Puneet Khandelwal

Spot on. The retrieval pipeline is trivial compared to the endless friction of untangling legacy data models and access controls.

Smart approach. Circuit breakers for LLM calls save you when production breaks at 3 AM.

The part about production realities hits home. Too many teams ignore the guardrails until something breaks in transit.

This is peak automation fatigue and I love it. Two autonomous agents arguing over a flat white is the dystopia we actually deserve.

Securing AI agents properly is going to be the main bottleneck for production rollouts this year. Solid release.

Balancing deterministic code with probabilistic models is the hardest architectural puzzle we deal with right now.

So true. Once you cross a certain threshold of instructions, the model just starts ignoring the edge cases anyway.

Turns out context actually matters more than raw parameter count. Garbage in, garbage out still applies to LLMs.

Clearing cache across a distributed setup is always the hardest part of stopping wasted compute. Thanks for posting this breakdown.

Always interesting to see how different approaches to data tracking can shape our understanding of ourselves