The AI-Native Company That's Turning Growth Into a Science
Unify x The Signal
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Hey y'all!
There is a new crop of AI-native founders building GTM tech. Austin, Connor, and the team at Unify are squarely in that camp — shipping fast, building in person (SF and NYC), leveraging the frontier AI models, thinking deeply about not just product but also distribution, and they have taste.
I have personally used Unify on a couple of consulting engagements, so I’ve seen the power of what they’re building, first-hand. I have interacted with their team a lot, they’re legit (Rhea, and others are badass).
They’re building a platform for Outbound/Growth/RevOps teams to scale pipeline through warm outbound plays, signal-based selling and leverage AI agents. They’re not building infrastructure to run the 2019 playbook — they’re building for the future playbook.
Oh, and they announced their Series B just this morning!
I caught up with Austin over a coffee in SF recently. We jammed on all sorts of things. One thing that stuck out was their mission. He told me they’re building Unify in a way to enable the best products to win. Philosophically, I love this thinking. Reminds me of the old adage:
“First-time founders care about product, second-time founders care about distribution.”
We're going into a world where distribution has become the ultimate moat. You can have the most elegant solution, the cleanest code, the happiest customers, but you can still lose to a company that's simply better at getting their product in front of the right people at the right time. Commoditization of software (eg: vibe coding) will continue to make building products easier, which means more software and competition will exist. Therefore, growth will become increasingly challenging in the future.
Austin and his team aren't just building another GTM tool. They're helping companies turn growth into a science so that the best products can win the distribution battle.
That’s why I’m excited to share today’s sponsored deep dive on Unify.
Here's what we cover in today's post:
The Distribution Problem: Why "build it and they will come" is dead
System of Action: The fundamental shift beyond traditional CRMs
The Outbound Quarterback: A new role emerging in the most successful teams
AI That Improves With Time: How Unify benefits from model improvements
Execution Over Signals: Why acting on data beats collecting it
Let's get into it.
The Distribution Problem
The old playbook was simple: build a great product, and customers will find you. Word of mouth will spread. Growth will happen organically. Even PLG was a silver bullet for viral or multi-player products (like Zoom, Figma, Notion, etc.).
That world is gone.
Today, having the best product isn’t enough. Especially as AI commoditizes code. What separates winners from losers is the ability to systematically and scientifically reach the right people with the right message at the right time. It's about turning growth from an intuition-based art into a repeatable science.
This isn't just something that looks good on a fundraising pitch deck. It’s real. Unify is becoming a true thought partner for some of the best companies in the world (like Perplexity, Cursor, Decagon, etc.) on how to completely rethink outbound from a data and AI-first perspective.
The companies that figure this out first will have an unfair advantage. I’m personally seeing this in the market. And I believe this gap will only widen over time.
System of Action vs System of Record
Most sales and marketing software falls into the "system of record" category—tools designed to store and organize data. Think Salesforce, HubSpot, and other traditional CRMs.
But storing data isn't enough anymore. What matters is being able to take action on that data.
Unify is building a "system of action"—software that doesn't just house your GTM data but actively helps you do something with it. It's designed around a simple philosophy: the real value isn't in having perfect data; it's in turning that data into revenue-generating activities. This is something I’ve been talking about for many years now: action > insights.
This distinction matters more than it might seem. Traditional GTM tools force you to jump between platforms, manually connecting dots, and relying on human interpretation to turn insights into action. A system of action streamlines that entire process, making the leap from "here's what we know" to "here's what we should do" as seamless as possible.
But here’s the nuance: Unify is not building a spammy AI SDR. They aren’t trying to eliminate the human element entirely. Instead, it pulls people into workflows where personal touch actually matters. Because, while AI can handle a lot of the heavy lifting, there are still moments where human judgment and relationship-building make all the difference.
The Outbound Quarterback
Austin led the Growth Product team at Ramp (notoriously one of the most forward thinking teams). So, he has thought deeply about how the most successful teams are structured since 2021. After his experience, and then working with dozens of other world-class companies, he's noticed that the teams that win consistently have a specific type of person at the center of their GTM motion.
He calls this person the "outbound quarterback."
This isn't necessarily a formal role—it might be a RevOps person, a systems person, a growth team leader, or even a technical SDR manager. But regardless of title, they all share one key trait: they think in terms of “plays.”
The outbound quarterback's job is to orchestrate scaled pipeline generation. They're constantly asking questions like: "What plays should we be running? Which signals should trigger which actions? How do we scale what's working and kill what's not?"
The best outbound quarterbacks Austin has worked with don't just run plays—they evolve them. They'll work with SDR teams to incorporate phone calls and personal outreach when it matters. They'll test new approaches, measure results, and continuously refine their playbook. I think of this as collapsing a GTM Engineer and a GTM Architect into a single role (probably looks most closely like a Growth persona).
What's interesting is that these teams often pull Unify into workflows that go beyond just email sequencing. They want to orchestrate calls, sync tasks to dialing tools (like Nooks and Orum), add LinkedIn touches (which Unify recently launched, and I’m very bullish on), and create sophisticated multi-touch campaigns that are relevant at scale.
It's a new kind of GTM role, and Austin's betting that as the market gets more competitive, every successful company will need someone thinking this way.
AI That Improves With Time
Unify is “AI-native.” Meaning, their product gets better without them writing any new code.
How? They're building AI-native from the ground up. As foundation models improve, Unify's customers automatically get a better experience. Better research. Better copywriting. Better decision-making.
Austin's team made a conscious decision not to spend tons of time fine-tuning models or building elaborate prompt engineering systems. Instead, they're betting that the underlying models will keep getting dramatically better—and they want to ride that wave.
I think this is the right approach. And it relates to a quote I recently heard from Sam Altman:
You can either build a business that bets against the next model being really good, or build a business that bets on that happening — and then benefits when it does.
Their (initial) AI use cases shows up in two key areas today:
Research agents that go out and do account research. The main skill these agents are still developing is tool calling—knowing when to use which tool and building good intuition around research workflows. The models are okay at this today, but Austin expects them to get much better quickly.
Copywriting and messaging. While AI-generated copy isn't perfect yet and requires some last-mile polish, it's improving rapidly. And when you're running sequences at scale, even modest improvements in AI-generated messaging can have massive downstream effects.
It's wild to think your software can get significantly better every few months without any additional (internal) dev work. Said another way: you can build software with the best engineers in the world (eg: at OpenAI) working “for” you. That's never existed before in the history of business software. Founders should act accordingly. Austin, Connor, and the Unify team are.
Execution Over Data/Signals
It’s confusing to me that so many companies today are not building the “engagement” component of outbound (eg: a sequencing tool). I used to think it was to “play nicely” with the big players in the space. Then I thought it was because it’s hard to build? (But, I don’t think that’s the case). So, then I can only imagine it’s a lack of ambition. Unify is ambitious (or naive enough… and ignorance is bliss baby! I mean that as a compliment) to ship sequencing. And most recently, they launched a space for reps to work out of… watch out OutLoft 👀.
Fun fact: Austin told me that in late 2023, they told their investors that they were going to build sequences and were advised to reconsider that decision, as they might be going too wide too early. Now, this is their biggest differentiator.
Unify's philosophy differentiates it from most companies in the space. While most GTM tools are focused on collecting more signals—more website visitors, more intent data, more social listening—Unify is obsessed with one thing: making it 100x easier to act on the signals you already have.
Austin summed it up to me perfectly:
9 out of 10 teams, the thing they actually struggle with is getting value out of the data, not getting the data itself.
Most companies are drowning in signals. They know when someone visits their website, downloads content, mentions them on social media, or fits their ICP. The problem isn't detection—it's execution. They have something called “infinity signal” which means signals are easy to capture, and APIs aren’t as relevant.
What happens after someone hits your pricing page? What's the right follow-up when a prospect goes dark for two weeks? How do you systematically work through a list of 10,000 potential accounts without missing the highest-value opportunities?
These are execution problems, not data problems.
Unify believes in the power of using signals in ‘warm’ outbound—and continues to invest in building their own (as timing is everything)—but they are betting that the biggest differentiation will lie in acting on signals efficiently.
That means seamless CRM integration. No deliverability issues. Automated follow-up sequences that feel personal. The ability to scale one-to-one outreach to hundreds or thousands of prospects without losing quality.
Owning the entire workflow end-to-end is a bold bet. You love to see it.
Looking Forward
Again, to reiterate, we're moving into an era where distribution advantages compound faster than product advantages.
The companies that figure out how to systematically identify, reach, and convert their ideal customers will build moats that are incredibly hard to replicate. Not because their product is necessarily better, but because their go-to-market engine is more efficient, more scalable, and more precise.
Unify is building the infrastructure for that future. A world where your best growth strategies don't walk out the door when top performers leave. Where insights from your most successful deals automatically inform how you approach similar prospects. Where the entire organization learns and improves at the speed of software, not the speed of human knowledge transfer.
Unify’s vision is simple but powerful: help the best products win by giving them the best distribution. In a world where that's increasingly important, it’s an epic problem to be solving.
If you—or someone on your team—is looking to run more outbound plays this year, and leverage AI to do it, you should chat with the team at Unify. I’m bullish.
Thank you for continued attention and trust — I do not take it for granted.
See you next time,
Brendan 🫡