What B2B Founders Are Saying in 2026

Introduction

This is a curated editorial drawn from in-depth conversations with 63 practitioners — founders, C-suite operators, and functional leaders building B2B companies. It is not a survey. There are no aggregated statistics or composite opinions. What follows is a collection of direct voices, organized by theme, so you can hear how different people building real companies are thinking about the same problems.

The people quoted here range from bootstrapped solo founders at pre-revenue to operators running $10M+ ARR businesses. Their companies span dev tools, vertical SaaS, compliance software, healthcare AI, and publishing technology — alongside the advisors, coaches, and consultants who work directly inside those organizations. The value isn’t in consensus — it’s in the texture. When a CMO who was previously a customer of his own product talks about CAC, or when a founder who’s closed 250 enterprise deals says he never did cold outreach, those specific details are what make the insight portable. Read for the pattern, but trust the specifics.

This report is organized in two sections: SaaS Voices (founders and operators building software products) and Leadership & Advisory Voices (coaches, consultants, and advisors who work across multiple B2B companies). Same themes, different vantage points.

Part I: SaaS Voices

Founders and operators building software products.

Insights & Perspectives

There’s a particular kind of founder clarity that only comes from having spent years in one narrow problem space. Several practitioners described the experience of watching others treat a solved problem as unsolvable — and the frustration of knowing exactly what was coming for them.

Joel Griffith — CEO & Founder, Browserless

Browserless provides headless browser infrastructure for developers, handling the messy edge cases of browser automation at scale.

“It’s managed complexity that looks like magic and you’re following every basic edge case for 10 years. That’s all it is.”

Joel was describing why prospects think they can build their own solution. The confidence is real, but the edge cases aren’t visible until you’re six months in. This is the core pitch problem for infrastructure and tooling companies: the customer can’t see the decade of decisions baked into your product.

“You almost have to be just ignorant enough not to know what you’re getting yourself into just so that you do it.”

Fazy — Founder/CEO, Corent Technology

Corent builds SaaS transformation tooling that helps ISVs convert existing software to SaaS architecture.

“The bottleneck is not the technology. The bottleneck is the mindset.”

“Don’t major in minor things.”

Fazy came back to this repeatedly when discussing why SaaS migrations stall. The technical path is often clear. What blocks companies is the unwillingness to commit to an architectural direction and stop relitigating it. Both quotes travel well outside the migration context.

So what: The product insights that matter most to buyers often live inside your operational complexity — the edge cases you’ve solved that they haven’t hit yet. Your job is to surface those costs before the prospect tries to DIY their way into them.

Growth & Scaling

Enterprise growth at the $5–15M ARR stage tends to hinge less on acquisition volume and more on whether both sides of a deal actually understand what’s being bought. Multiple practitioners described this as a clarity problem.

Daniel Stradtman — CMO, Bloomfire

Bloomfire is a knowledge management SaaS platform serving mid-market and enterprise customers. Daniel was a Bloomfire customer before he became its CMO.

“I actually bought Bloomfire — I was a customer before I was CMO.”

“You’re not just buying zeros and ones on a screen, you’re buying a partnership.”

Daniel’s credibility in enterprise sales conversations comes partly from having been on the buyer side. His framing of the software purchase as a partnership decision — not a features comparison — is the kind of message that lands with economic buyers who’ve been burned by implementations that stalled post-signature.

“There’s no search volume behind that new category until you create it. But you’re going to find plenty of search volume behind those business problems that you’re trying to solve.”

This is a direct challenge to the “we’re creating a new category” positioning common among early-stage SaaS companies. Buyers aren’t searching for your category name. They’re searching for their problem.

So what: Stop positioning around what your product is and start positioning around what your buyer is already searching for. If you’re telling an enterprise prospect they need a new category, you’ve already made the sale harder.

Pricing & Revenue

The revenue conversations in this cohort were less about pricing models and more about the risks of optimizing for the wrong thing — growing too fast, chasing vanity metrics, or building a business where one dependency can shut you down overnight.

Sarah Jenkins — CEO, Genesis Digital

Genesis Digital bootstrapped Kartra, an all-in-one marketing platform, to $10M ARR without outside investment.

“Every time you have the SendGrid or the Constant Contact or the Survey Monkey, everything you API plugin when they tell you to update your API, if you don’t, you lose that service. You could wake up and your business is down.”

Sarah was making the case for reducing third-party API dependencies as a revenue protection strategy — not just a technical one. At $10M ARR bootstrapped, a single integration failure is a retention crisis.

Francis Brero — Co-founder, MadKudu

MadKudu builds predictive lead scoring and pipeline intelligence for B2B SaaS companies.

“Trying to rush too quickly to monetary ROI can actually burn you because you’re going to have to take some shortcuts and those shortcuts are really hard to fix after the fact.”

Francis was talking about the pressure to show revenue impact quickly from new tools or GTM investments. The shortcuts he’s describing — loose attribution, compromised data hygiene, skipped qualification steps — tend to show up later as churn or pipeline inflation.

Patrick White — Founder, L-Spark

L-Spark is a startup accelerator that has worked with over 130 early-stage companies.

“Revenue solves all problems. If you focus on gaining revenue, it’ll lead to a lot of good things — you’re showing traction, you’ll have conversation with investors, the banks like it, accelerators like it.”

At the earliest stage, nothing substitutes for actual revenue. That framing is stage-specific: it applies at $0–$2M ARR. At $5M+, the question changes to which revenue, at what margin, with what dependency risk.

So what: Revenue is the right obsession at $0–$2M ARR. At $5M+, the question shifts. Both framings are correct — they’re just for different stages.

Customer Acquisition & GTM

The GTM section had some of the most operationally specific quotes in the cohort — people who have run the experiment and can tell you the exact input.

Zander Deitz — VP of Sales, Productive

Productive is a project management and agency operations SaaS platform.

“Not all revenue is good revenue.”

Short, but said in the context of early-stage GTM where the pressure to close anything leads to taking on customers who churn early, require excessive support, or distort your product roadmap.

Joanna Ridgway — SVP Global Sales, Cien.ai

Cien.ai builds CRM data quality and GTM intelligence tools for B2B sales organizations.

“You might query your CRM to try and understand where are my best lead sources or how many countries am I operating in and you simply can’t understand that without months of work. And luckily we can resolve that in three to five business days.”

The “months of work” framing is the kind of before/after contrast that makes enterprise value propositions land. The specific time claim — three to five business days — is the kind of precision that separates a product pitch from a consulting pitch.

So what: If you’re still building your ICP definition from intuition rather than closed-won CRM data, you don’t have a GTM problem — you have a data quality problem. Fix the data before you run more campaigns.

AI & Product Innovation

No theme generated more tension in this cohort than AI. The practitioners who were most credible on this topic were the ones who had shipped something, not just evaluated tools.

Fazy — Founder/CEO, Corent Technology

“We have startups that they spend half a million easily and they said, ‘Hey, I could have done this for you 18 months ago in a week.’”

Fazy was describing how his platform compresses SaaS build timelines — but the quote also captures a broader market dynamic: the cost of not knowing what tools now exist is increasingly being measured in six-figure build budgets.

Daniel Stradtman — CMO, Bloomfire

“There is a lot of rushing into the layer of AI on top of data that really isn’t ready for it.”

This is one of the clearest practitioner warnings in the dataset. AI on top of bad data produces confident, wrong answers. Daniel was describing what he sees across the knowledge management space — companies deploying AI search on top of unstructured, inconsistent knowledge bases and wondering why the outputs aren’t trustworthy.

Mo — CEO, Emitter

Emitter builds AI receptionist tools for healthcare practices, targeting the 20–25% of inbound calls that go unanswered.

“That pitch works very well if you’re trying to raise capital. That’s a place to talk about category creation. But for customers, really what matters is how do you solve their problem.”

Mo was drawing a sharp line between investor messaging (category creation, market size) and customer messaging (your specific problem, solved now). The mistake is using the investor deck language with buyers.

Chris Cade & Steve Boey — Co-founders, SaaSBerry Labs

SaaSBerry Labs helps B2B SaaS companies add AI capabilities to existing products.

“Customers don’t want workshops. They don’t want days and days of figuring things out. They have a pretty good idea of what the use case could be and they immediately want to go right into building out an MVP prototype.”

This is a meaningful signal for anyone selling AI implementation services. The market has moved past exploration — buyers want to build.

“In the next 12 months, things are moving so rapidly. If you’re not investing, you’re already falling behind.”

Diana — CTO, Netlify

Netlify is a web development platform that has been operating for 10 years and reached Series D. Diana leads its engineering organization.

“Prepare your team for this. Find opportunities to get people comfortable. You’re going to have a mixed bag of cynics and early adopters and it’s going to be uncomfortable for everybody because the rate of iteration is happening so quickly.”

Diana was addressing AI adoption inside engineering teams — the change management piece that technical leaders often underestimate.

So what: The AI implementation failure mode isn’t moving too slow — it’s layering AI on top of processes and data that were never cleaned up. Fix the substrate before deploying the model.

What the Numbers Actually Say

A few specific metrics from this cohort are worth holding onto — not as benchmarks, but as reference points for your own operation.

85% of B2B buyers establish their purchase requirements before contacting any vendor — per the 6sense 2024 Buyer Experience Report, corroborating what Heath at Mixmax described in conversation. If your GTM motion still depends on demos as the primary education vehicle, that model is increasingly out of sync with how buyers actually make decisions.

Top AI-first companies are reaching $5M ARR in 24 months, versus 37 months for SaaS companies a few years prior — a 13-month gap, per Stripe’s 2024 annual letter, cited by Heath Barnett. This isn’t an argument to rebuild your stack — it’s context for why the competitive clock is accelerating.

20–25% of inbound calls to healthcare practices go unanswered, according to Mo at Emitter — a figure corroborated by multiple industry benchmarks showing 24% for hospitals, 27% for dental practices. He built an entire business on this single operational gap. The lesson isn’t about healthcare — it’s about finding the missed calls in your own target market.

80% of AP staff time is typically spent researching how invoices should be coded, according to David Stifter at Predict AP, which builds AI-powered accounts payable automation for mid-market real estate. One customer discovered $40,000 per month in late fees they hadn’t known were accumulating. The insight here is that the ROI case for workflow AI often hides in error costs that nobody’s currently measuring.

A single SEO blog post generated over $1M in new ARR for Jonathan Brun’s company, Nimonik, a 16-year-old bootstrapped compliance SaaS. The post was written after one conversation with an industry insider about a regulatory change. Content ROI at this level is rare — but it requires being close enough to your market to know what’s about to matter before it trends.

Frameworks SaaS Practitioners Are Using

Inbound-First Growth Stack (Mo, Emitter): Build customer acquisition in sequence — bottom-of-funnel content first to capture high-intent searchers, then paid ads to validate keywords, then organic SEO using paid insights, then outbound only after ICP is well-defined. Emitter runs 70% inbound, 30% outbound from this approach.

AI Employee Onboarding Ramp (Mo, Emitter): Adopt AI tools the same way you’d onboard a new hire — start with limited, low-risk tasks, observe performance, then progressively expand scope. Avoids the change-management failure that comes from deploying AI broadly before trust is established.

Mentor-the-LLM Development Model (Diana, Netlify): Experienced developers treat LLMs like junior developers — providing direction, reviewing outputs, and correcting before deployment. Diana’s framing: deep CS knowledge is what separates useful AI-assisted development from reckless AI-assisted development.

The Million-Dollar Blog Post Method (Jonathan Brun, Nimonik): Conversations with industry insiders surface emerging regulatory or market pain points before they appear in search data. Turn those insights into SEO content immediately. The competitive advantage is the conversation, not the writing.

Tribal Knowledge Centralization (David Stifter, Predict AP): Identify operational knowledge held by a single long-tenured employee, then encode it into an AI system so the business doesn’t depend on any one person. David applied this to AP coding rules across 12,000 legal entities at a client — the knowledge transfer that used to take years now happens at onboarding.

Revenue Bow Tie (Heath Barnett, Mixmax): Replaces the linear funnel with a continuous flywheel where sales, marketing, customer success, and support all contribute to one unified customer journey. The insight is that post-sale investment directly drives pre-sale credibility through retention metrics and case studies.

Qualify, Qualify, Qualify (Edgar, Regpack): A consultative sales method focused on deeply understanding the prospect’s organization, change motivation, and fit before advancing any deal. Edgar’s team converts roughly 30% of high-intent inbound leads — the qualification filter is what makes that rate possible without burning reps.

Part II: Leadership & Advisory Voices

Coaches, consultants, and advisors who work across multiple B2B companies — offering perspective that comes from pattern recognition across many organizations, not just one.

Insights & Perspectives

Jonathan — CEO, Product Savvy Consulting

Product Savvy Consulting advises early-stage SaaS companies on product development strategy and avoiding costly build mistakes.

“It’s never the fault of the developers. It’s always the fault of the leadership.”

Jonathan was making this point in the context of failed SaaS builds — the kind where founders spend $500K and end up with something unusable. The developers executed on unclear requirements set by leadership that didn’t know how to specify what they wanted.

Robert Fritz — Founder, Robert Fritz Inc.

Robert Fritz is a composer, filmmaker, and organizational consultant who has spent decades studying how structure drives behavior in organizations.

“Most people don’t think structurally, they think situationally. Composers think structurally.”

“You can change the riverbed, you can change the underlying structure. And when you do, you change where it’s likely to go.”

Fritz was distinguishing between founders who respond to organizational problems as isolated incidents (situational) versus those who ask what structural conditions are producing those incidents repeatedly (structural). The river metaphor is core to his consulting framework.

So what: When something breaks repeatedly in your organization, ask what structure is causing it before you ask which person is causing it. The same team in a different structure often produces different results.

Growth & Revenue

Omar — Area President, Focus CFO

Focus CFO provides fractional CFO services to growing companies navigating rapid scaling.

“The worst thing that can happen as a landlord is actually not your property empty. It’s having a renter in your property who’s not going to pay. Because you continue to have to spend money and there’s no benefit.”

Omar was applying this to SaaS: a churning customer who doesn’t pay their final invoice isn’t just a revenue loss — they consume support resources, inflate accrual-basis revenue, and deliver nothing to your bank account. At 8% of revenue — the rate in a real client case he walked through — bad debt is a larger drag on profit than most companies’ entire marketing budgets.

“Because if I’m getting sales but I’m spending more money on the sale, then that’s not actually profitable. I need to focus my efforts on profitable revenue. Because at the end of the day, I need to be able to take something home in my pocket as a small business owner.”

Matt — CRO and Co-founder, Iversoft

Iversoft is a mobile app and software development agency that has closed over 250 enterprise deals without cold outreach.

“When you and the prospect really both understand what you know there’s no doubt about what you’re delivering, what it’s going to, what the outcome is, what the risk is, it’s like very easy.”

Matt was describing what makes enterprise deals stall or die — it’s usually ambiguity about the outcome, not objections to price or fit. When the scope is clean and the risk is named, the close is almost mechanical.

So what: Growing revenue without knowing which revenue is actually profitable is just an expensive way to delay a reckoning. The fractional CFO and agency operator perspectives converge here: clarity of outcome and financial discipline matter more than speed.

Team & Hiring

Josh — Executive Coach, Fortune Management

Josh coaches founders and practice owners on leadership transitions, particularly the move from operator to CEO.

“Both roles, you can’t say, ‘I don’t know.’ and you can’t ask for help because you feel like you’re on this island for whatever reason. And so it becomes a very lonely place and now you’re just in your head ruminating.”

Josh was describing the CEO and senior executive experience — the isolation that comes from being expected to have answers. His coaching practice exists specifically in this gap.

“I can screw in a light bulb — that doesn’t make me an electrician. Put your ego aside. This is an area that you don’t know anything about per se. Get some help.”

Rick McPartlin — CEO, The Revenue Game

The Revenue Game is a sales consulting firm focused on B2B pipeline structure and revenue operations.

“You can’t maximize profit unless your people are optimized. And you can’t optimize people in chaos.”

Rick was describing what happens in sales orgs that grow headcount before fixing process. The inefficiency compounds: more reps doing the wrong things at higher cost.

So what: The advisor perspective on team problems tends to be structural before it’s personal. Chaos in an organization usually has a structural cause — and the people inside it often can’t see it without outside eyes.

Voices in this report

Abdul Ajay Anmol Anthony Arielle Arman Becky Ben Chris Dana Daniel Dave David David Ed Edgar Edward Farokh Feyzi Francis Gorish Heath Izzy Jason Jason Joel John Jonathan Jordan Justin Justin Justin Kendra Kevin Lihong Linda Lloyd Lukas Matthew Mike Molly Moran Patrick Randy Rob Robert Sarah Steve Trey Varun