1. Problem space
The problem space is everything true about a person's situation before anyone proposes a solution: what they need, what they do now, what stops them, what they are really after. It is explored by observing more than asking, by looking for patterns rather than quotes, and by going for root causes rather than symptoms.
- What is the problem space in product discovery?
- How do you explore a problem without jumping to solutions?
- What is the difference between a symptom and a root cause in customer research?
§There is a space that exists before your does. It is made of the people you want to serve, what they are trying to get done, how they get it done today, what gets in their way, and what they would really rather be doing. Nothing in it is yours. It was all there before you arrived and most of it will be there after you leave. That is the problem space, and discovery begins by admitting that it has to be looked at rather than imagined.
§ 1.1What lives there#
§Four things, and they are worth separating because teams collect one and think they have all four.
§Needs and pains. What the person is trying to achieve and what it costs them today, in time, money, stress or missed outcomes. This is the layer people can talk about, which makes it the easiest to collect and the most misleading, because people describe their pains in the language of the solutions they already know.
§Current behavior and workarounds. What they actually do now. The spreadsheet, the group chat, the intern, the habit of doing it on Sunday night. This layer is more honest than the first because it is observed rather than reported, and it is where the real cost of the problem shows: nobody builds a workaround for a problem they do not have.
§Constraints. The environment: the boss who has to approve, the regulation, the device they are on at the moment the problem occurs, the budget that is not theirs to spend. A solution that ignores this layer is a solution for a person who does not exist.
§Underlying motivation. What they are actually after, one level up from . The founder who wants "a better CRM" wants to stop losing deals; the person who wants to stop losing deals wants to make payroll without fear. Solutions can address any level. The ones that last address the level the person cares about.
§ 1.2How it is explored#
§Steve Blank's instruction from two decades ago still holds: get out of the building. The building is where solutions live. The is wherever the person is when the problem happens, and there are four habits for looking at it properly.
§Observe more than ask. What people do when they think nobody is watching outranks what they say when someone is. Look for patterns rather than stories: one person's complaint is an anecdote, five people's identical workaround is a fact. Understand the context, because the same task at nine on a Monday and at four on a Saturday is two different problems. And keep asking why until the answer is a cause rather than a symptom, since a symptom addressed is a problem that returns.
§ 1.3The trap in the problem space#
§The trap is that you are biased by your own understanding of the world, and the problem space is exactly where that bias is most invisible. A founder who has spent five years in an industry sees its problems the way the industry describes them, which is usually the way the incumbents want them described. The honest difficulty, as the original guide put it, is that it is hard to know when you have enough data about a problem, because the feeling of understanding arrives long before understanding does.
§The next chapter is about the other space, the one you do get to invent, and why it is dangerous to enter it early.
The problem space is what is already true. You do not invent it; you go and look at it.
- Steve Blank, The Four Steps to the Epiphany (2005), on customer discovery. steveblank.com/books-for-startups
- Teresa Torres, Continuous Discovery Habits (2021), on the opportunity space. www.producttalk.org/continuous-discovery-habits
- Aravind Srinivas, interviews on Perplexity's origin as a tool for answering questions with citations (2023–2024). www.perplexity.ai/hub