there's this interesting misalignment of incentives in a certain type of heavily financed software startup wherein engineers are not only encouraged to be cost-agnostic in the solutions they design, but are actively discouraged from spending time to save money
this makes sense in the short term as the company seeks to find product/market fit, and to iterate quickly on features to capture as much of the market as possible
but longer term it has the effect of locking out access to an entire market segment of price-sensitive consumers
due to architectural decisions not prioritizing cost, this sets a very high opex floor, which has downstream consequences on pricing structure, which constrains the target demo to price-insensitive buyers such as large institutions
this, in turn, influences the product backlog
iterated over several years this can effectively lock in corporate strategy and make it downright impossible to target smaller consumers, as the entire organization is used to a certain way of working, with a certain amount of overhead and flex budget built into the process
this overhead opens the door for smaller leaner competitors to swoop in & scoop up large swaths of the market that ur product was inaccessible to; since there are typically many more of these consumers, this gives your competitors a treasure trove of a market research opportunity
this huge pool of many low-value clients, while harder to scale a business with, does enable one to iterate much faster and with a higher risk tolerance, which has accumulated benefits for R&D, allowing these competitors to challenge you for the higher-value clients down the line
this is a major part of why I'm generally more philosophically aligned with the B2C SaaS startup approach, as it's much easier to scale up to target large enterprises than to scale down to target smaller consumers
having many small users drastically increases your learning rate
the practical upshot is that if it's feasible for ur problem space, to start off by targeting the low-value market segment, investing in quicker iteration & lean ops early on; you'll be more likely to arrive at an optimal equilibrium prior to locking in strategy during scaling