给 Dots 连派 10 个任务的翻车风险
作者引用 OpenAI 系统卡数据,指出任务链越长错误越会累积,并用四角色分工方案降低 Dots 在交易等场景的出错率。
OPENAI DOTS LAUNCHED. EVERYONE POSTED THE PLUSH TOYS. NOBODY POSTED WHAT HAPPENS WHEN YOU GIVE A DOT 10 TASKS IN A ROW from openai's own system card: chain 5 steps, 8.6% of runs get flagged for boundary problems. chain 10, already 19.7%. more than double if errors were independent, 10 steps would give 16.5%. the measured number is higher. errors compound. a step that drifts slightly hands a wrong picture to the next step, and the next step builds on it now imagine this on http://pump.fun. 98.6% of tokens are scams. the dot found a token, read holders, calculated concentration, evaluated momentum, decided to trade. if step 1 pulled a scam, every following step builds a case for buying that scam i built a dot with 4 seats instead of one: > LOOKOUT: only monitors. no evaluations > MAKER: prepares the analysis, shows the artifact > SKEPTIC: checks MAKER against the checklist, lists what failed > RUNNER: only executes approved work. asks before every trade one agent. one memory. four narrow roles. the seat switches, the context stays the main rule: a chain never runs more than 5 steps. after step 5 the SKEPTIC runs a checkpoint and waits for PASS > top-5 holders control more than 50%? HOLD > dev wallet sold? HOLD > contract with freeze or mint authority? HOLD > any claim without a link to the source? HOLD in an environment where 98.6% is scams, the seat that looks for problems matters more than the seat that looks for opportunities full guide, prompts, permission ladder, checkpoint: article below
这条是引用着另一条写的:x.com/leanxbt/status/2106055029207568824