Founder Playbook · Sub Club by RevenueCat

11 tactics from Jack McDermott and Tanme Jane

ElevenLabsLeading AI voice lab running 10-12 internal speedboat teams of ~12 people each, shipping at a monthly-launch cadence with 300-400 total employees.

How ElevenLabs Ships So Fast With Small Teams

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Product
inside of 11 Labs if you were to take a look at it we really look like and feel like maybe 10 or 12 individual startups that are all building shipping and iterating all at once... our mobile team is about 12 people right now... each team that we kind of set up as a pod or a speedboat is their own kind of self-contained development design growth product

Speedboat teams: 12 people, full autonomy, monthly ship cadence

ElevenLabs organizes its 300-400 person company into 10-12 fully self-contained speedboat teams, each with its own design, engineering, growth, and product responsibilities. The mobile team ships major features monthly, far faster than the typical once-per-quarter cadence. This structure lets the company operate as many small startups simultaneously without the coordination overhead that kills speed at larger companies.

Shipping
the first thing you're going to do is turn that into a Twitter thread and we're going to think about what is the main headline what's the interesting hook... if you're working on a feature and it doesn't make for a good Twitter thread you better have like a really good reason to be building it

Write the Twitter thread before writing the code

ElevenLabs requires every new feature to be distilled into a Twitter thread before a line of code is written. If you cannot write a compelling hook and three sub-tweets about what you are building, you do not yet understand why it matters and users will not either. This acts as a pre-build virality test that filters out features too incremental to earn attention and forces clarity on the core value proposition.

Launching
earn media is really a compounding effect right like every launch we do earns more eyeballs which means that the next launch earns more eyeballs and it is truly compounding and then it compounds down in our paid media as well... the first place we start is 11 Labs branded search it's the lowest hanging fruit

Earned media compounds: each launch makes the next one bigger

ElevenLabs treats earned media as a compounding asset, not a one-time spike. Each launch that earns press attention increases brand-search volume, which makes paid search more efficient, which makes the next launch convert better. The flywheel: earn attention, capture branded demand, demonstrate ROI on paid, repeat. Most companies optimize each launch in isolation; ElevenLabs optimizes the cumulative earned-media trajectory.

Onboarding
what's the base case like what happens if you just have a sign up form that goes directly into your zero state product... we over rotated a lot in that specific area... if you don't compare it to a base case of just strip it out entirely for 5 days and see what's the opportunity size

Test stripping your onboarding quiz entirely before optimizing it

ElevenLabs spent too many experiment cycles optimizing an onboarding quiz before asking the more fundamental question: what happens if it is removed entirely? When the zero-onboarding baseline was finally tested, the difference in retention and monetization was smaller than expected, suggesting the quiz had been adding friction without commensurate value. Always benchmark new onboarding complexity against a control group with no onboarding at all.

Pricing
by separating out we were able to really basically get licensed to go and try out a variety of different pricing and packaging in a really unique and useful way... 11 reader they don't think in terms of credits and tokens... Jack was able to really align the costs to an hour's sort of experience

Separate apps unlock distinct pricing per ICP without compromise

Running two separate apps let ElevenLabs offer radically different pricing models to different ICPs. The flagship app uses credits and characters that power-creator users understand, while Reader prices by listening hours, which maps to how consumers think about audiobook consumption. A single app with one pricing model would have forced an awkward compromise; separate apps allowed pricing clarity for each audience.

Product
we take a good hard look at public GitHub profiles to see who's engaged in what... we look for those that build side projects on their own that can identify a user pain point and like really build and be obsessed with that... it just becomes a referral flywheel

Screen GitHub profiles before interviews to hire product-minded engineers

ElevenLabs screens engineering candidates' public GitHub profiles before the first interview, looking specifically for developers who independently build and ship side projects. This filters for product-minded engineers who own outcomes rather than just close tickets. These hires then attract similar people through referrals, compounding the culture without diluting the founding character of the team.

Mindset
our CEO encouraged a quote from Brian Armstrong at Coinbase where action gets information... in hindsight it might be a flash in the pan but in forward sight it might actually help guide your future decisions... we're always coming from the lens of like how does this improve the user experience not wouldn't it be cool if we shipped this thing

Action gets information: flash-in-pan features still teach you real things

When features do not retain users long-term, ElevenLabs frames them as data-gathering wins rather than failures. The act of shipping generated market intelligence no pre-build research would have revealed. The condition for this framing to hold is starting from a genuine user problem rather than from 'wouldn't it be cool if.' Features built on real problems teach real things even when they eventually get replaced.

Content
people forget why Spotify wrapped really took off... it took this like passive consumption user behavior and then it turned it into this natural sharable experience... you have to think about what your natural sharable moment in your product is right

Find the natural sharable moment in your product instead of copying Spotify Wrapped

Most Wrapped clones fail because they copy the format but not the mechanism. Spotify Wrapped worked because it surfaced something users already felt identity around (their music taste) and made it beautiful and shareable. A coffee shop's annual spending summary does not carry that same identity weight. The question is not 'how can we do Wrapped?' but 'what do our users already want to brag about?'

Product
it's so powerful to be the first best customer of your API... having those consumer products can be a superpower for the API... it's a better API when internally you can be testing against it and know what the experience is of building against that API

Consumer apps are the best dogfood for your API product

ElevenLabs builds consumer apps in part because they make the API better. Internally using the product surfaces quality issues, latency problems, and UX friction that external API customers experience but rarely report clearly. The consumer product and API product become mutually reinforcing: shipping a better consumer experience reveals model improvements needed, which compounds the technical moat for API customers as well.

Pricing
the biggest win that we had on our side was just we stripped out an entire pricing tier we switched over to be able to communicate with the amount of hours that you spend to be able to play great content... beginning to abstract away from a lot of the fine-tuned details that go into an AI model

Price in listening hours not tokens: abstract AI complexity away from consumers

ElevenLabs Reader's biggest win was collapsing a complex multi-tier pricing structure into a single price denominated in listening hours, completely removing references to tokens, credits, and model tiers. Consumers buying an audiobook experience think in hours of listening, not in AI compute units. The internal cost model is an implementation detail — hide it entirely and price around what users actually care about.

Shipping
speed is becoming the moat right and I think that we kind of live by that... when small teams with driven product-minded engineers and founders fit together with this go fast and ship move then that's where you really start to get harmony and you can deliver bigger results

Speed is the moat: small teams plus founder-mindset engineers compound their edge

ElevenLabs' competitive edge is not just the voice model but the organizational structure that lets them ship improvements faster than any competitor can respond. Small teams, founder-mindset engineers, and a culture where speed is the explicit guiding principle combine into a compounding advantage: the company that learns fastest wins, and learning speed is a direct function of ship cadence. In AI, a quarter of stagnation can cost market leadership.