Consider Starting an AI Startup in Parallel | Generated by AI
Question: Should I start a startup based on my resume?
Answer:
After reading your resume, my answer is:
Yes—but I would not quit your job immediately. I would build a startup in parallel until it has clear traction. (Zhiwei Li)
The interesting thing is that you are not a typical software engineer thinking about entrepreneurship. You have already been a founder before.
From your resume, you have:
- Founded two startups
- Raised approximately 500k CNY in investment
- Built a product with 30,000 users
- Reached around 3 million CNY annual revenue
- Applied to Y Combinator and even reached the interview stage once
- Written hundreds of technical articles with 75k monthly page views
- Built many open-source projects
- Worked in enterprise engineering (HSBC, DBS, LeanCloud, etc.)
- Spent the last several years becoming deeply involved with LLMs, AI coding, GPU training, and AI infrastructure. (Zhiwei Li)
Those are much stronger founder credentials than most first-time founders.
Your biggest strengths
1. You are a builder
Many founders can pitch.
Many engineers can code.
Relatively few people can:
- design
- code backend
- code frontend
- build mobile apps
- deploy infrastructure
- train models
- write documentation
- market through blogging
You can.
That dramatically reduces early startup costs.
2. You already have distribution
Many engineers start with:
Great product. Zero audience.
You already have:
- technical blog
- GitHub
- AI community
- years of public writing
That is a significant advantage.
3. AI is your timing advantage
Looking through your resume, your interests are concentrated around:
- AI agents
- LLM engineering
- GPU optimization
- developer tooling
- automation
- AI coding
Those are among the fastest-growing software markets today.
Your weaknesses
I think there are three.
1. You enjoy technology more than selling
Your resume contains pages of engineering accomplishments.
Very little about:
- customer interviews
- pricing
- sales
- recurring revenue
- retention
- marketing funnels
That is normal for engineers.
But startups usually fail because they cannot sell, not because they cannot build. Research on software startups consistently finds that weak problem validation and insufficient market learning are common failure patterns. (arXiv)
2. You like learning many things
Your interests include:
- AI
- machine learning
- vision science
- investing
- English
- Japanese
- blogging
- hardware
- travel
That makes you interesting.
It can also reduce focus.
Great startups often require obsessive focus on one problem for years.
3. Enterprise salary has opportunity cost
You now have:
- stable income
- family
- children
A startup is much riskier than when you were 22.
That changes the equation.
What startup would fit you?
I would avoid consumer social apps.
Your advantage is clearly developer productivity.
Ideas that fit your background:
- AI engineering platform
- AI coding workflow
- AI DevOps
- AI testing
- enterprise AI agents
- documentation automation
- multilingual AI documentation
- AI infrastructure tools
- GPU optimization tools
These leverage everything you’ve already built.
What I would do if I were in your position
Phase 1 (0–6 months)
Keep your current job.
Spend nights and weekends building one AI SaaS.
Goal:
- 10 paying customers
not
- 10,000 users.
Phase 2
Reach roughly enough monthly recurring revenue to meaningfully offset your salary (for example, 30–50% of your employment income).
Only then consider reducing work hours or leaving your job.
Phase 3
When the business demonstrates sustained growth, commit full-time.
That greatly reduces downside risk.
One thing I would change
Your resume says:
AI Engineer
I think your positioning is actually stronger as:
AI Product Engineer
or
Founding AI Engineer
because your experience combines:
- engineering
- product
- startup
- AI
- infrastructure
That combination is rarer than simply being another AI engineer.
Overall assessment
If I were scoring founder potential:
| Area | Score |
|---|---|
| Engineering ability | 10/10 |
| Learning speed | 10/10 |
| Product intuition | 8/10 |
| AI knowledge | 9/10 |
| Distribution (blog/open source) | 8/10 |
| Business execution | 7/10 |
| Sales | 6/10 |
| Fundraising potential | 8/10 |
Overall founder potential: 8.8/10
I believe you have a realistic chance of building a successful AI company. The main challenge is unlikely to be technical execution—it will be identifying a painful customer problem, validating demand early, and staying focused on one product long enough to achieve product–market fit. Founder characteristics matter, but investors and customers ultimately care about execution and traction rather than credentials alone. (arXiv)
References:
- Your resume: https://lzwjava.github.io/resume-en (Zhiwei Li)
- Research on founder assessment and startup success: (arXiv)
- Research on why early-stage software startups fail: (arXiv)