Carles Reina reveals how ElevenLabs scaled to $3.3 billion

Transitioning from the rigid, hierarchical world of banking to the chaotic frontier of early-stage startups requires more than just a change in scenery; it demands a fundamental shift in mindset.

made this pivot sixteen years ago, leaving Barcelona for London and eventually joining

Uber

when its international team consisted of just twenty people. This move wasn't about seeking safety; it was about the hunger for impact. In a massive corporate structure, you are a number. In a twenty-person startup, you are the engine.

This early exposure to

's skyrocketing growth triggered a realization: the early days of building from scratch offer a level of agency that vanishes once politics and bureaucracy take hold. For Reina, the goal has always been to identify the "hidden trend" before it becomes a headline. This philosophy guided him through

Tractable

, one of the UK’s first AI unicorns, and eventually led him to

ElevenLabs

. The common thread in these successes is a refusal to settle for the status quo and an obsession with solving problems that others find too unsexy or too difficult to tackle.

Abandoning the playbook for constant experimentation

Many go-to-market (GTM) leaders fall into the trap of the static playbook. They believe that because a strategy worked at a previous SaaS company, it will work for a foundational AI model. Reina argues that any fixed playbook is fundamentally flawed by nature. The speed of execution in the current market has collapsed the enterprise sales cycle from eighteen months to thirty days. In this environment, a rigid strategy is a death sentence.

Instead of a playbook, Reina advocates for a culture of aggressive experimentation. At

, this means over-indexing on testing Ideal Customer Profiles (ICPs), pricing models, and pitches across different regions. What works in the UK rarely translates directly to Japan or the US without localization. A true GTM leader must be an entrepreneur at heart—someone willing to act as the company's first Sales Development Representative (SDR) to build the culture from the ground up. This hands-on approach ensures that leadership isn't disconnected from the reality of the customer's pain points. If you aren't experimenting, you are falling behind.

The infrastructure of voice and the new AI agent economy

has positioned itself as more than just a voice-cloning tool; it is an infrastructure player similar to

Amazon Web Services

or

Microsoft Azure

in the early days of cloud computing. By providing foundational models for high-quality audio, they have spawned an entire ecosystem of verticalized applications. Reina sees the future of voice AI not just in entertainment, but in deep, utility-driven sectors like healthcare and automated support.

The horizontal play—offering foundational models—is only one half of the strategy. The next frontier is verticalization.

is moving into AI agent platforms capable of handling inbound and outbound calls, acting as AI receptionists, and voicing articles for major publications like

TIME

. This shift targets the massive portion of the market that lacks the engineering skills to build their own tools. By creating the workflows and applications themselves, they penetrate deeper into the enterprise market, moving voice from a gimmick to a mission-critical business asset.

The operator-investor edge and the $5,000 conviction

Success as an angel investor isn't about the size of the check; it's about the value of the advice. Reina has completed over 70 angel investments, including an early bet on

. His approach centers on being an "employee without being an employee." This means helping founders with contract negotiations, pricing strategy, and opening doors through an established network.

Access to the best deals—the "top tier" signal—comes from building a reputation for being helpful before asking for equity. For a startup operator, angel investing is a long-term game of community building. Reina recalls that his early $3,000 and $5,000 checks were significant personal risks, but they were bets on the people and the ecosystem. Even if a specific company fails, the talent from that company often goes on to build the next unicorn. By backing the founders early, an investor earns a seat at the table for the entire lifecycle of the tech ecosystem's growth.

Robotics and the GPT moment for hardware

The most significant emerging trend is the convergence of

with industrial robotics. Reina believes robotics is currently experiencing its "GPT moment." For years, hardware was dismissed by many VCs as too slow or too capital-intensive. However, companies like

VIMA

in Manchester and

Techer

in Barcelona are proving that merging LLMs with robotics allows machines to perform an unlimited number of non-sexy, autonomous tasks.

This shift is particularly relevant in Europe, where labor shortages in manufacturing, elder care, and defense technology are reaching a breaking point. The ability of robots to operate autonomously, rather than being driven by a human operator, changes the ROI calculation entirely. This is "deep tech" in its truest form—hard to build, but essential for the future economy. Investors who ignored hardware in the past are now being forced to change their tune as autonomous systems become the backbone of the next industrial revolution.

Managing liquidity and the art of the 20% trim

One of the most complex decisions an angel investor faces is when to exit. The tech landscape is littered with "paper millionaires" who held on too long, as seen in the case of

, where valuations soared and then cratered. Reina suggests a disciplined trimming strategy: selling 10% to 20% of a position during a Series B or C round once the company reaches unicorn status.

This strategy allows an investor to lock in significant gains—often returning the entire original investment many times over—while still maintaining exposure to the massive upside of a potential decacorn. If you invested in the

pre-seed at a $9 million valuation and the company is now worth $3.3 billion, the math for a partial exit is undeniable. It isn't about a lack of faith in the founder; it's about responsible portfolio management. In a market where preference shares can wipe out common shareholders in a downside scenario, taking some chips off the table is the only way to ensure that a "win" on paper becomes a win in reality.