Juicebox

If I were joining a company today, I wouldn’t optimize for the last round they raised. I’d optimize for what they did after the round. It’s tempting to anchor on logos and headlines. A big Series A. A well-known fund. The signal feels clean and comforting. I’ve done this myself as a candidate. But now that I'm on the other side of the table, I’ve realized those are lagging indicators. What matters more is whether the company can keep the curve going once the money is in the bank. - Did momentum accelerate, or did it flatten? - Did the product actually ship meaningful improvements? - Did the team get sharper, or just bigger? A company that compounds after a round is very different from a company that coasts on the round. And as a candidate, that distinction is crucial. You’re not joining the funding announcement - you’re joining the next 12–24 months of execution 📈

🧃 Introducing Ashby One’s Outbound Sourcing Sponsor: Juicebox Outbound is where momentum starts and few teams understand that better than Juicebox. Our partnership is built around a simple idea. Sourcing should be precise, intentional, and deeply connected to the rest of your hiring motion. The Ashby and Juicebox integration makes that real by turning high quality outbound into structured, trackable workflows inside Ashby. Less swivel chair work. More signal from the very first touch. The teams we see win are the ones who treat sourcing as a craft. Juicebox is helping push that craft forward. Meet their team at Ashby One and see what modern outbound can look like: https://hubs.li/Q04304_v0

The Juicebox team just keeps growing 🌱 Today, we're introducing Justice McPherson, who is joining us as an Account Executive! Justice joins us from Adobe, where he spent the last several years supporting the go-to-market motion for emerging products like Frame.io, Firefly, and Adobe Express. He first started his sales career at Frame.io as one of the first BDR hires post Adobe acquisition and helped grow the business to $100M ARR. From there, Justice joined the team that introduced Adobe's Firefly AI to the market, and later became a founding member of the Adobe Express enterprise sales team. At the time, Adobe Express was a brand new offering. Selling a new product inside a big company is a different muscle. You have the brand, but you’re still figuring out positioning, building pipeline, handling brand-new objections, and shaping the playbook as you go. Justice has done that at multiple stages through his career: - Startup sales at Frame.io - Introducing generative AI to the market - New enterprise motion for Adobe Express We're building something new in the recruiting space too, so that kind of experience matters. Excited to have you here, Justice 🎬 🧃

Introducing another new team member...drum roll 🥁 Welcome Pranav Kumar 🧃! Pranav was one of the highest-energy candidates we’ve ever seen go through our interview process. In his first week, he volunteered to take calls at 7am, 10pm, and everything in between. We never asked him to - he just raised his hand because he wanted the quickest way to ramp up into his role. That tells you a lot. What really stood out about his background was his history in investment banking before making the jump into sales. He also joins us from Verkada and Luminance where he developed strong sales experience and a mindset built for intensity. and has been a top performer ever since. Welcome abroad, Pranav 👋

Talent engineering is no longer a novelty.
 For years, most recruiting functions have been built around effort: Post the role. Source candidates. Send follow-ups. Repeat.
 But a small group of teams are starting to treat hiring differently. They’re not optimizing for effort. One of our customers, Jordan Kindler, COO at Starbridge, is a great example.
 After raising a $42M Series A, they needed to scale quickly across product, engineering, and sales. The default playbook would’ve been to hire a few recruiters, post roles, and increase outbound volume.
 Instead, they engineered a candidate discovery system. Here's how it worked: Step 1: Define the talent market with Clay Before sourcing a single candidate, they used Clay to score and build a list of companies utilize including specific tech stacks, specific cultures, specific growth stages.
 That scored list became the input layer of the sourcing system. Step 2: Build a sourcing infrastructure with Juicebox They uploaded those scored company lists into Juicebox and created multiple Juicebox sourcing agents, each mapped to: ➔ One role
 ➔ One inbox
 ➔ One sequence
 The agents auto-source candidates from those defined markets, and allows them to focus on iterating on sequences the same way a GTM team iterates on messaging. Step 3: Orchestrate responses and funnel movement with Front and Ashby They use Front as a shared inbox so replies from their outbound across multiple mailboxes all roll into a single view per role. Templates in Front include dynamic Ashby booking links. When a candidate replies “interested,” and books a screen, they are automatically tied to the correct job within their ATS. Put together, the system looks like this: → Clay (scored company universe) → Juicebox agents (scaled sourcing)
 → Front (centralized replies)
 → Ashby (structured funnel tracking) And the results weren’t incremental. They went from 20 employees to 60 in a single quarter. Conventional benchmarks would suggest that pace of hiring requires six or seven recruiters. But they did it with roughly one and a half. The title "talent engineer" doesn't exist at most companies yet. But the work does. Companies that recognize and invest in this shift early will build a hiring advantage that compounds over time — because they’ve named, owned, and invested in a capability others are still struggling to define.
 Learn more about Starbridge’s story in the link below 👇

I don’t buy the narrative that AI will replace recruiters. I’ve heard this a lot, and on the surface it may sounds inevitable. If AI can source, screen, schedule, and even interview, why wouldn’t it replace the human in the loop? Because recruiting is a competitive workflow. When multiple companies are going after the same candidate, the difference is in who shows up better? Who builds trust faster? Who creates a process that feels human instead of transactional? In competitive markets like the U.S., recruiting is already an arms race. Everyone will eventually have access to better and more powerful tools. But what actually differentiates your company is how the candidate experiences the process. For example, how well does the role align with their career goals, how they frame the role, how they advocate for the candidate internally, and much more behind the scenes. That’s why I’m skeptical of fully automated recruiting experiences. For roles where competition is real, stripping out the human relationship removes one of the few levers companies still have to win. AI will absolutely reshape recruiting. It should take away the busywork. It should make sourcing smarter and processes tighter. It should give recruiters data leverage they’ve never had before. But replacing recruiters misses the point of adding AI to the function.

You can usually tell if a hire will work out in the first conversation. This might sound overconfident, but in my experience, the very first chat carries the highest signal. In that conversation, you learn what actually motivates someone: ➝ What are they optimizing for? ➝ Why this company? ➝ What do they want to build, learn, or become? It’s the moment with the most net-new information. Everything after that is often confirmation or contradiction of what you already sensed. The second highest-signal moment comes when you see real work output. Every hire we’ve made has done the job during the interview: ➝ SDRs run mock cold calls ➝ AEs run mock discovery calls and demos ➝ Engineers work on a small, role-relevant project The key is realism. The exercise should look as close as possible to what they’ll actually do once hired. Everything else - resume, references, even panel interviews - ranks lower for us. And then there’s the final truth: the first week on the job tells you a lot too. Hiring is about reducing uncertainty. But if you get the first conversation and the work sample right, you’re usually not surprised.

We're welcoming one of our 1st Enterprise Account Executives to Juicebox 🧃 Meet Trevor Smith! Before joining Juicebox, he spent over five years at Handshake where he built and scaled relationships across their Enterprise and Strategic segments. He worked with their largest customers, including Fortune 100 companies, and helped them roll out Handshake across big, complex orgs. These weren't quick-turn sales cycles. They were long-cycle, high-trust, multi-stakeholder partnerships that required real depth and rigor to make sure the product was the right fit across complex teams. What I really respect is that he knows how big companies actually buy software - how to show real use cases, navigate decision loops, and stay close to the customers' goals long after the deal is signed. As Juicebox starts to see more enterprise conversations than ever before, we couldn’t be more excited to have Trevor onboard for this next chapter. Let’s goo 🚀

Welcome to Juicebox, Kai One of our favorite patterns is when great customers turn into teammates. And Kai is a perfect example of that. Before joining Juicebox, Kai was on the talent team at Zip using the product day to day. He also sent us thoughtful, candid feedback over email as a customer, and we were genuinely blown away by how on point and actionable it was. That same clarity has carried into his new role as our first Product Operations hire. Two weeks in, Kai has already been leading product updates for our bi-weekly product meetings and weekly team meetings, helping translate real recruiter feedback into clear product direction. He brings sharp product intuition, a deep understanding of recruiter workflows, and a level of ownership and agency that shows up everywhere he touches. Fun fact - Kai once built and ran a matcha café in San Jose on his own, which is both very cool and very on brand for someone who likes to build real things from scratch Welcome to the team!