01
Complete
Fundamentals
C, memory, data structures, algorithms. CS50x, then continued in C on my own.
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AI journey
Models are the visible part. Serving, data pipelines, evaluation and behaviour under load are infrastructure — and that is the foundation I am building. One stage complete, one underway, two ahead.
01
Complete
C, memory, data structures, algorithms. CS50x, then continued in C on my own.
02
In progress
APIs, data modelling, authentication, and typed service code. One stack understood properly rather than five sampled.
03
Planned
asyncio, queues, caching and the failure behaviour of distributed components. Formalised alongside the systems track at BITS.
04
Planned
Serving, evaluation, data pipelines and the infrastructure models actually run on — the backend problem, with a harder correctness story.
A model that returns the wrong answer is a research problem. A serving layer that returns the right answer to the wrong tenant, or silently drops a third of a batch, is an engineering failure — and it is the kind of failure I have already spent four years learning to design against in a physical system.
So the sequence is deliberate. Fundamentals first, because you cannot reason about cost without them. Then backend depth, because that is where correctness is enforced. Then concurrency and distribution, because that is where correctness gets hard. ML systems last, because they need all three.