Great conversation about the future of open-source AI models. The tension between safety and openness is one of the most important debates of our time.
Controversial take: Most AI wrappers will die in the next 12 months.
Only those building real moats — proprietary data, unique UX, vertical integration — will survive.
The "ChatGPT but for X" era is ending.
Just shipped a new feature using AI-assisted coding. What used to take 2 days took 4 hours. The productivity gains are absolutely real 🔥
Tools I used:
• Cursor for code generation
• Claude for architecture planning
• GitHub Copilot for boilerplate
New paper alert 📄
We achieved 94.2% accuracy on cross-lingual transfer learning using only 1% of the training data.
Key insight: pre-training on code dramatically improves language understanding across all tasks.
Deployed our ML pipeline using Kubernetes and it's been rock solid for 3 months now. Zero downtime.
Happy to share the architecture if anyone's interested. DM me or reply here 👇
Year 2 of our startup journey:
• 50K users
• $2M ARR
• Team of 12
• Zero paid marketing
The secret? We built in public and let our community do the talking.
Here's everything I learned about organic growth 👇