This week, we’re digging into how this 190-person company kept headcount steady while increasing velocity and cutting costs.

Scale Without Size: How Linktree is Using AI to Accelerate and Do More With Less

Going into annual planning for 2025, Linktree’s executive team faced a choice. The company had evolved from a simple link-in-bio tool into a platform supporting 70 million creators and businesses, building a two-sided marketplace, enabling affiliate commerce, and launching influencer campaign tools. Traditional wisdom pointed to significant headcount growth to keep racing ahead with their ambitious roadmap.

But rather than scaling headcount, they made a different bet, opting to stay lean at the sub-200 people mark and push AI adoption, hard.

Fast forward to this summer and there are a number of early indicators that this strategy is paying off. Headcount is flat, but launch velocity has picked up, costs are down, and tooling adoption is up (so much so that Devin now sits at the top of their internal PR leaderboard).

As you’d expect, there wasn’t any one silver bullet here. “AI is advancing much faster than us humans are willing to change our habits,” says Linktree CTO Farnaz Azmoodeh. “The gap won't close itself — you have to relentlessly push for it. Helping people get over that hump is your number one job as an eng leader right now.”

In this week’s Applied Intelligence essay, Azmoodeh and former CPO Jiaona Zhang (who's since joined Laurel) share exactly how they transformed their organization, including:

• The specific tasks where Devin excels, and the failure modes to watch out for.
• Surprising takeaways, like how using codegen tools effectively is a lot like managing, so senior engineers are actually well positioned to be power users.
• Why we need to go deeper than just saying “prototypes are the new PRD” and the prompt consolidation technique that bridges the gap between vibe-coding and production.
• How execs can personally push AI adoption (Azmoodeh built an automated dashboard and personally DM’d engineers who weren’t using the new tooling) and why they should focus on their own practice:preach ratio.

Thanks, as always, for reading and sharing!

- The Review Editors

This week, Color co-founder and CEO Othman Laraki shares the strategies that helped him build a billion-dollar business in an industry he had zero professional experience in.

To Learn a New Market, Start by Building Your Product — Tactics From a Twitter PM Turned Healthcare Founder

Having a beginner’s mindset can help you build a more resilient product — by being open to getting a lot wrong.

When Othman Laraki teamed up with Elad Gil to build a cheaper genetic test for cancer screening, the duo approached the problem from a technical perspective. They were former Google PMs who’d just sold the startup they co-founded to Twitter. Gil had gotten his genome fully sequenced, which sparked curiosity about the astronomical cost of genetic testing. Laraki had a family history of cancer and felt compelled by the idea to make screening more accessible. They figured it must be an engineering problem, so they started with what they knew: building a product.

But as they waded deeper into the foreign waters of the healthcare industry, they had to constantly rethink their assumptions.

“When you enter a new space, it's important to be willing to question the status quo, but also have a lot of humility,” says Laraki. “It took many years and pivots to hone in on what worked. At every step, some people might feel that change is a failure, but in my experience, that’s often the wrong reflex.”

Untangling the web of buyers, incumbents and unit economics in healthcare led them to pivot from a direct-to-consumer testing service to a virtual cancer clinic that sells directly to employers and health plans. Today, Color is a billion-dollar business that has partnerships with the American Cancer Society and the National Institutes of Health.

In this exclusive interview, Laraki shares what the Color team learned from a years-long iterative building process in a market the founders previously knew nothing about. Here are a few of his immersion tactics:

• Follow the money and decision-making. Laraki thought like an anthropologist and set up exploratory conversations with key healthcare industry insiders to map out the market. For healthcare, that meant plotting how a transaction moves through suppliers, manufacturers, distributors and buyers. “Who influences, who decides, who sets the price, who sets the terms, how the transaction actually occurs and how you get paid — this is what you have to untangle,” he says.
• Find “unsexy” experts and identify creative ways to work with them. Since Color’s early days, Laraki has sought out respected cancer researchers as advisors. Getting the product in these experts’ hands helped the team validate its scientific rigor. “Find advisors who are doing the work — not the ones who spend most of their time talking about it,” he says.
• Study the incumbents to find your wedge. It was ultimately learning about how insurance incumbents control pricing dynamics that led Color to pivot away from being a testing vendor. “With consumer products, if a more competitive product shows up, that product can win in the market and gain traction. But in a market like healthcare, it’s the polar opposite. The mechanism of accessing the market is held by insurance companies extracting margins out of services,” says Laraki. “If you show up with a better mousetrap, you don’t have an open liquid market to compete in. You still have to break in and figure out how to force your way.”

Thanks, as always, for reading and sharing!

-The Review Editors

This week, B2B marketing expert Emily Kramer shares why early-stage founders need to ditch the VC-speak — and how to write effective copy for customers.

Don’t Ship Your Pitch Deck to Your Website. Here’s How to Translate Your Story for Customers

Emily Kramer has noticed that founders have a bad habit. As a marketing advisor to dozens of early-stage startups, she’s reviewed too many websites that sound an awful lot like the founders’ pitch deck.

It’s understandable to want to squeeze as much marketing juice out of your pitch deck as possible. It’s one of the first communication assets you craft as a founder. You probably spent north of one hundred hours perfecting it.

But customers don’t care how you got funding. “A great pitch deck makes for an ineffective website. It also makes terrible outbound copy,” says Kramer. “You can’t copy-paste that deck to your homepage because your prospects likely aren’t VCs. And even if they are, VCs look for very different things in software than they do investments.”

On The Review, Kramer unpacks her framework for creating effective early marketing messaging. She then walks through how to adapt your pitch deck into copy for your website — slide by slide. Good news, founders: You can do this yourself, without a marketing hire.

Here’s a preview:

• The problem slide → Your homepage hero: In a pitch deck, you use the problem slide to to convince investors why what you’re building matters and show what you’re building in the medium term. But customers only care about what your product can help them do today.
• Vision & why now slide → “About” page: This slide is designed to inspire belief in a big future and show why this moment is the right time to build. In your marketing messaging, this story is an opportunity to tie your product to a broader movement or emerging shift customers want to be part of. But this messaging shouldn’t be front and center on your homepage.
• Competition slide → Product page: Acknowledging your competitors in a pitch deck shows your awareness of the landscape and how you’re different. On your website, you can highlight your differentiators, but only mention competitors where necessary. Kramer recommends using comparison pages, customer stories on switching products and sales-specific content (like battle cards) to get precise on how you stack up against a single competitor.

“A pitch deck is a great forcing function to think about your story and start compiling assets that will be useful in marketing. But you need to take a few extra steps to make it ready for prospects and customers,” says Kramer.

Thanks, as always, for reading and sharing!

-The Review Editors

This week, we’re back with another installment in our Paths to Product-Market Fit series with Owner co-founder and CEO Adam Guild.

The Story Behind Owner’s Pivots to a Billion-Dollar Business

Back in 2017, Adam Guild set out to find customers for his new growth platform for restaurant owners. Except this wasn’t your typical founder-led sales grind.

Guild was a 17-year-old high school dropout with no relevant credentials, aside from a wildly successful Minecraft server that he built when he was 12 and pulled in six figures a year. He was literally knocking on doors of restaurants all over Los Angeles, but his self-described baby face made it hard to be taken seriously.

Guild’s mission was personal. He had the idea to build a digital platform to help small businesses grow after helping his mom find more customers for her newly opened dog grooming salon. He taught himself local SEO and put it to work on his mom’s website. Suddenly, her business went from struggling to thriving. He wanted to do the same for mom-and-pop shops in his native LA.

Out of hundreds of knocked doors and thousands of cold emails, he managed to find a few intrigued restaurant owners to try the product. He bootstrapped the company to six figures in ARR with a steady roster of customers, including P.F. Chang’s.

Then came the pandemic in March 2020, and Owner’s PMF evaporated practically overnight. Guild decided to pivot to online ordering and built the new product in two months.

These are just a few of the inflection points in Owner’s winding path to product-market fit. Flash forward to today, and Owner has nabbed a $1B valuation and over 10,000 customers.

In this exclusive interview, Guild shares some of the lessons he’s picked up on his unconventional journey, including:

• The silver lining of brute-force sales: Guild found cold outbound demoralizing after a while, but looking back, he’s glad he did it. “A sales-led motion forces you to talk to customers extensively at every step of their journey, and it creates a higher perceived value of whatever you're selling,” he says.
• The value of founder-led content: Guild wanted to complement his outbound efforts by drumming up inbound demand. To do it, he began writing contributed articles for top restaurant publications, which built a distribution engine and helped him learn the industry's nuances. “The work I was doing to research these articles improved my ability to communicate with the restaurant community, and gave me a much deeper understanding of the broader landscape,” he says.
• Why he went multi-product sooner than usual: Guild resisted the classic advice to wait until your core solution is working before going multi-product. Within a year after launching the V2 product, Owner rolled out a bundle of additional products. "This was one of the best decisions we ever made because it improved everything. It improved the customer's results. It improved our retention rates. It created a higher perceived value and willingness to pay,” he says.

Guild’s remarkable story is well worth the read for any founders with nontraditional backgrounds.

Thanks, as always, for reading and sharing!

-The Review Editors

This week, we’re back with another installment in our Paths to Product-Market Fit series, this time with Linear CEO and co-founder Karri Saarinen.

Linear’s Path to Product-Market Fit — Quality and Craft > Speed and Scale

The metrics founders use to measure product-market fit — sales conversion rate, burn multiple, ARR — didn't matter to Karri Saarinen.

He's prioritized a non-numerical KPI since day one of building Linear: quality. Finnish by birth and a product designer by trade, he’s long balked at Silicon Valley’s obsession with scale and speed, which, he thinks, often comes at the expense of craft.

While a design lead at Coinbase and Airbnb, he grew frustrated with the product and engineering team’s project management software. “When I first started using it, I thought, ‘Why is it so messy and complicated?’” he says.

His Finnish friends Jori Lallo and Tuomas Artman, engineers at Coinbase and Uber, used the same tool at their jobs and shared Saarinen’s frustration. Over beers one night, the trio decided to team up to build a better one, figuring there must be a market of IC product builders just like them craving a faster and more elegant tool.

But before rushing to start a company, they let the idea simmer for a while, even running some lightweight user research with coworkers while still at their day jobs.

“Sometimes it's good to not build immediately. We didn’t want to commit right away and move really fast. We wanted to take some time to talk to people and form our thinking around this idea,” says Saarinen.

So when they set out to build the prototype over a year later, Saarinen says this incubation period made the actual work of designing the product very intuitive. ”Because we did so much pre-work and pre-thinking, a lot of the architecture was basically built into the product by the time we started,” he says.

Fast forward to today, and Linear now has plenty of numbers to show for it. Earlier this summer, Linear announced an $82M Series C, bringing its valuation to $1.25B, with a 15,000+ customer roster that includes the likes of OpenAI, Ramp and Vercel.

On The Review, Saarinen walks us through Linear’s methodical six-year build, detailing how the founding team…

• Built a highly opinionated prototype that met the co-founders’ high standards
• Launched in private beta and handpicked early users to join
• Stayed focused on the day-one ICP of IC product builders even with subsequent product launches
• Designed the sales process to be an extension of the product

Saarinen credits Linear’s success with this craft-first ethos, which hasn’t wavered even at its size today. “Quality is our first principle. Every other metric and decision flows from that,” he says.

Thanks, as always, for reading and sharing!

-The Review Editors

This week, we’re detailing exactly how Carta built an agent to solve one of its most pressing accounting problems.

The Dynamic Context Problem: How Carta’s Internal AI Agents Save Thousands of Hours of Back-and-Forth Work

Jayant Tikmani, Director of Machine Learning at Carta, finds the best problems for AI to solve based on this principle: deliver a differentiated customer experience and enhance service quality rather than reduce cost.

He found a worthy problem in the company’s fund administration business.

This service-based org of 600 people helps 2,500 customers handle complex accounting, reporting and compliance work. There’s a wide set of tasks this team can do for clients, so when a problem arises, it takes a lot of time to figure out what’s happening, what to do and how to fix it. Scaling is bottlenecked by context-gathering, which CPO Vrushali Paunikar says is an industrial engineering challenge.

So Tikmani worked with domain experts in the fund admin business and engineers to pinpoint workflows where agents could understand a task, build relevant context and suggest or complete next steps.

The result was the creation of an agent to handle cash reconciliation — turning an 11-minute task into one that could be completed in seconds. There are 20,000-25,000 of these tasks per month, which saved Carta’s internal team over 3,500 hours per month. Here’s how he and the team did it:

• Use a focused, low-investment PoC to assess risk, feasibility and answer key questions. Could the agent retrieve the right context from an internal tool via an API or database query? How should they structure and present the agent-generated diagnosis and recommendations to internal teams? Did users actually find the output useful and accurate enough to act on?
• Give the agent the right context for specific tasks and tools. Domain experts diagrammed the full workflow in Lucidchart, which acted as the source code for the agent’s system prompt. With that input, they created a set of gold-standard prompting techniques relying heavily on in-context learning: provide examples, the expected output structure and task framing.
• Lightweight design meant to evolve through iteration. Prototype and get a product in the hands of users to move as quickly as possible. To do this, they decoupled product performance (which is based on model behavior) from UX and workflow integration. They could evolve the agent’s reasoning and output quality without needing to constantly rebuild the product surface or its backend systems.
• Evaluating on one metric: helpfulness to users. Internal experts drove the agent’s feedback process. They provided a helpfulness rating via the product’s interface, compared normal task resolution speed to that of the agent and tracked reduction in back-and-forth between teams by monitoring escalations and handoffs.

This essay is a detailed look into how Carta identified a problem, set the right parameters for solving it and actually built the tool to do it. It’s an excellent example of AI in production driving meaningful business impact.

Thanks, as always, for reading and sharing,

-The Review Editors

Today, we’re excited to launch our new publication focused on how companies are using AI in production to drive real results. 

From Memo to Movement: Shopify’s Cultural Adoption of AI

We all know AI will transform every aspect of how we live and work. But the gap between that future state and our current reality still feels like quite the chasm to cross. 

As science fiction writer William Gibson once said, “The future is already here — it’s just not evenly distributed.” 

Most companies are navigating the “memos and demos” phase. Ambitious plans and mandates to start using AI are boldly declared in an ever-growing collection of CEO memos (initiated by Shopify co-founder and CEO, Tobi Lütke). Board decks trumpet “AI-first” roadmaps. Flashy features are center stage in the demoware that’s rocketing around social media. 

Yet scalable implementations and real results remain murky. 

That’s why today, we’re launching a brand new publication to close this gap: Applied Intelligence. 

For more than 12 years now, The First Round Review has published tactical playbooks from builders. Our obsession has always been with ground truth over grand theory, on mechanics of company building over market maps. Applied Intelligence extends that mission — to share how builders are using AI at their companies and the impact they’re seeing. 

Our inaugural essay is with Shopify’s VP & Head of Engineering, Farhan Thawar. Think of it as the sequel to Tobi Lütke’s famous memo, where we’ll explore the non-obvious insights, tactics and workflows Shopify used to bring the ambitious memo to life: 

• The surprising tools built by non-technical teammates when Shopify gave everyone access to expensive models
• The LLM proxy, which houses all internal agents and MCPs — allowing employees to build the workflows they need 
• The mentality behind hiring 1,000 interns to foster a “beginner’s mindset” and help teams solve problems faster 
• How they’re “context engineering humans” by identifying the high-impact workflows to inject AI 

You can read the essay here. And if you want to learn more about Applied Intelligence, go here. 

Thanks, as always, for reading and sharing!

This week, we’re looking at how founders can build out the initial version of their customer success orgs, from identifying the right people to hire, to the best early metrics to track.

The Founder’s Guide to Building a V1 of Customer Success

At some point, founders can no longer moonlight as customer success leaders.

The moment you realize it’s time to turn off support notifications can come in different forms — maybe something breaks and you’re drowning in tickets, or maybe too many high-profile customer requests pull focus away from other responsibilities.

Knowing when it’s time to build the CS function is one thing. Knowing how to build it is another.

Stephanie Berner, Atlassian’s SVP of Customer Success, is here to give you a blueprint. Prior to Atlassian, she led customer success for LinkedIn’s Sales Solutions arm, was the Senior Director of Customer Success Management at Box and gained early startup experience at Medallia, all the while learning the ins and outs of delivering strong customer experiences.

“Customer success is all about getting your product into your customer's hands as fast as possible,” she says. “If founders and product builders are spending disproportionate amounts of their time solving customer experience problems instead of driving the mission forward, it’s time to formalize your customer success operations.”

In this exclusive interview, Berner breaks down the crucial components of building an early customer success org, with specific zero-to-one tactics for founders standing up CS from scratch. Here’s what you’ll learn:

• Whether your first hire should be someone technical or an industry specialist
• Interview questions to ask that will evaluate drive, self-awareness and customer empathy (which are the most important traits of first hires)
• Why your CS leader should report to the CEO instead of the CRO or CPO
• Target ratios for the number of CSMs on SMB, mid-market and enterprise accounts
• Why customer health and renewal rate are the most important early metrics to track (and why NPS and CSAT can wait)

This is an invaluable, tactical approach for founders who are just starting to build their customer success functions.

Thanks, as always, for reading and sharing!

-The Review Editors

Recommended resources:

-How to calibrate your gut for hiring

-How to build a “board of brains” with AI