Pratik’s Pakodas \ud83c\udf7f
Pratik BhavsarPractical insights for becoming a top AI Engineer.
| Platform |  | Pricing | Only free issues | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 80 | Founded | 6 years ago | Last Issue | 13 days ago |
| Active | |||||
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pakodas.substack.comLatest Issues
State of LLM Routers in 2026
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Every few months the AI industry seems to discover a new optimization. The focus moved from prompt engineering to retrieval, then to reasoning, then to agents, and more recently towards routing.
Infrastructure providers are...
How Code is Evaluated in Benchmarks
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Cursor got acquired last week and it reminded me to survey how coding benchmarking is done. If you come from the world of knowledge benchmarks like MMLU or reasoning benchmarks like GPQA, coding evals look familiar at first:...
How to create loops for AI Research
Research is hard. You get a desk, a problem, and a vague feeling to produce something novel. So most people reverse-engineer the job from what they can see: papers, threads, announcements. What they learn is how to look like a researcher....
Continual Learning Without Evals Is Just Drift
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Harrison Chase published a useful framework this week for thinking about continual learning in AI agents. He breaks it into three layers: model (updating weights), harness (optimizing the agent code), and context (memory, ski...
How to Be a 30x AI Engineer with a Taste
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A different kind of engineer is becoming disproportionately valuable. And almost nobody can precisely explain why.
The word that keeps coming up is “taste.”
Emma Tang, head of data infrastructure at OpenAI, said it directly...
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