Stanford NLP amplifies case for teaching agents by writing the raw loop from scratch
stanfordnlp · x · 2026-11-12
Stanford NLP's account amplified a take arguing that building agents from scratch without black-box high-level frameworks is the only way to truly master error recovery and sliding context compression — teaching students to write the raw loop first demystifies agent engineering. It feeds into the ongoing debate over framework abstractions vs. bottom-up understanding in AI education.
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