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[📷] 8월의 더위도 잊게 만든 우정들의 축하 덕분에 시원하고 행복했던 하루 생일 축하해줘서 고마워요, 우정💖 #연정# #YEONJUNG# #우주소녀# #WJSN# #HAPPY_YEONJUNG_DAY# #연정이_생일이_왔뎡#

[📢] HAPPY YEONJUNG DAY LIVE 안내 📅 2025.08.03 (SUN) 6PM 🔗 #연정# #YEONJUNG# #우주소녀# #WJSN# #HAPPY_YEONJUNG_DAY# #연정이_생일이_왔뎡#

性价比最高的10个应用： 💰小额案（200-500）容易成单 LUUP、马赫兼职、乐天返利、Trima、可口可乐ON 💎高单价（1000+）利润猛 Studio Sapuri、U-NEXT、Happy Mail、Pairs、Tapple 关键是用户不花钱，转化特别容易，特别适合新手。

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!