tools and rate your value against them. If they say you’re worth 50% of their $100K Salesforce contract, they’re telling you they see you as a $50K value. Bonus: you learn where they’re already spending money.

3. Price metric: Put several candidate metrics on the page and ask: Imagine you’re happy with the product a year into the contract and the price goes up 50-100%. What metric moved that made you believe I earned that increase? A clear answer points to your value metric. A blank stare means the metric isn’t intuitive.

4. Packaging schema: What do you like, what do you dislike, and which package would you choose? Bring your best packaging hypothesis. Put it into a good-better-best table without pricing. You’re trying to understand how customers expect the product to be packaged and purchased.

5. Max willingness to pay: At what price would this become totally prohibitive? What’s the most you can spend without needing someone else to approve it?? Later, introduce a price and use multiple-choice answers. “I’d buy immediately” signals underpriced. “I’d need significant internal approval” signals overpriced. You’re aiming for the middle.

6. Other influences: Besides pricing, what influences your decision to buy a product like this? Give them a list to react to. This helps you understand what drives the purchase and gives your champion ammunition if they aren’t the economic buyer.

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Your next steps:

• Complete the one-sentence value statement. If you can’t, fix product strategy before you touch price.

• Pick five recent customers and run the willingness-to-pay conversation this month

• Ask your team: is our pricing function as important to growth as engineering or sales? If not, why not?

• Name a single pricing owner by stage (CEO under $10M ARR, product from $10-50M, a dedicated pricing lead above that) and write down 3-4 principles they’ll use to break ties

• Put a monthly 2-hour pricing meeting on the calendar with sales, product, engineering, success, and marketing

• Pitch your own pricing in the mirror, or replay your last enterprise close. Did it sound confident or fumbled?

Craig Rosenberg is the Chief Platform Officer at Scale Venture Partners, where he works with portfolio companies on GTM strategy and execution. He was the co-founder of TOPO, which was acquired by Gartner, and the host of The Transaction podcast.

“Nobody cares that you shipped.”

Shipping a product doesn’t mean customers will use it. Many product orgs conflate releasing something with delivering value, but the release is only the beginning. Bruno Aziza breaks down how teams can successfully launch a product and make sure it actually lands.

Nobody Cares That You Shipped.

“How Anthony Pierri helps B2B companies with razor-sharp positioning”

Some people’s ideas are so brilliantly simple that they make you say, “Dang... I wish I’d thought of that.” If you’ve ever had an Anthony Pierri post come across your LinkedIn feed, you’ll know the feeling. We hosted Anthony at a recent Scale Marketing Council to shake up the stodgy positioning traps many B2B companies fall into. Here’s a deeper dive into how and why he zeroed in on homepage positioning for B2B SaaS companies as his One Thing.

How Anthony Pierri picked one thing to be known for

“Why ‘traction’ can hurt your first round”

You have pilots in progress, paying customers, some early revenue, and a credible team investors can believe in. Surely that should make raising your first round easier. Not necessarily. Maria Rotilu of Openseed VC explains the “€50K ARR trap”: the uncomfortable middle where you have too much traction to be evaluated purely as a conviction bet, but not enough to make the growth story undeniable.

Why “Traction” Can Hurt Your First Round

“The mistake GTM teams are making with AI is very familiar”

If you’ve also heard enough about the “importance of the foundation before you even attempt to build agents for GTM” and wondered what that “foundation” really is, Crissy Saunders explains it in detail, including how it changes based on the job an agent is meant to perform.

SubstackThe mistake GTM Teams are making with AI is very familiar…

“AI anxiety in sales: what you can actually control”

Across a dozen conversations with founders, CROs, senior executives, and reps, John Barrows found that the common sentiment around AI is full-blown ANXIETY. If AI has you excited and worried in equal measure, John’s Substack speaks directly to that tension.

AI anxiety in sales: what you can actually control | JB Sales

John also came to Scale’s Sales Council to tell us what will tank outbound (hint: relying on AI without human judgment is a big part of it) and how to revive your sales messaging:

Sales-Ready Messaging in the AI Era | Scale Sales Council

“Win the answer, not just the citation”

Speaking of AI citations, Tim Sanders (Chief Innovation Officer at G2) nailed it on our Transaction podcast. One of the sharper takeaways:

Marketers need to write answer-shaped content, not message-shaped content. Content structured as problem-solution-feature-benefit-CTA reads as “vendor speak” and lowers model confidence, while FAQ-style, conversational content that mirrors real Reddit-thread discussions earns more citations.

Win the AI Answer, Not Just the Citation with Tim Sanders, Chief Innovation Officer at G2 - Ep 85

And ICYMI, the latest issue of How We Scaled This belongs somewhere on this list too, or so I’ve heard from the people who’ve read it: Launching a company out of stealth

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Craig Rosenberg is the Chief Platform Officer at Scale Venture Partners, where he works with portfolio companies on GTM strategy and execution. He was the co-founder of TOPO, which was acquired by Gartner, and the host of The Transaction podcast.

The content contained in this post is based on the playbook, Launching out of Stealth, developed by Sydney Sloan, CMO Exec-in-Residence at Scale Venture Partners.

I’ve talked with a bunch of early-stage founders recently about launching into the market. They’ve been heads-down building their product for months and are finally ready to come out of stealth. Their tone is the same: pop the champagne, ring the bell, the hard part is done.

Yeah…no. Launching a product requires more than just building a product. Before you launch, you’ll need to develop a strong company narrative that articulates the problem you solve, how you solve it, and why customers should pay you to solve it. (Hopefully, you’ve talked to a bunch of customers before building to get a sense for the real problem and have built something customers want, but we’ll cover that another time).

Scale GTM advisor Sydney Sloan has advised dozens of startups on the journey from pre-seed to Series A and beyond, and she’s seen founders struggle to tell their own stories before they have a marketing team in place. But to get the runway to grow your company to the first million and more, they need to tell a compelling story that resonates in the market.

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In order to help more founders at scale, Sydney created the playbook for launching out of stealth. It’s a step-by-step guide over the course of 8 weeks, designed to fit into your already-bonkers schedule, resulting in a clear, compelling narrative and a solid plan.to kickstart growth.

This post covers part of a playbook we developed for launching your company out of stealth, including:

→ Building anticipation before launch

→ Activating the people who can amplify your story

→ Directing attention into relationships you own

→ Extending momentum beyond launch day

There are four core beliefs that underpin the playbook:

1. Go direct. Founders are best positioned to shape the narrative because they hold the insight that sparked the company and can explain, defend, and evolve the idea in their own voice.

2. Own the timeline. Share your news on your terms, through channels you control. If news leaks, don’t just react to someone else’s narrative. Create a new conversation and guide it forward.

3. The story is the product. Treat your narrative as seriously as your engineering. The story is what convinces people to join your team, buy your product, invest in your company, or believe in your vision.

4. Launch again and again. A launch is a repeatable capability. After coming out of stealth, every major product milestone, market shift, or company evolution creates another opportunity to launch.

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Craft your company story

No one will care about your product if they’re not invested in your story. Before you worry about a logo, visual identity, social presence, or even the website, you need to nail down a compelling narrative.

GTM expert and startup advisor Scott Albro joined one of Scale’s Founder Councils with a stark diagnosis: “Everything is downstream of attention.” Every startup enters the market in obscurity, and it’s noisier than ever. Product alone no longer creates separation. Attention is the bottleneck.

Albro’s answer is what he calls the Attention Engine, a system for “engineering pull” instead of relying on push. Most startups are running close to 99% push on day one (cold outbound, ads, founder-led sales) and only 1% pull (people coming to you). The goal is to flip that ratio as fast as possible, because that’s the only way to hit today’s growth expectations. Albro’s suggested benchmark is 80% pull, 20% push.

The Attention Engine breaks into three parts:

• Narrative: what you want the market to believe

• Distribution: how you spread that narrative

• Network/market: where you spread it, through a network of high-leverage nodes you have to navigate

“Humans are wired to consume narratives, not information. Stories are essentially shortcuts for what matters, what has meaning, how you frame issues,” Albro told us.

And in the AI economy especially, narrative matters more than ever when product, content, strategy, and tactics are getting easier to replicate.

Here are the three questions you need to answer to write your story.

Think about explaining your answers to someone at a party who isn’t in your industry and has no idea what you do. In other words, be clear and more specific than you’d think is necessary.

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Scale portfolio company Bland, an AI voice platform, hit all three of these questions square on the head when they launched out of stealth with a $16M Series A.

Why now?

Voice AI is finally advanced enough to hold complex, extended customer service conversations, beyond just answering Interactive Voice Response prompts

Why you?

Co-founder Sobhan Nejad was motivated by a personal experience; his aunt couldn’t get through to her insurance company on the phone and as a result was denied medical treatment.

Why this?

Everyone can relate to the frustration of waiting on hold for ages in elevator music purgatory, only to find that the person on the call can’t help you after all. For the enterprise, that pain manifests as paying employees to sit on the phone all day solving the same problems over and over. The enemy Bland is fighting against is the antiquated customer service phone system itself.

Once you’ve answered these questions, your next step is to filter through what communications strategist Lulu Cheng Meservey has coined the Three Circles of Authentic Positioning: Truth, Relevance, and Usefulness.

The ideal messaging falls right in the middle.

Build the messaging foundation

The next step is to create a reusable messaging kit:

• The one-liner (10 words or fewer), not to be confused with your tagline. It’s the plain-spoken answer to “what do you do?”

• The 30-second pitch (3 sentences)

• Three message points that hit what you want the market to believe about your company

• Positioning statement (for internal use)

None of the above are meant to be polished copy for your website or press releases. At first pass, don’t overthink it; just get your ideas down. Then spend the majority of time refining it. The more clear you can make it, the better it will resonate. If you don’t have an emotional reaction by the end, you’re not there yet.

The point of honing the foundation is to get really good at telling your cohesive story so that it sticks and helps you stand out.

Taglines and marketing copy will come later.

Take Action

To put this framework into practice, complete these concrete steps:

• Complete the Phase 1 Worksheet: Download the playbook to access the full worksheet. Answer the three core narrative questions: Why Now (what changed in the world), Why You (your secret/earned insight), and Why This (naming the enemy/broken status quo).

• Build your core messaging kit: Draft your one-liner (10 words or fewer), 30-second pitch (3 sentences), and positioning statement. Define your three core message points and ensure each point is supported by at least two defensible proof points (customer metrics, quotes, product demos, or credentials).

• Apply the Three-Circles Filter: Test every claim to ensure it is verifiably True, directly Relevant to your target audience, and Useful toward your launch goals. Cut any message that fails any of these three tests.

• Get feedback: Pitch your one-liner to 10 individuals in your Ideal Customer Profile (ICP). If they cannot accurately repeat it back after hearing it once, rewrite it. Pay close attention to their initial questions to discover what is missing or unclear.

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  Kristina McMillan is an Executive-in-Residence at Scale Venture Partners, where she works with portfolio companies on integrating AI in GTM strategy and execution. She is a long-time GTM thought leader, early-stage founder advisor, and advocate for female founders. Her work can be found at Hopelessly Ambitious.

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This article was previously published on Topline.

Speaking on stage with me at LinkedIn, Maya Spivak (founder, Marketing.fan) described the perfect founder-brand use case: a founder had just landed their biggest deal yet, and not only had they never spoken with the buyer, but the buyer had never visited the company website. They’d been following the founder’s content and reached out based on a peer recommendation.

This is founder-led growth working exactly as intended.

Pipeline is the issue I hear from nearly every founder and GTM leader I talk to. Cold email response rates dropped from 8.5% in 2019 to 3.43% in 2026. What worked three to five years ago is far less effective today.

At this point, I get to pretend I’m a Jedi Master and introduce the single most powerful and efficient GTM motion available to a startup: founder-led growth on LinkedIn.

This isn’t about becoming a LinkedIn influencer, though that may be a byproduct. It’s about getting your unique narrative in front of your target ecosystem and driving real revenue.

The data is hard to argue with: LinkedIn’s own research shows companies generate 33% more leads when founders post regularly, with deal sizes 3.7x higher when prospects follow your executive team and deals closing 22% faster when buyers feel like they already know the founder. Sendoso’s analysis goes further: deal sizes are 120% higher when buyers follow the executive, and win rates climb 11% from a single executive post viewed before close.

You don’t need a massive marketing team to pull it off. As Scott Albro (GTM advisor, founder brand expert, and my co-founder at TOPO) puts it, “LinkedIn is one of the few places where companies at every stage can punch above their weight.”

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Founder Brand is More Than Just Personal Branding

At its core, founder-led growth is about having a human face for your company — one with the deepest understanding of the product and the problem, who can credibly speak to what your market cares about.

In a market saturated with AI-generated expertise, your original perspective is the one thing no competitor can replicate.

Done well, you become what Scott Albro calls “synonymous with the category.” Rather than posting company updates, you use your point of view to shape how your ICP thinks about their role, market, and key challenges.

Most teams optimize for reach and get lost in the noise. Founder-led growth optimizes for the audience that buys, refers, and stays.

After three years evangelizing founder brand on LinkedIn, I’ve heard every objection: “I don’t have time.” “It feels self-promotional.” “I tried it and nothing happened.” “I’m not a writer.”

But engaging on LinkedIn is a skill you can develop, not a talent you’re born with. Founders who commit see a consistent progression. The first few months feel like talking to yourself. Then something shifts: a buyer you didn’t know DMs you or a prospect mentions to a sales rep that they loved one of your posts. By month five, content-engaged opportunities are showing up in the forecast and closing faster. By month eight, candidates are citing your posts in job applications. The ones who quit before month three never find out.

Trust comes before interest in the product, not the other way around. Gal Aga (CEO, Aligned) describes the sequence: people listen, feel deeply connected, trust you, then check out what you do.

The discomfort of posting is real but temporary. The question is how to do it. Let’s focus on five key areas to launch your founder brand:

1. The audience ecosystem: who you’re writing for

Beyond defining the audience you’re writing for and their roles, the higher-leverage move is mapping the ecosystem your buyers already trust (i.e., the influencers, analysts, bloggers, etc.). Make a list of 50 to 100 and start consuming their content. Follow the trends shaping your market. The goal is to get them engaging with you.

One early-stage cyber security founder posted two to three times per week and commented selectively on independent analyst posts. Today, four of his top 10 influencers regularly engage with his content, one mentioned him in an article his sales reps now use as an icebreaker with target CISOs, and meetings have followed.

2. The narrative: what you’ll tell the audience

The single most common mistake founders make is talking only about their technology. Your audience wants insights, not product pitches.

To rise above the noise, you’ve got to deliver a big, differentiated idea. Marc Benioff took over CRM with his “no-software” narrative, and we know how the rest of that story went.

Here are three narrative types and how each has played in the market:

Keep in mind that these story types are not mutually exclusive — someone’s personal journey can lead to a transformational shift, and so on.

Your narrative evolves like a product: ship it, see what resonates, and adjust.

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3. Execution: take your narrative to the market

Step 1: Create

A few tactical elements matter most:

Your hook — the first line — is your scroll-stopper. If it doesn’t make someone pause, the rest doesn’t matter. Treat every post as a market test: Gal Aga rewrites any post that isn’t pulling one to two Likes per minute within the first 15–30 minutes.

Don’t overthink length. LinkedIn data shows 400 to 800 words generates nearly 3x more engagement than posts under 50 words, but exceptions exist in both directions. The rule is depth of value, not word count.

Alec Paul (founder, SalesBrand) calls the sweet spot the “prolific zone” — the narrow band between obvious and crazy, where your content is authentic, polarizing, and relevant enough to make your ICP feel something. His benchmark: If less than 10% of comments are pushing back, you’re playing it too safe. A contrarian reply from your ideal buyer is worth a hundred “great post!” reactions.

One more lever: comments. Many current LinkedIn influencers built their following by commenting before they ever posted, and most still do. Same rules apply: add value to the “conversation,” don’t pitch.

Step 2: Distribute consistently

Consistency is often a design problem. The founders who do this well treat content creation like pipeline generation: they build a repeatable process and run it whether they feel like it or not.

You’re already generating the raw material every day: every customer call, sales conversation, and product decision is content waiting to happen. Some systems that work:

• Voice memos after meetings. A 90-second voice memo, stockpiled, becomes a content bank of pain points and objections, hook ideas, and scar stories.

• Batched writing. Gal Aga blocks Sunday mornings to write three posts for the week: one scar story, one contrarian take, one customer insight.

• Prompts for when you’re stuck. A mistake you made, a recurring customer question, a belief you’ve changed, what most energized you. Each is a post.

On AI: Use it as an editor and pattern-finder, not a ghostwriter. Feed it your voice memos for post angles; feed it your past posts to surface recurring themes. Let it sharpen the hook, but don’t let it replace the first-person voice that makes the content worth reading.

Step 3: Amplify

Once your organic content is generating real engagement, amplify it. LinkedIn’s Thought Leader Ads (TLAs) let you promote posts from individuals rather than company pages, and they perform in ways standard ads don’t.

For startups specifically, TLAs drive 7.6x more engagement than other paid formats, with 1.5x higher click-through rates, 45% more demo requests, and 30% more efficient cost-per-click. The reason is simple: a post from a real person that your audience already recognizes reads less like an ad and more like what they were already engaging with.

Start by putting budget behind your highest-performing organic posts. Don’t guess what will resonate at scale — let the audience tell you first, then spend behind it.

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4. Conversion: turn the founder brand into founder-led pipeline

When an ICP prospect engages with your post — Likes, comments, or follows — they’ve self-identified as interested. Act immediately: send a connection request with a short note referencing the post, opening with a feedback ask rather than a pitch. Not “Can I show you a demo?” but “Would you be open to a 30-minute conversation on what you think about [topic]? I’d love your take.”

One founder I work with generates six to eight meetings per week from this play; others report roughly 40% conversion to meetings — a rate no cold outreach tactic touches. The content warms them up and the DM closes the gap.

For top accounts and key influencers, the DM should come from the founder. A founder reaching out to an engaged VP or C-suite prospect is a fundamentally different conversation than an SDR cold sequence. For non-top tier accounts, hand the engaged prospect to your SDRs or AEs — the LinkedIn warmth still lifts conversion.

5. Measurement: the right metrics at the right time

Founder-led GTM is hard to measure. Trust, resonance, and reputation don’t fit on a dashboard. They show up in deal velocity, inbound DMs, and the way people talk about you when you’re not in the room.

Still, there’s a clear progression of indicators. If you track the right ones at each stage, you’ll be less likely to abandon something that’s actually working just because the pipeline number hasn’t moved.

First 90 days: Track leading indicators (i.e., Likes, comments, and click-throughs to your profile). These are intent signals that become pipeline with consistency.

Next 90 days: Monitor your content-influenced pipeline, adding a “content-influenced” deal stage in your CRM, tagging every prospect who has engaged with your content, then measuring their deal velocity and win rate. Train sales to log when prospects mention your posts on calls.

Six months in: Measure direct pipeline impact. Inbound founder-brand leads come via your LinkedIn posts; outbound come from the DM play.

Plenty of tools handle the tagging. Factors.ai, Fibbler, Dreamdata, and Revsure come up most often in conversations with operators.

The numbers from founders who do this well are not incremental. In one month, Kacie Jenkins (former SVP Marketing at Sendoso, now Head of Marketing for Claude Code) drove six figures of qualified pipeline through DMs alone. At Wynter, Peep Laja attributes roughly 80% of new signups and demo requests to LinkedIn. Gal Aga’s rule is the clearest target I’ve heard: if 20% or more of your pipeline mentions your content, you’ve won.

Founder Brand Works Because People Buy From People

If brand is the market’s perception of you, founders have a strategic obligation to shape that perception in a way that drives revenue. The payoff compounds in ways nothing else in your GTM stack can match: Every public conversation with a customer creates a feedback loop that keeps you tied to the market, and as you scale, your founder brand and your company story reinforce each other — each one making the other more credible.

Founder-led growth is one of the most reliable and efficient levers available to any startup. Show up consistently with a real point of view, build the systems that drive it, and measure the right things at each stage.

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Craig Rosenberg is the Chief Platform Officer at Scale Venture Partners, where he works with portfolio companies on GTM strategy and execution. He was the co-founder of TOPO, which was acquired by Gartner, and the host of The Transaction podcast.

I’m hosting a new kind of event for founders and GTM leaders. Instead of abstract presentations, we’ll offer real, interactive conversations and workshops with a few of my personal tech heroes: Scott Albro (former founder & CEO of Topo), Cristina Cordova, Chief Operating Officer at Linear, and Chris Degnan, first rep and former CRO of Snowflake. It will be live at LinkedIn in San Francisco so you be around your startup peers as we take on crucial topics in driving growth.

Here’s a preview of Scott’s session, which will be all about building your startup’s attention engine:

Together, we’re learn how to create demand, sharpen positioning, and build a repeatable GTM machine in competitive and volatile markets. We’ll also have a lot of fun. Anyone from the Scale community will be invited in.

Details below:

📆 Thursday, March 26

⏰ 1 to 6 pm PT

📍 LinkedIn Headquarters in San Francisco (222 2nd St, San Francisco, CA 94105)

Register here.

To reach one prospect, an SDR had to:

• Add the prospect in Outreach

• Pull first-party data from Snowflake, Salesforce, and Tableau

• Pull third-party data from ZoomInfo, Google, and LinkedIn

• Sort through 30,000+ Outreach sequences to choose the right fit

They repeated these steps dozens of times a day. Over time, reps got tired, skipped research, and reused the same sequences. This led to generic and inaccurate emails that prospects couldn’t relate to.

To fix this, Snowflake rebuilt its workflow using AI and orchestration to automate the most time-consuming parts. The results have been strong: more relevant emails now earn them a 7.6% reply rate (15x higher). What’s more, they’ve booked more than 2,000 meetings from just 55,000 prospects.

At Scale’s GTM AI Summit, Jeff Long, Senior Technical GTM Operations Manager at Snowflake, explained how his 300-person SDR team is using AI orchestration to send better outreach at scale, avoid burnout, and spend more time on pipeline-generating activities.

This article is based on Jeff Long’s presentation at Scale Venture Partners’ GTM AI Summit.

Use AI and orchestration to scale outreach

Many sales teams already use AI to quickly research prospects or draft cold emails. But if you’re just prompting your own LLM instance, you can only do this on one prospect at a time, which isn’t enough to help you manage hundreds of accounts.

Snowflake faced the same limitation. AI could help with individual steps, but it couldn’t support the volume their 300-person SDR team needed.

“We knew that AI could be incredibly powerful for our teams, but how do we make it scale without SDRs actually having to put prompts into a large language model and get these emails out?” says Jeff.

The answer was orchestration; specifically, with the integration platform Workato. Jeff describes Workato as “a layer that sits over your existing tech stack and connects tools that don’t natively talk to each other to perform different tasks one after the other, with the first action triggering each step automatically.”

Orchestration automates the sequence of tasks across your tools so the entire workflow runs on its own.

At Snowflake, this process starts in Outreach. When an SDR adds a prospect to a sequence, Workato pulls first- and third-party data automatically and sends it to Claude to draft the email.

Watch: Jeff describing how this workflow works

Validate your AI email drafts to avoid errors

One of the biggest lessons Snowflake’s SDR team learned was not to use the first draft of the email that AI generated. It might be accurate eight times out of 10, but there will always be drafts with irrelevant or inappropriate information. And when you’re prospecting thousands of people, those one-off mistakes add up to hundreds of emails that don’t resonate with the recipient or hurt your reputation.

Watch: Jeff on the importance of verifying emails

To avoid this, Snowflake added a validation layer that gives each email a 1-10 score and flags any draft below a score of seven for review. “The system reviews the draft for accuracy, tone, and sentiment, to make sure it’s right for the person that we’re sending it to,” Jeff says.

Once the rep has validated the email, Workato sends the final draft back into Outreach using XML.

Use XML to tag and extract key information consistently

AI outputs are often inconsistent. Even with good prompts, Claude or ChatGPT may add extra sentences, include headers you don’t need, or format things differently each time. This means you can’t use all the output, just certain parts, which adds back the time you saved from using AI in the first place.

Snowflake solved this by using XML to structure every AI-generated email before sending it back into Outreach. “XML is like a filing system with labeled folders organized into named sections that computers can easily read,” Jeff says. “It adds tags around the important parts of the email, so when you’re loading it back into Outreach, you get consistent outputs every time.”

With XML, the system extracts only the tagged fields—such as the subject line or body—and ignores everything else. This removes extra or unnecessary text and ensures the same structure every time. Instead of reps manually copying and pasting sections from an LLM response, the workflow handles it automatically and consistently across thousands of emails.

Here’s what an AI-generated email from this workflow looks like. It’s well-researched, relevant, and concise:

What Snowflake’s orchestration workflow looks like today

Snowflake’s orchestration workflow has expanded over time. In addition to drafting emails, the system now generates prospect briefs and call scripts for outbound calls, giving SDRs all the information they need in one place.

Here are examples of the brief and call script:

The entire end-to-end process—triggered by one action—replaces hours of manual research and writing for SDRs. Here’s what the advanced workflow looks like:

1. The SDR adds a prospect to a specific Outreach sequence, and then Workato takes over.

2. Workato pulls first-party data like product usage, account details, and internal insights an SDR would normally gather.

3. It pulls third-party data like company news, updates, and contact-level information.

4. It runs a web search through Bing to collect recent, relevant news.

5. It uses a Retrieval-Augmented Generation (RAG) workflow in Snowflake to identify relevant customer lookalikes to reference in the email.

6. Claude drafts the first email using all combined data.

7. The validation layer scores the email for accuracy, tone, and relevance, and flags anything that needs improvement.

8. Claude generates follow-up emails, a prospect brief, and a call script to support both email and phone outreach.

9. XML structures all outputs, and Workato loads them back into Outreach in a clean, consistent format.

This workflow originally took around 10 minutes when models were slower. Today, SDRs can add 20 prospects at once, and the system processes each one in two to three minutes, which is a huge time-saver.

Build specialized prompts to handle one task

A common mistake is asking one prompt to handle the entire workflow: research, summarization, email drafting, and follow-ups. Yes, the current AI models are powerful, but right now they work better when each prompt does one thing well and you orchestrate the tasks together.

So split the workflow into small, single-purpose prompts, each responsible for one clear task, and orchestrate them automatically with Workato or another tool of your choice. This improves the quality of each AI result and reduces how much manual work your team needs to do.

Test new workflows with a pilot team to earn their buy-in

Rolling out a new AI workflow is a major change that affects how reps work every day, so teams need time to understand it and trust it. If the workflow has too many problems at the start, reps will be reluctant to keep using it, and you’ll lose momentum.

Instead of introducing the new process to everyone at once, ease adoption by starting with a pilot team. A pilot helps you see where the workflow breaks, what needs to be adjusted, and what training the rest of the team will need before a full rollout.

Snowflake didn’t send the new workflow to all 300 SDRs on day one. Rather, they started with a pilot group of 10 reps. They created a Slack group, asked the reps to put half of their prospects into the new AI sequence and the other half into their usual sequence, and encouraged them to share what worked and what didn’t.

Because the group was small, reps felt comfortable pointing out problems, asking questions, and suggesting improvements. Their feedback helped Snowflake fix issues with the process and build a better product for reps, before rolling it out to the rest of the team.

AI prospecting is giving Snowflake’s SDRs 100s of hours back

Across most sales teams, SDRs spend a large part of their day on tasks that don’t directly create pipeline. They research accounts, check different tools for context, draft emails from scratch, and manage follow-ups. These tasks are necessary, but they take time away from the work that actually drives meetings and revenue, like cold calling or connecting with company executives.

Jeff explained that this is why he introduced AI and orchestration—to automate the tedious and time-consuming work that slows SDRs down. “We have no plans to get rid of our SDR teams or slow hiring. We want to automate some of their tasks so they have time to do all the other things they’re falling behind on,” Jeff says.

And with the manual work handled automatically, SDRs now spend more of their day on high-value outreach and also send far more relevant and personalized emails which has led to higher reply rates and more meetings booked.

AI hasn’t replaced SDRs and won’t anytime soon. But paired with orchestration, it makes SDR teams more productive and helps them hit targets faster.

More from the GTM team

• Craig Rosenberg on the State of GTM AI, published on Pavilion’s new GTM blog Topline (ICYMI, check out the full report here)

• Kristina McMillan on the evolution of AI SDRs, where they can be used to improve top-of-funnel efficiency, and what still needs the human touch, at least for now.

• Robert Koehler on using AI to coach reps on discovery, including the full prompts that dropped evaluation and reporting time from two to three weeks to two days

You can expect content from our events, including our summits, what’s working (and not) in AI for GTM teams, and near-real-time benchmarks. First up, Sydney Sloan, CMO at G2, walks us through search in the age of AI, from the basics of how it works to the strategic framework to help you capitalize on it.

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Want to switch your team’s focus from SEO to AEO (answer engine optimization)? Take a moment to consider how different those two media are.

Sure, both types of search are text-based. Yes, users still ask questions. But the way people ask questions has changed. Open your own search history to see: Do you really ask one question at a time anymore? Or do you ask a series? “It’s no longer question-and-answer,” says Sydney Sloan, CMO at G2. “The questions get really complex. It’s more of a chain of questions.” Further, you probably offer ChatGPT more context than you did Google—when searching for vendors, you tell it your tech stack, goals, and challenges.

Many marketers feel paralyzed because this upends the old playbook and because it all keeps changing. What does it mean for your marketing when buyers dictate to AI rather than type? Work in collaboration with AI chatbots? Aren’t exposed to your branding until late in the cycle?

That’s why Sydney took the stage at GTM 25 AI Summit to discuss what G2, the premier B2B review site, has learned about optimizing for AI search. G2’s own site is a major source of AI answers. Within, you’ll learn how you too can coax the new wave of answer engines to surface your answers when someone’s doing their research.

Watch the full session

AI is now core to the buying journey

LLMs set a land-speed record as the fastest-spreading work technology ever. Fifty percent of B2B software buyers say they’re more likely to start their search on LLMs rather than Google, according to a G2 survey of 2,000 companies. That’s up from 29% four months prior. Sydney feels confident it will continue to rise.

Here are the changes for your marketing team to consider:

AI wants complete answers in natural language

AI search tools browse the internet using the same old crawlers as search engines, but the similarities end there. Traditional search, if it can now be called that, produces a list of sources that probably include a link to your website. Whereas AI search aggregates one answer from many sources and may or may not link to your website. It probably also provides enough context that the user doesn’t even want to visit your website. This means that while there is some crossover value from all the authority your team has been building with SEO articles and FAQs, there are likely also major gaps.

“AI is searching for answers in natural language,” says Sydney. “So you’re going to want to think about the user-generated content where those answers may lie—in reviews on review sites. That’s where AI learns about what people like and don’t like, and how they compare products and weigh value.”

AI eats into your traffic

AI answer engines cannibalize your organic search traffic. That is their purpose: to save people the click and summarize long reads. That means fewer people will arrive at your website. But it also means that those who do are probably further along in their evaluation and better qualified.

“If you haven’t started thinking about how to optimize your speed from site visit to a meeting, you should be,” says Sydney. “Buyers arriving there are way further along in their research than before. You really want to understand that, and what the LLMs told them, which is based on user-generated content.”

AI answer engines seek consensus

If your brand and message are different everywhere they appear—if all the reviews and teardowns about your software say something different—you won’t have much influence on what the AI says. That’s because AI relies on consensus signal simplification, says Sydney. “When the AI says ‘thinking,’ it wants to give you the right answer, and so it’s looking across many sites for consistency or sources of higher authority. If everything people say about you matches, that’s likely to reinforce the narrative the AI search tool picks up on.”

Given all this, Sydney has arrived at three ways to switch your team’s strategy to generate AEO mentions.

Three ways to earn far more mentions in AEO

1. Build your brand where users live

Increasingly, LLMs are the front door to B2B buyer research. Marketers can expect less and less organic and paid traffic from other sources, but it’s not an all-or-nothing switch. This is simply about reallocating resources from your existing programs to what’s becoming the dominant way for buyers to shortlist vendors.

In G2’s survey, buyers say their number two source for unbiased information is software review sites. LLMs feel the same. AI search tools like ChatGPT and Claude rely heavily on forums, review sites, and self-publishing platforms like Medium. This creates a clear directive for marketers: If you want to be found in AI search, encourage more user-generated articles and reviews. “Only 5% of G2’s customers use an in-app review popup, yet they are all leaders. So, founders, don’t be nervous about putting questions in your product,” says Sydney. “Ask them for a review at moments of success. For example, the Vanta team asks for a review when someone gets their SOC 2 compliance. That’s ideal.”

The quality of those reviews matters, and you must earn real ones. G2 knows that when an individual comes back to update their review, that indicates real value, so G2 gives it higher priority. G2 isn’t alone in carefully ranking reviews by such signals, and AI follows its lead. All these systems are trying to approximate real, human-assessed value. For this reason, Sydney advocates running a “review refresh” campaign to ask your reviewers to make updates—and to encourage real honesty. A five-star review may actually be less believable than a slightly lower one.

“4.6 is the ideal review balance for believability,” says Sydney. “People want to see constructive feedback. Your role as marketer is to ensure you are addressing questions so other customers can see. It’s like when a hotel general manager replies to a questionable review. It makes you feel good about them and now you still might book to stay there.”

Get your founders involved in those conversations in a way that feels natural to them. People trust real people, and founders have credibility and star power. This takes a real time commitment, so prep them for that, and convince them to carve out time to contribute on their own to LinkedIn, X, Reddit, or elsewhere.

2. Retool your content strategy for greater relevance and consistency

As buyers do more of their research earlier, how do you engage them? In G2’s survey of 2,000 companies, most buyers said they can do their own research and only want to talk to salespeople during the evaluation. This means your content needs to reach those buyers earlier, which requires that you know them even better than you do today.

Sydney recommends revisiting your persona and their jobs to be done, and creating more tailored content to match those personas and jobs. Try to distribute more of it through user-generated content around the web. This isn’t a huge departure from content marketing today—building a relationship and demonstrating value in advance of an evaluation—but it does mean shifting the balance toward more of a distributed model, off your main properties.

“Today this means building out your AI personas and ideal profile, and ensuring they are constantly teaching themselves, updating themselves, and challenging themselves,” says Sydney. Her team automatically feeds Gong call summaries into a spreadsheet, which updates their AI knowledge base. “And then ask yourself, how do we integrate those personas into the content publishing workflow? Not a single piece of content should leave your company if it hasn’t been tested or validated against this persona.”

Build a persona for the “LLM” buyer, too. “LLMs are one of your new customers,” says Sydney. “Build content to train the LLMs separate from your buyers’ jobs to be done. I’ve seen people build whole shadow websites with hidden content for LLMs to index, in the language and tone they want it to pick up. Or maybe their content editor builds their own blog as a separate authority, answering those exact questions.”

Finally, ensure your content is consistent. For traditional search engines, you’d get dinged for too much repetition. In AI search, that’s actually the key to training the algorithm. You want to syndicate your reviews, key messages, and top content across many places to help nudge that consensus.

3. Get your PR game back on

Other sources LLMs value highly are traditional media outlets such as CNBC, Harvard Business Review, TechRadar, and other journalistic publications. This means that PR is back in fashion.

“For a while, marketers were like, ‘PR doesn’t play anymore, we’re just going to be on LinkedIn,’” says Sydney. “But now everything I do—and I don’t care what it is—I put out a press release about it. Because that gets indexed. I also went back and hired a PR agency and am investing there.”

In many ways, this is still the same old PR game as ever, only now it’s about getting indexed by LLMs to influence their answers. As always, search for the moments of unique, ownable drama. Sydney’s team saw the MIT study claiming that 95% of AI projects are failures and didn’t find it credible. They ran their own study with a counter-narrative and pitched it to VentureBeat and Forbes. “Publishing your own first-party research has never been more important,” she says.

While the PR game may not have changed, the publications have. Many have gone through decades of declining budgets and cyclical firings, so there are fewer writers covering larger beats. They tend to want to write about the biggest existing players in your space, so it may be more difficult to find an angle. But there are also plenty of pay-to-play outlets where this barrier doesn’t exist. A Forbes Councils subscription can cost as little as $1,600, and Fast Company has a similar program. “You write it and their editors still vet it, so they’ll go back and forth with you,” says Sydney. “And if you get a lot of engagement and your content is relevant, they’ll all also ask you to answer questions in other editorial content. When you share that on your social media, you look authoritative.” And of course, that may get indexed by AI crawlers.

Also pay attention to the AI citations you see when asking AI about your space. Take note of any writers or influencers with a preexisting following. Consider hiring them as a content strategist or expert contributor. “Clay did a great job of this. I didn’t know who Clay was a year and a half ago and now they’re everywhere,” says Sydney. “They hired like 75 influencers for a two-month period and completely drowned LinkedIn. Everywhere you looked, people were talking about Clay.”

The important thing is to start right now

If you aren’t yet building or executing a strategy for how you’re going to win in AEO, now is the time to begin. Don’t feel bad about what you’re starting from. Everyone is still trying to figure it out, and there isn’t a playbook yet.

What is certain is that you should be focusing more on user-generated content and ensuring that everything people say about you is consistent and indexed. Continuously capture all that and feed it back into your team’s own LLMs, and run content through those synthetic personas—including a persona for the LLM. Some teams are going as far as to create undiscoverable but indexable sections of their website just for LLMs. There are no particularly wrong answers, aside from waiting to see how things play out. Much like the early dot-com rush to secure domains or SEO rush to early search authority, those teams running active AEO experiments are the likeliest to figure it out and edge out the competition.

More from the GTM team

Check out all sessions from our AI GTM Summit on Substack or YouTube.

Use our marketing planning template to lay out your strategy for AEO and other initiatives in 2026.