Summary of Tom Digan & Greg Stewart - Building the World’s Best Fitness App - [Invest Like the Best, EP.454]

Overview of Invest Like the Best — Tom Deegan & Greg Stewart (Episode 454)

This episode traces Ladder’s improbable journey from near-bankruptcy to the top strength‑training app, driven by engineering-led product design, relentless empiricism, and a TikTok-native growth engine. Tom Deegan and CEO Greg Stewart explain the early survival fights (creditors, leadership reset), the product re‑imagining that became Ladder 2.0, how they discovered and validated their customer, the playbook for growth, the role of AI, fundraising lessons, and the company’s long-term vision to be the “system of record” for health and fitness.

Key takeaways

• Product-first + engineering DNA wins: Ladder differentiated by designing software to increase workout completion (their North Star) rather than being a content library.
• Member‑driven, empirical product development: decisions come from surveys, app reviews, and talking directly to thousands of customers, not investor opinion.
• Ruthless prioritization: focus on one thing at a time that moves workout completion; avoid chasing every opportunity.
• Growth = creative ownership + rapid experimentation: they learned TikTok from scratch, owned creative internally, and iterated aggressively.
• AI is an enabler, not a replacement: used to scale support, synthesize user feedback, boost coach productivity, and enable quick launches (e.g., Nutrition).
• Capital strategy matters: early survival required anyone-who-would-invest funding; later they secured structured growth capital (General Catalyst) to underwrite CAC and control fundraising timelines.
• Long-term vision: build the mobile-first system of record for health & fitness—workouts + nutrition + biomarkers + commerce.

The Ladder story — timeline and turning points

• Ladder 1.0 (pre‑2020): a managed marketplace for personal training—operationally complex and low margin; limited scale.
• Leadership reset (late 2019): Tom, as a major shareholder, pushed for a reset and named Greg CEO—transitioned focus to a software-first product for strength enthusiasts.
• Survival mode (2020): debt negotiation with creditors (including deals at ~20¢ on the dollar), micro‑fundraising, daily operational triage while rebuilding product.
• Early validation: hacked a group coaching MVP with a single coach (Lauren) that achieved >90% renewal and real community behavior (members meeting in person).
• TikTok growth (2021 onward): built creative muscle and performance marketing expertise, scaling organic and paid efforts; went from low ARR (~$3–5M) to explosive growth.
• Product expansion: launched Nutrition (free tracking to earn trust) and integrated AI tools (Maeve support bot, Ladder Pulse) to scale human coaching.
• Scale today: north of ~300k paying members; approaching ~$100M ARR; team ≈ 50 (30 core + ~20 coaches).

Product strategy & playbook

• North star metric: workout completions. Every feature is judged by whether it increases completion and retention.
• Design principles:
  • Make it easy to “not think” — deliver prescriptive, progressive plans so members don’t need to choose.
  • Persona-first programming: target specific user segments (e.g., busy New York women) rather than trying to be everything to everyone.
  • Social/accountability + coach relationship — community and perceived human connection are key motivators.
• Evidence-driven feature development:
  • Use deep surveys and review analysis (hundreds/thousands of responses) to form hypotheses.
  • Beta/incubate features with teams and small cohorts, survey weekly, iterate until adoption thresholds met (example: nutrition reached ~85% readiness before broad release).
• Nutrition strategy:
  • Offer table‑stakes macro tracking for free to capture inputs, build trust, and unlock downstream paid experiences.
  • Nutrition provides the input side of the fitness math (exercise = output; diet = input), enabling a broader product ecosystem.

Growth engine — how they cracked TikTok

• Approach:
  • Treated TikTok as a media product (not Instagram rules). Focused on content that the algorithm can place in front of the right persona.
  • Built organic proof points first (accounts grown from 0 → 250k followers in ~45 days) before scaling paid experiments.
  • Owned creative internally (full-time creators, in-house creative partnership) rather than outsourcing to agencies.
  • Rapid iteration: dissect every successful video (hook, setting, copy, movement) and repeat mechanics that work.
• Performance marketing learnings:
  • Reject Facebook heuristics — learn platform-specific mechanics and iterate quickly (Tom frequently changed budgets many times per day).
  • Combine organic learnings with paid spend to scale efficiently.
• Results:
  • TikTok became the primary acquisition lever that unlocked the later ARR inflection. Short‑form strategy expanded beyond TikTok to other channels as awareness grows.

Team, operations & AI adoption

• Team structure and culture:
  • Engineering-first mindset; product and growth are held as equal, essential skills.
  • Small, highly prioritized teams; no managers in an earlier ~30-person team—focus on autonomy and alignment.
• AI usage examples:
  • Research & synthesis: use LLMs to analyze thousands of responses, generate creative hooks, and accelerate insight extraction.
  • Customer support: built “Maeve” — a purpose-built AI support tool that handles ~90% of incoming tickets and improves speed/quality.
  • Coach enablement: Ladder Pulse automatically reads chats, summarizes top member issues, and recommends coach actions, reducing cognitive overload.
  • Product enablement: AI substantially reduced the engineering overhead needed to launch features like Nutrition.
• Philosophy: AI augments human motivation/relationship rather than replaces it.

Fundraising & capital strategy

• Early phase: survival fundraising—friends, family, and internal checks from Tom; conviction and “skin in the game” mattered more than decks.
• Growth financing: partnered with General Catalyst’s Customer Value Fund to underwrite CAC, allowing them to scale marketing while controlling dilution and timing.
• Current stance: with recurring cash flow and structured capital, Ladder can be selective about new investors and focus on long-term partnerships (board/operating value over pure cash).

Opportunities, risks, and future vision

• Vision: become the system of record for health & fitness — mobile-first, engaged daily, combining workouts, nutrition, biomarkers, commerce, and services.
• Opportunity areas:
  • commerce/marketplace for supplements/apparel,
  • biomarker integration (DEXA, labs),
  • broader user expansion/freemium on‑ramp for outer rings of fitness,
  • partnerships with GLP‑1 providers (seen as potential tailwind due to need for strength training).
• Risks:
  • Product dilution if pursuing too many revenue streams at once.
  • Android expansion and other platform moves require disciplined timing—splitting focus prematurely could be harmful.
  • Competition from free content (YouTube) and new entrants using commoditized tech—brand and trust are defensible assets.
• AI and GLP‑1 stance:
  • AI = accelerant for personalization and scaling; they’ll continue to build proprietary AI tools aligned with Ladder’s data and workflows.
  • GLP‑1s likely a net tailwind (need for strength training to avoid muscle loss), not a direct threat.

Practical lessons & recommendations for founders

• obsess over one measurable North Star (for Ladder: workout completion) and build everything to move it.
• talk to real users relentlessly—use surveys, app-store reviews, and 1:1 calls to form product decisions.
• prioritize ruthlessly—ship the few things that materially increase the North Star; avoid shiny distractions.
• own creative when building social/video channels — don’t outsource the learning loop.
• use AI to automate repetitive internal tasks and to accelerate research, but preserve human relationships where they matter.
• fundraising: early—conviction & skin in the game; later—structured capital that underwrites growth economics gives optionality.

Notable quotes

• “We’re solving for you to actually complete workouts with Ladder.” — the product North Star in a sentence.
• “Don’t listen to investors on product feedback.” — the founders’ mantra: rely on user signals, not prescriptive investor wishes.
• “We have to be black‑belt at both product and growth.” — both must be excellent to build durable consumer companies.
• “Nutrition gives us the whole math equation of inputs and outputs.” — why nutrition was the natural next step.
• “AI let us have our cake and eat it too — deliver personalization at scale without exploding headcount.” — practical AI framing.

Actionable next steps (for listeners / founders)

• If you’re building consumer product: define a clear North Star and interview users weekly until the signal is obvious.
• If leaning into short-form video: build an internal creative team, iterate on hooks, and own the creative feedback loop before scaling paid.
• If looking to use AI: target high‑leverage internal workflows first (support triage, coach assistance, research synthesis) to reduce headcount drag.
• For fundraising: think about capital that underwrites CAC/payback economics, not just raw checks—structured partners can buy time and leverage.

If you want the “dirty” survival stories, fundraise anecdotes, and the detailed TikTok/creative playbook, listen to the full episode — it’s a practical masterclass in surviving, validating, and scaling a consumer product under extreme constraints.