tl;dr; Forming a market thesis means spotting trends with data and gut feel, asking if they fit our strengths and market potential, and monitoring signals. Past bets like Golang show how we position for the next wave.
Figure out where the market heads and how we fit in; that's the core of a market thesis. Think of it like a bet, but a really serious one. It's not a wild gamble. It's a firm belief that takes a lot of groundwork, time, and team effort to see through. Get it right, and we position ourselves for the next wave. Get it wrong, and well, we learn.
Spot worthwhile pulses
To spot a trend or "pulse" with real potential isn't simple. It's less about a magic formula and more about a mix of sharp analysis, deep experience, and sometimes, a good gut feel. Here’s how we can approach this:
1. Beyond the gut: the role of data and observation
- Data is a start, not the whole story: Sure, we collect data. Our Growth engine is designed to pick up signals, things like hire trends, fund news, and tech talks. This is our "what." It tells us what goes on. But data alone rarely shouts "this is the one!" It often needs thought and context. The raw Vietnamese note "la thanh phan bo tro" (it's a supporting component) in the original draft really nails it; data supports, it doesn't decide.
- Develop informed intuition ("the gut"): Your "gut" isn't mystical. It's how your brain quickly sees patterns, built from experience. In the early days of a trend, when media coverage is zero and data is thin, keen observation is king. What do innovators and early adopters actually do and talk about? What quiet shifts happen in niche groups or VC circles? If you dig in and stay curious, it pays off here. No one has a crystal ball, but seasoned observation can give us a head start.
2. Add layers of nuance: questions to ask ourselves
Once a pulse catches our attention, from data or gut feel, we need to dig deeper:
- Problem-solution fit: Does this new tech actually solve a real, big problem for someone? Or is it a cool solution that needs a problem?
- Strategic alignment and our strengths: Does this fit who we are and what we're good at? Can we realistically build the skills, or is there real excitement and energy from the team to learn? A bet that doesn't fit our core or passion is tough to win.
- Market potential and scalability: Okay, it's cool, but is there a real market for it? Can solutions based on this pulse actually scale, or is it just for a small niche?
- The competitive vibe: Who else shows interest in this? Is it already a crowded space, or can we bring a unique angle and truly stand out?
- Timing and ecosystem readiness: Is the world ready for this? Are the base technologies and setup mature enough to support it? (This links to the "adjacent possible" we talked about in
cycle.md). - Resource reality check: What will it really take to chase this? We need an honest look at the cost in time, people, and money versus the potential win.
It's this mix, initial signal spot, deep-dive questions, and strategic thought, that helps us move from "huh, that's interesting" to "okay, this might be a serious thesis."
- The upside
what can we make with this new tech? what do customers want with this new tech? can we implement them? how long does it take?
Monitor social signals
The tech world always buzzes. Builders constantly create these "tiny pulses," new ideas, projects, and companies. Some fade fast, but a few grow into big waves that change how we work and live. Think of it as a constant flow of possibilities. Right now, we see a lot of energy around areas like advanced AI automation, changes in platform operations (DevSecOps, LLMOps), the slow but steady move of blockchain into more common financial uses, and the setup for spatial computing. The key isn't to chase every pulse, but to check them against the thesis we build.
Past theses and lessons learned
We learn from the past; it's part of this. Over the last ten years, we've made several bets:
- Mobile app development
- Strategic shift from Ruby to Golang
- Infrastructure evolution: Ansible > Docker > K8s
- Fuchsia OS (didn't pan out as a major path for us)
- Rust (we chose to skip)
- Elixir (didn't get the traction we explored)
- Blockchain dapps (some traction, but the market went a different way than early guesses)
When we look ahead, areas like deeper AI automation and spatial computing are definitely on our radar; we constantly check them out.
Case study: Golang adoption
My bet on Golang is a good example of this process. With a software engineer background, I always studied languages and practices to build better software. After years with Java, Python, and Ruby, I saw Go as a new language. It fixed many pain points and had huge potential, especially for systems that do many things at once.
It wasn't just a tech curiosity. I helped build the Golang Vietnam community. This group gave developers a space to learn, try things, and use this concurrency-first language. This hands-on community work provided priceless real-world signals. Turns out, Go delivered on its promise. We built a strong team around it and got to work with top-tier companies. This proved that early thesis right.
Resources
- Understand the value chain
Next: Test the water or Keep it sharp
