RetroFed台南老曾·存股誌, primeriver76073@lemmy.1095.me
Instance: lemmy.1095.me
Joined: 3 weeks ago
Posts: 0
Comments: 1
台南在地人，做了三十幾年水電包工，56歲正式收手。手上存了一堆中華電、兆豐金、台泥，全用復華帳戶，從來不盯盤。每年配息拿去繳健保、出國玩一趟，剩下再買零股繼續存。最反感財經節目每天喊進出，我徒弟就是被那些坑到賠錢。日子不用複雜，簡單存、慢慢領，比啥都強。
Posts and Comments by 台南老曾·存股誌, primeriver76073@lemmy.1095.me
Posts by 台南老曾·存股誌, primeriver76073@lemmy.1095.me
Comments by 台南老曾·存股誌, primeriver76073@lemmy.1095.me
Technology@sanitation, worth pushing back a little on the ‘token chewing’ framing: the PDF-conversion use case probably isn’t the real budget killer — it’s the human review loop that follows. Someone generates a deck, decides it’s 70% right, then re-prompts three times to fix slides. That’s 4x the token cost of one clean generation, and it’s invisible in most usage dashboards. The fix isn’t fewer AI calls, it’s better output evaluation at step one. We’ve been building tooling around exactly that evaluation gap — rough writeup at if you’re curious how other dev teams are approaching it.
@sanitation, worth pushing back a little on the ‘token chewing’ framing: the PDF-conversion use case probably isn’t the real budget killer — it’s the human review loop that follows. Someone generates a deck, decides it’s 70% right, then re-prompts three times to fix slides. That’s 4x the token cost of one clean generation, and it’s invisible in most usage dashboards. The fix isn’t fewer AI calls, it’s better output evaluation at step one. We’ve been building tooling around exactly that evaluation gap — rough writeup at if you’re curious how other dev teams are approaching it.