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[🎂] HAPPY DAY 2026.03.03 𝐇𝐀𝐏𝐏𝐘 𝐂𝐇𝐎𝐑𝐎𝐍𝐆 𝐃𝐀𝐘🎉 에이핑크의 영원한 롱리더 초롱의 생일을 축하합니다💛 #에이핑크# #Apink# #박초롱# #초롱# #ChoRong# #HAPPY_CHORONG_DAY#

[#에이핑크#] 250303 해피 초롱 데이! 🐰 오늘은 우리 핑크의 소중하고 사랑스러운 리더 초롱이의 생일입니다! 🎉 특별한 이 날, 롱롱이의 생일을 함께 축하해주세요🌟 초롱아 생일축하해💕 #HappyChoRongDay# #Apink# #ChoRong# #박초롱# #초롱#

[#에이핑크#] 20240303 HBD 초롱🐰 오늘은 우리핑크 영원한 리더🌟 초롱이의 생일입니다🎉 우리의 자랑 롱롱이의 생일 함께 축하해주세요❤️ 초롱아 생일축하해💕 #HappyChoRongDay# #Apink# #ChoRong# #박초롱# #초롱#

We tried using Meta's new Muse Code agent, but it has a bug that doesn't let it sign in from a docker container. So we did a fun experiment: Meta claims Muse Spark 1.2 was co-trained with their Muse agent harness. So we extracted instructions from their system prompt and added them to the Cline harness. TL;DR of this special prompting: - Trust source code over the user prompt, so read every call site and existing tests before starting the task - Weigh edge and error cases as heavily as the happy path - Always reproduce the bug before fixing - Don't trust the first passing test suite, and verify suspicious looking half-baked tests - Never stop at just editing, keep working until the change is verified complete. We then asked this modified harness to fix a real bug from our repo, and compared the results to the original Cline agent harness. Results: - Used 2.7x fewer tokens (19.7M → 7.2M) - Finished 2x faster (49min → 24min) - Cost 2.4x less ($7.69 → $3.25) Same Muse Spark 1.2 model, same task, only the prompting changed. Incredible how much of a performance gain Meta was able to achieve training it on these special instructions!

"Aw, this the best in the world, right here." Ant's daughter left a heartfelt message inside his NBA All-Star ring box in February 🥲❤️ Happy 25th Birthday, @anthonyedwards!