Mark Roberge at Stage 2 Capital co-created the Science of Scaling methodology, a quantitative framework used by hundreds of startups to decide when to scale based on leading indicators like product-market fit and retention, which he codified in his book and podcast. He positions himself as a professor-operator VC who concurrently runs Harvard Business School courses and teaches structured, step-by-step approaches to revenue growth that founders widely cite as canonical playbooks for building sales engines.

• A heavy emphasis on mastering enterprise sales dynamics and building internal champions. Closing large deals relies on identifying advocates who can navigate complex decision-making units behind closed doors. For example, pointing to early Cloudflare sales strategies, the core idea is that the winning vendor is ultimately chosen when the sales rep is out of the room, making it vital to find advocates who are both willing and capable of pushing the deal forward.
• Advising on the nuances of early-stage sales hiring and scaling strategy. Founders should avoid prematurely scaling or defaulting to legacy corporate structures, instead focusing on customer development and agile planning. As a specific example, early Cloudflare teams hired helpful engineers rather than traditional account executives to talk to customers, and startups are encouraged to use quarterly planning instead of annual cycles to avoid doubling down on bad assumptions. Early sales hires must also be highly capable of translating market feedback directly to product and engineering teams.
• An analytical approach to defining product-market fit rather than relying on gut feelings. Product-market fit should be definitively measured early in the sales process to prevent wasting engineering resources on faulty market signals. One recommended tactic is pushing early customer interviews toward securing a contract or pre-payment as a concrete test of actual demand, which proves value much better than basic founder intuition. 
• Observing the strategic role of artificial intelligence in reshaping pipeline generation and software adoption. Artificial intelligence is highly effective for high-level strategy, process automation, and account targeting, though founders must navigate changing executive attitudes toward new software. For instance, the startup QuotaPath successfully built a complete sales pipeline without hiring entry-level sales reps by leveraging artificial intelligence to strategically refine their ideal customer profile and automatically identify the best target accounts.