Doppel's first enterprise customers came from referrals via their existing crypto clients. Founders from the crypto space, who previously worked at larger tech or finance companies, made introductions to their former colleagues, creating a warm path into new verticals.

Instead of pitching features, Katera builds AI agents that find sales opportunities for their prospects (e.g., relevant Reddit threads) and sends those leads directly. This "show, don't tell" approach provides immediate value and dramatically increases response rates.

Contrary to the PLG trend, Canary focused on building a scalable outbound sales engine first. Their rationale: if you can make cold outreach profitable, you have a more controllable growth lever. Inbound can then be layered on top as a bonus, rather than being the sole, less predictable driver of growth.

To scale, MongoDB built a sophisticated "Pipeline Generation Recipe" that took a day and a half to train. It combined technical tactics (like reverse IP lookups) with persona-based messaging for developers, ops, and LoB owners. This transformed the sales motion from passive to active demand creation.

Nathan May built a $1M ARR business with a private, invite-only newsletter for just a few hundred key decision-makers. Instead of mass marketing, he manually invited high-value targets via LinkedIn, using social proof (mentioning their peers) to build trust and generate high-ticket sales.

Fletch PMM grew its business entirely through LinkedIn by focusing on a hyper-specific niche. This targeted content pleases the algorithm and attracts high-intent leads who are already indoctrinated into their methodology before the first sales call, making the sale nearly automatic.

Fueled by massive inbound demand, some AI B2B companies scale to $50M ARR with sales teams of five or fewer. This represents a 20x reduction in sales headcount compared to the traditional SaaS playbook, which would require over 100 reps to achieve the same revenue milestone.

To fill her sales calendar without sacrificing her own time on manual outreach, Merge's founder hired a college intern. The intern's sole job was to research prospects and send cold outbound messages using the founder's identity, allowing the founder to focus only on booked meetings.

The AI company generated 30-35% of its new ARR over the past year using an efficient Account-Based Marketing (ABM) stack. They use Apollo for data sourcing, Clay for data enrichment, and Smart Leads for sequencing email and LinkedIn outreach, supplemented by a small in-house orchestration tool. This offers a concrete playbook for lean teams.