Datasets are the real bottleneck in African AI
Most people talk about models first. In African AI, the real constraint is still the dataset layer.
Writing / Essays / Notes
Ideas about AI infrastructure, voice systems, and what real deployment actually requires.
Writing is where I try to make the strategy legible. The product work matters, but the deeper questions are usually about language, access, infrastructure, and what it takes to build systems that survive contact with the real world.
Essays
4
Pieces on language infrastructure, voice, and execution
Themes
- Qwen 3.5
- Amharic
- Tokenization
- Research
- Datasets
Why This Page Exists
The homepage shows the work. Writing explains the logic behind it: why voice matters, why datasets matter, and why real deployment is harder than most teams admit.
More Essays
Why voice AI will dominate emerging markets
In markets where interfaces still exclude large parts of the population, voice is not a feature. It is the product layer.
The gap between demos and deployment
A good demo proves that something can work once. Deployment proves that it keeps working when conditions stop being ideal.
Editorial Note
These essays come from building, not commentary. They are written to make the realities of African AI clearer: the constraints, the tradeoffs, and the decisions that matter in practice.