laalshaitaan

4 ms·

1.
by laalshaitaan 3mo ago
ai slop again
2.
by laalshaitaan 3mo ago
that on the customer's side to redact the PII as you are the ones sending it and you'd know better than us
3.
by laalshaitaan 3mo ago
i get the push, most teams come to us after they've done/tired of the claude running analysis thing manually and want a pro-active thing. we're also targeting conversation first use cases and for them this serves as their eve
4.
by laalshaitaan 3mo ago
its fascinating how the toyota example comes up anywhere, its so good! wdym by modelling the messages and conversations though? i lose you a bit there! for the crm approach, i do think it'll be a problem at some point right now. the re
5.
by laalshaitaan 3mo ago
a lot of our customers want a daily morning report on slack & flag things instantly rather than to wait for a week so thats why we keep it realtime
6.
by laalshaitaan 3mo ago
it gets hard when you need this continuously across lots of chats/calls, with metadata, changing clusters, going deeper into a user journey, etc. the LLM call is just one part of it lol we're keeping it useful every week, finding
7.
by laalshaitaan 3mo ago
i agree w you for smaller teams tbh. if you have a few hundred convos and someone can maintain scripts/prompts, hand-rolling is probably fine. it becomes less tiny when it’s 10k+ msgs/week, long voice calls, metadata, changing clu
8.
by laalshaitaan 3mo ago
im hearing this for the first time and damn! i just told this to my cofounder/cto and he said hes gonna give this a shot in the coming days. damn, i read bayesian in statistics like years ago, never thought itll come back this way
9.
by laalshaitaan 3mo ago
seems ai slop
10.
by laalshaitaan 3mo ago
oh gotcha, yeah happy to chat more! yeah DMing
11.
by laalshaitaan 3mo ago
i love this comment bec we started as analytics for mcp servers haha! we then expanded to conversations bec thats where most mcp servers were being used lol. we havnt figured out yet how to do the b2b2b kinda thing where we surface insights
12.
by laalshaitaan 3mo ago
i like these kinds of critiques, we don’t think conversation logs or analysis on top of it is alone enough to replace observability or evals. imo they answer diff questions for diff use-cases. we're betting that there is a TONNN of pro
13.
by laalshaitaan 3mo ago
yea, at our volume which we still consider small as we've been able to figure out a way with llms & embeddings, its still fine. + we onboarded a voice ai company with more than 2 hour calls and thats when it was super hard to solve
14.
by laalshaitaan 3mo ago
okay nice, also is it safe to assume you do once a fortnight releases then? like look at the last week's data then use it for product decisions the coming week? also have you updated/made any changes to this skill that has improve
15.
by laalshaitaan 3mo ago
oh damn, can you share what the skill is actually doing for you like on a daily basis: is it creating clusters, scoring known issues, or finding new patterns? and what data points are you giving it to if any w the messages? usually a bounda
16.
by laalshaitaan 3mo ago
on a satirical note: we also have an mcp server/api endpoint if you dont want the ui
17.
by laalshaitaan 3mo ago
we're still learning and so our the prompts haha, whats your take though
18.
by laalshaitaan 3mo ago
lol i wish it was just wrapping prompts but things got harder once our customers grew bigger, we had to build queues. we had to do context management for bigger conversations and bunch of metadata fields started coming in per customer.
19.
by laalshaitaan 3mo ago
lol true but then you’re just building another us :D
20.
by laalshaitaan 3mo ago
codex is great for like a one-time/overview analysis on a handful of transcripts. we usually serve to companies where the volume is >10k messages & continuous ingestions + with claude/codex it messed up this + metadata link
21.
by laalshaitaan 3mo ago
haha yea, i even got the domain rageprompt dot com like a couple of days ago lol i love the name too. for profanity, did you define keywords or just let the agent figure out rage stuff? how many rounds did you set for the hermes? claude doe
22.
by laalshaitaan 3mo ago
I’m gonna try and give this to my cloud agents and get a benchmark now lol
23.
Launch HN: Agnost AI (YC S26) – Extract user feedback from agent conversations(agnost.ai)
85 points by laalshaitaan 3mo ago|52 comments
24.
by laalshaitaan 3mo ago
lessgooo! context dev ftw!
25.
by laalshaitaan 3mo ago
If that's the case, how does one make them smarter for their specific use case? I'd like to believe that vast knowledge is still more than what I have in my mind?
26.
Ask HN: Why are we humans still prompting to make Agents better?
2 points by laalshaitaan 3mo ago|3 comments
27.
by laalshaitaan 6mo ago
The debugging part at this scale is harder than you would expect - behavioral drift between parallel agent instances is nearly invisible without something aggregating what they are actually doing across runs. We hit this ourselves: two agen
28.
by laalshaitaan 6mo ago
I think one of the very few who actually support ebpf & xdp, which you do need when you're building low level stuff. + the bare metal setup is like out of the world lol.
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by laalshaitaan 6mo ago
Runtime policies as an actual gate rather than prompt instructions is the right model. Most frameworks just bolt governance on as a wrapper and hope the model obeys. What I'd want on top of this: observability into why agents are hitti
30.
by laalshaitaan 6mo ago
The oracle problem is tractable when the output is code: you can compile it, run tests, diff the output. For conversational AI it's much harder. We've seen teams use LLM-as-judge as their validation layer and it works until the ju

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