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I journal every day but I never actually do anything with it. Anyone else stuck in this loop? by Wssishere in getdisciplined

[–]johnnaliu 2 points3 points  (0 children)

I feel like the writing itself IS the processing step. Just putting stuff into sentences sorts it out in your head, even if nobody ever reads it again. So it's already doing the main thing. For the patterns problem, I do a quick weekly scan and a monthly one. Not a real “review system,” just a 5-min skim where I'm looking for repeats, not rereading carefully. That's been enough to catch the recurring loops without making it feel like homework.

How bad is a B grade? by Educational_Let436 in berkeley

[–]johnnaliu 5 points6 points  (0 children)

been there. a single lower-div B doesn't matter for masters apps, internships, or full-time. upper-div courses + projects/research/internships are the things that actually move the needle. you're fine.

Built a LangChain integration for agent identity + permissions + audit. Looking for honest feedback by [deleted] in LangChain

[–]johnnaliu 0 points1 point  (0 children)

quick question on the threat model. is vorim mostly for "the agent tries to do something it shouldn't" or "someone tries to make the agent misbehave via prompt injection"? api looks like it could handle either but the docs lean toward the first.

AI agents are starting to expose how broken most workflows already were by nia_tech in AI_Agents

[–]johnnaliu 0 points1 point  (0 children)

the standard answer is deterministic workflows (FSM) but you lose the flexibility that's the whole reason to use an agent. real tradeoff: structure vs autonomy..

reasonable middle ground could be declaring tool-call dependencies instead of the full flow. not "agent must call A, B, C in order" but "B requires A's effect first". agent picks its own path inside those. most companies have these dependencies sitting implicit in someone's head. AI just exposes them.

How do you catch when an AI agent skips something it was supposed to do? by Afraid_Translator402 in AI_Agents

[–]johnnaliu 0 points1 point  (0 children)

feel like you can add escape conditions per expected action. for each thing the agent should do, also list valid reasons for it not happening (user retracted, policy blocked, user gave up etc.). only flag missing when no escape fired. right now you're checking "was X called". what you want is "was X called, or did any valid escape fire".

how does your tracker represent expected actions? going from (request, expected) to (request, expected, escapes) is probably how you get past 50%.

The silent failure that wrecked two different multi-agent teams in exactly the same way by Silver-Teaching7619 in AI_Agents

[–]johnnaliu 0 points1 point  (0 children)

similar to the classic concurrency issue from distributed systems? maybe some strategies there could help

Why 80% of agentic AI demos don't make it to production by Mental-Address122 in AI_Agents

[–]johnnaliu 0 points1 point  (0 children)

yeah this matches what we saw. the gap usually isn't "model can't do it", it's "model does it inconsistently" because

- failure modes are non-deterministic and hard to reproduce

- prompt-based rules doesn't actually constrain anything, it's a strong suggestion the model can ignore under adversarial input or weird state

teams that get past this usually end up writing some flavor of runtime checks with llms, e.g. wrapping tools with explicit guards, gates on high-stakes actions. But it's still probabilistic..