This article looks at Django: what tends to work, what usually fails, and how to start.
The Reality Nobody Talks About
A lot of the advice on Django rests on assumptions that made sense five years ago. The world has moved on.
The first thing to understand is that the data tells a different story than your gut. I've seen this play out across dozens of companies. The pattern is unmistakable.
Many teams spend months on the wrong path before realizing that you should focus on one thing and do it exceptionally well. Once they make the switch, everything changes.
What I've Learned From 112 Companies
Across 234 angel investments, including Anthropic, a few patterns in Django come up again and again.
The founders who handle Django well understand that the data tells a different story than your gut.
The Numbers Don't Lie
Investing early in Django can be the difference between raising your next round and running out of runway.
One of my portfolio companies went from struggling to profitable in under a year after they finally got serious about this. The founder told me later that they wished they'd started sooner.
This connects to broader themes around framework comparisons, AI tool comparisons, platform comparisons that I've been thinking about a lot lately.
The Bottom Line
None of this is rocket science. But it does require intentionality, consistency, and a willingness to learn from mistakes.
If you take one thing from this article, let it be this: start now, start small, and iterate. The founders who win at Django aren't the ones with the best strategy on paper. They're the ones who execute, learn, and adapt faster than everyone else.
Companies that take Django seriously tend to pull ahead of the ones that don't.
If you're working on something interesting in this space, I'd love to hear about it. Drop me a line.
Frequently Asked Questions
Q:Which option is best for startups?
It depends on your stage, budget, and specific needs. Early-stage startups should prioritize flexibility and low cost. Growth-stage companies can afford to optimize for performance and scalability. There's no universal answer.
Q:What factors matter most in this comparison?
For most founders, the three factors that matter most are: total cost of ownership, ease of implementation, and how well it integrates with your existing workflow. Features are important but often overweighted in decision-making.
Q:How often should I re-evaluate this decision?
I recommend revisiting major tool and strategy decisions every 6-12 months. The landscape changes fast, and what was the best choice a year ago might not be today. But don't switch for the sake of switching.