Step 8: Understand what is possible to build
Phase 1: Preliminary Research · Step 8 of 13
Technology selection follows customer understanding. But you need to know what is possible and what it costs before you can make honest capability assessments later.
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Technology is a means, not an end. But understanding what is technically possible, what it costs, and what talent it requires is essential context for honest strategy. Too many founders either overestimate what they can build or underestimate what it will take.
The technology landscape for any market has three layers. The current layer is what powers today's leading solutions. Understanding this tells you the table stakes: what any new entrant must match just to be considered. The emerging layer is what is becoming possible in the next one to three years. This is where new entrants can leapfrog incumbents if their timing is right. The speculative layer is what might become possible but is not yet reliable enough to bet a business on.
Cost is the reality check. A brilliant technical approach that costs ten million dollars to build is not viable for a bootstrapped founder. A simple approach that can be built for fifty thousand dollars but only achieves eighty percent of the performance might be the smarter bet. Understanding these tradeoffs early prevents the most expensive mistake in technology: building the wrong thing at the wrong scale.
AI deserves special attention in any current technology assessment. The gap between what AI can demonstrably do and what AI is marketed as doing is enormous. For your specific market you need to understand where AI is creating real, measurable value and where it is still a science project dressed up as a product. This distinction will affect both what you build and how you position it.
Talent scarcity is the often-overlooked dimension of technology assessment. If building your solution requires skills that are rare and expensive, that affects your timeline, your budget, and your ability to iterate. Understanding the talent landscape now prevents painful surprises when you start building.
Key Takeaways
- Why: You need to know what you can actually build before you commit to solving a problem.
- What: Use AI to map the technology landscape for your market.
- Output: A technology summary covering current solutions, emerging capabilities, and build cost estimates.
AI Prompt
Act as a technology analyst. Based on this market and competitive landscape: [paste your step 2 and 6 outputs here].
Provide a technology landscape assessment. Include:
- What technologies currently power the leading solutions in this space
- What emerging technologies could disrupt or enable new solutions in the next one to three years
- Realistic cost ranges for building a basic viable solution in this space today including infrastructure, talent, and tooling
- What AI capabilities are currently being applied in this market and where they are producing real value versus hype
- What skills are required to build in this space and how scarce that talent is
Flag all cost estimates as estimates and note what drives variance. Flag technology predictions as speculative. Cite sources for current technology claims.