Tokens, training, context windows, and temperature — the four concepts that explain everything about large language models.You know how your phone suggests the next word when you’re texting? Type “I’m going to the” and it suggests “store” or “park.”Now…
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Production-ready answers for 2026 ML interviewsContinue reading on Medium »
By Mudit Dave | AI EngineerContinue reading on Medium »
There’s a particular kind of tedium that every AI engineer knows intimately: the prompt-tuning loop. You write a system prompt, run your agent against a benchmark, read the failure traces, tweak the prompt, add a tool, rerun. Repeat this a few dozen times and you might move the needle. It’s grunt work dressed up in […]
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A ~300-line Python package that gives AI coding agents persistent, confidence-based memory via the Model Context ProtocolContinue reading on Medium »
The “bigger is better” era of LLMs is officially taking a backseat to a new, more competitive frontier: The Small Language Model (SLM)…Continue reading on Medium »
I’ve been reading the recent research on “cognitive surrender” — the term for how people stop using logical thinking when they rely on…Continue reading on Medium »
How Claw Code different from Claude Code?Continue reading on Data Science in Your Pocket »
Photo by Nahrizul Kadri on UnsplashContinue reading on Medium »