Solution-First vs. Problem-First: Building Products That Matter

Jan. 23, 2025
  
Written by Frank Eiffel
Solution-First vs. Problem-First: Building Products That Matter

Introduction: The Expensive Mistake 90% of Founders Make

Did you know that 42% of startup failures stem from building solutions nobody needs (CB Insights)? Yet most technical founders keep repeating this costly mistake. And I’m not proud to admit that I’ve made the same mistake myself.

Why do we create elegant [enter tech buzzword] solutions for non-existent problems? Well they exist in our minds, and we believe other people feel or identify with the same pain daily. But that's not generally the case.

This post will reveal:

  • The psychological traps of why we create useless products.
  • Practical methods to discover problems worth solving (the part we hate doing)
  • Ideas to confront these problems and create an engineering-based approach to solve these issues.

Why Our Brains Love Solution-First Thinking: The Builder's Bias

Short Explanation:

Psychologist Barry Schwartz notes in The Paradox of Choice: "Expertise creates cognitive narrowing."

Basically, this means that we instinctively ask ourselves "What can I build with React/AI/Web3?" rather than "What needs fixing?"

The long explanation:

As Daniel Kahneman explains in "Thinking, Fast and Slow," our brains are wired to favor cognitive ease, often defaulting to what he calls as "System 1" the fast, automatic, and intuitive mode of thinking to solve problems with minimal effort (which is incredibly important to navigate daily menial tasks like the mechanics of walking and breathing, you basically don't even think about them when you are doing them).

This "System 1" relies on heuristics, biases, and ingrained patterns to generate quick answers, bypassing the need for deliberate analysis. By contrast, "System 2", our slower, effortful, and analytical mode, requires conscious activation and mental energy, an example would be a hard math question where we need to take time to properly do it.

Humans inherently lean on "System 1" to avoid the strain of engaging "System 2", a tendency Kahneman calls the "law of least effort." While this efficiency helps navigate routine tasks, it can lead to errors in judgment when complex problems demand logical scrutiny.

In simple terms, when we’re brainstorming ideas or identifying problems to solve, we often skip thorough research to figure out what’s truly worth pursuing. The same thing happens during the validation stage we cut corners because of our biases. As tech enthusiasts, we tend to gravitate toward the programming and technical side of things, putting less effort into research and validation, which feel less exciting or outside our comfort zone.

On the flip side, a marketer might approach this very differently. They might prioritize building a minimal viable product (MVP) and creating a solution that resonates emotionally with their audience. Even if the product is low-value, they might still gain traction because they’ve effectively tapped into a pain point that people are eager to address. While this approach can drive initial interest, it might not always lead to long-term value.

Info: OpenAI's GPT-3 release sparked 5,000+ "AI wrapper" startups in 2022. Less than 12% survived 18 months (Crunchbase).

The Problem-First Advantage: Why It Wins (When Done Right)

Case Study: From Solution Graveyard to $4.2M ARR

  • Problem: Restaurant owners wasting 11 hours/week manually updating menus across 15 platforms
  • Solution: Airtable-like tool requiring coding skills → Failed
  • Pivot: Zapier-for-restaurants with pre-built templates → Miso ($4.2M ARR)

3 Reasons why Problem-First Works Better

  1. Pain Valuation: Again, In Thinking, Fast and Slow, Daniel Kahneman, highlights loss aversion which is the psychological impact of losing something. Which is roughly 2.25 times stronger than the pleasure of gaining something of equivalent value.
  2. Focused Differentiation: Niche problems == less competition.
  3. Validation Shortcut: Existing complaints == proven demand.

FAQ:

Q: Won't focusing on problems limit my technical growth?
A: Opposite—real-world constraints breed innovation. Stripe emerged from payment pain, not "cool API ideas."

Q: How technical should the solution be?
A: 72% of successful SaaS started as manual services (Y Combinator). Start human, then automate.

Q: What if my skills don't match the problem?
A: 83% of product engineers learn new tech after validating the problem (Stack Overflow Survey).

Lastly, Your New Development Workflow

  1. Mine (1 week):

    • Scrape 500+ pain points using scripts (or manual info retrieval)

  2. Validate (3 days):

    • Create "fake" solution landing page
    • Run $200 FB ads to target niche
    • Check if FB ads give positive response, if not, go back to point #1.

  3. Build (1 month):

    • Manual MVP first (don't spend more than 1 week)
    • Automate only after 5-10 paying clients

"The art of innovation is not building—it's listening. Code is just the final whisper." - Adapted from Steve Blank

External Tools and Resources: