“Strategy is about making choices, trade-offs; it’s about deliberately choosing to be different.” — Michael E. Porter
The Growth Compass: How the Best Companies Pick Their Path and Pivot with Purpose
There’s no single road to scaling a company. In fact, there are at least eight.
From the early days of tech sales dominance to today’s AI-native companies exploding with product virality, the question isn’t just how to grow — it’s who leads the growth. Is it the product? The sales team? Engineers, designers, or the data itself? Or maybe, in the age of generative AI, it’s the algorithm doing the selling?
Welcome to the world of -Led Growth strategies — where your growth engine isn’t just what you build, but who drives it.
This post explores the major growth motions shaping modern companies: what they are, how they emerged, when they work, and why transitioning between them is often the key to survival.
The Classic Four
1. Product-Led Growth (PLG)
Try it → Love it → Buy it → Tell others.
PLG is the darling of SaaS. Here, the product itself is the primary driver of growth — not salespeople or big marketing campaigns. Think Slack, Zoom, or Notion: no demos, just value from the first click.
History: Sparked by the rise of freemium and the consumerization of B2B software in the 2010s. Cloud apps had to be delightful, simple, and self-serve.
Champions:
- Blake Bartlett (OpenView) coined the term.
- Wes Bush wrote the book Product-Led Growth.
What Good Looks Like:
- Calendly created instant value with one-click scheduling.
- Notion leveraged templates and collaboration for exponential growth.
Pitfalls:
- Complex onboarding kills momentum.
- It doesn’t work when the product is too technical or enterprise-focused.
When to Use It:
- Self-serve users, fast time-to-value, low CAC goals.
2. Sales-Led Growth (SLG)
Relationships drive revenue.
In SLG, it’s all about the reps. Ideal for complex, high-value B2B deals, this strategy is built on human connection, deep discovery, and long cycles.
History: Dominated the software world pre-2010. Big-ticket enterprise sales ruled before SaaS reshaped distribution.
Champions:
- Marc Benioff (Salesforce): Mastered evangelism.
- Aaron Ross (Predictable Revenue): Revolutionized outbound sales.
What Good Looks Like:
- Salesforce built internal champions and closed huge multi-year deals.
- Snowflake layered sales on top of product-led traction for full-market coverage.
Pitfalls:
- High CAC. Long ramp-up. Slower feedback loops.
- Doesn’t scale without clear ROI or PMF.
When to Use It:
- Big deals, executive buyers, multi-stakeholder sales.
3. Engineering-Led Growth (ELG)
Build it so well, devs can’t ignore it.
Engineering-led growth focuses on APIs, documentation, integrations, and developer experience. It thrives when devs are the buyer — or the influencer.
History: Rose with the API economy and shift-left DevOps culture. Developers gained budget power.
Champions:
- Jeff Lawson (Twilio): “Ask your developer.”
- Patrick Collison (Stripe): Turned payments into code.
What Good Looks Like:
- Stripe’s copy-paste docs.
- Datadog’s seamless integrations for engineering teams.
Pitfalls:
- Bad docs, no community, or poor onboarding kill adoption.
- Technical merit alone isn’t enough without developer trust.
When to Use It:
- Technical audiences, usage-based pricing, and platform extensibility.
4. Design-Led Growth (DLG)
Delight drives demand.
DLG puts UX, aesthetics, and emotional connection at the heart of growth. Users stay not just because it works, but because it feels amazing.
History: Fueled by Apple’s influence and the rise of mobile-first, design-centric apps in the 2010s.
Champions:
- Jony Ive (Apple)
- Brian Chesky (Airbnb)
What Good Looks Like:
- Superhuman’s luxury onboarding created fanatical users.
- Airbnb’s interface made hosting and booking frictionless.
Pitfalls:
- Design without function alienates users.
- Aesthetics doesn’t substitute for core value.
When to Use It:
- Consumer or creative tools. Differentiation by experience.
New Players in the AI-Native Era
5. AI-Led Growth
Let the algorithm do the selling.
Here, AI isn’t just a feature — it’s the engine. Value increases as the model improves, adapts, and learns.
Champions:
- Jasper, Copy.ai, Runway, Midjourney
What Good Looks Like:
- Jasper adapts copy in real time based on user context.
- Midjourney grows through outputs that market themselves.
Pitfalls:
- Poor inference speed, hallucinations, and lack of clarity on value.
- High infra costs can kill margins.
When to Use It:
- When personalization, automation, or data-to-output is the core value.
- When users expect the AI to evolve with them.
6. Community-Led Growth (CLG)
Your users are your sellers.
CLG turns customers into contributors, evangelists, and educators. Think templates, YouTube tutorials, forums, and Discords.
Champions:
- Notion, Figma, OpenAI
What Good Looks Like:
- Notion’s ecosystem of user-generated content.
- OpenAI’s plugin marketplace and dev community.
Pitfalls:
- Community takes time to build and needs constant care.
- Toxicity or misinformation can backfire.
When to Use It:
- When network effects matter or creators are core to growth.
- When you need to scale trust and learning.
7. Data-Led Growth
Let the numbers guide the journey.
Data-led growth leverages analytics, user insights, and personalization loops to increase retention, monetization, and product depth.
Champions:
- Spotify (Wrapped), Duolingo (Streaks), AI copilots
What Good Looks Like:
- Products that get smarter the more you use them.
- Benchmarks and feedback loops drive deeper engagement.
Pitfalls:
- Privacy violations or unclear data usage.
- Over-reliance on data without a narrative.
When to Use It:
- When insight is part of the value proposition.
- When AI/ML features depend on user behavior.
8. Founder-Led Growth
Vision sells early. Execution scales later.
Early-stage companies often grow because the founder leads the charge — through charisma, credibility, or category creation.
Champions:
- Elon Musk, Alexandr Wang, Emad Mostaque
What Good Looks Like:
- Early traction through vision, storytelling, and evangelism.
- Strong GTM built around a central founder thesis.
Pitfalls:
- Founder bottlenecks.
- Lack of scalable process or team redundancy.
When to Use It:
- Pre-PMF or when building a new category.
- When trust and narrative are everything.
How to Transition Between Growth Models
Companies almost always blend these models over time. Successful transitions are intentional, data-driven, and typically occur as a product or market matures.
- Slack: PLG → SLG → Enterprise Land & Expand
- Databricks: ELG → PLG onboarding → SLG for upsell
- Superhuman: DLG → Founder-Led → PLG at scale
- OpenAI: Founder/Engineering-Led → PLG → Community-Led + AI-Led
Picking the Right Compass in the AI-Native Era
AI-native companies face unique pressures: faster innovation cycles, heavier infra costs, and the need to show value fast. That changes the playbook.
Best Combinations for AI-Native Startups
- AI-Led + Product-Led + Community-Led: For viral tools with evolving value (e.g., Jasper, Midjourney)
- Engineering-Led + Data-Led: For dev platforms and infrastructure (e.g., LangChain, Weaviate)
- Founder-Led → Transitions to PLG or AI-Led: For visionary tech with fast GTM needs
Models to Use Carefully
- Sales-Led Alone: Too slow for fast-moving AI categories. Use it as a layer, not the foundation.
- Design-Led in Isolation: Delight won’t save an unstable model or unclear value.
TL;DR: The Growth Strategy Cheat Sheet
| Growth Model | Best Fit | Risk if Misused |
| Product-Led | Self-serve, low friction, viral UX | Poor onboarding = churn |
| Sales-Led | Enterprise, high ACV, multi-buyers | High CAC, long cycles |
| Engineering-Led | Dev tools, APIs, technical buyers | Weak docs, poor DX |
| Design-Led | Consumer, emotional products | Style over substance |
| AI-Led | Adaptive, personalized, automated products | Latency, hallucinations |
| Community-Led | Creators, evangelists, network effects | Needs moderation + investment |
| Data-Led | Insight-driven, behavioral UX | Privacy and transparency pitfalls |
| Founder-Led | Pre-PMF, vision-driven startups | Not scalable, dependency on 1 voice |
Wrapping up…
The best companies don’t just pick one growth engine — they build a portfolio of growth strategies, evolving as their product, customer, and market matures. In the AI-native world, where users expect instant magic and explainability, hybrid models win.
So ask yourself:
- Who’s driving your growth today?
- Who should be driving it next quarter?
- And what’s your strategy for getting there?
Because in the end, growth isn’t a tactic — it’s an organizational belief system.
