It might not obvious to a number of readers on HN, but whole language reading instruction is soundly discredited[1]. For those who prefer listening, the America Public Media podcast Sold a Story[2] covers the history of reading instruction in the English-speaking world and the rise and (slow) fall of whole language hokum in extensive depth.

And CrazyStat's implication strikes me as still largely true, so I'll make it explicit: even frontier LLMs will still resort to sycophancy when there's sufficient contradictory information in their weights to reproduce only some of it in response to a user query. And the harnesses that LLM providers silently, invisibly integrate behind-the-scenes to counteract hallucination and syncophancy are definitionally patch-jobs at best. The latest models may be better when explicitly instructed or configured by default to search the web and pull sources into their context, but the root problem remains unsolved and can still rear its flattering head if you're not paying close attention.

[1]: https://journals.sagepub.com/doi/10.1177/1529100618772271

[2]: https://features.apmreports.org/sold-a-story/