26:T500,A couple months ago, I found that a) visual image watermarking is trivially defeated by AI image editing so invisible image watermarks are likely the future and b) the only steganographic image watermarking tools are hard-to-use open-source tools or proprietary tools like SynthID. So as an experiment I tried using agents to create a novel image watermarking approach…and it unexpectedly worked: mostly imperceptible, tamper resistant, higher capacity, doesn't use a neural network, and real time encode/decode.

I want to open-source it as there are very many legitimate uses for image watermarking. However, as of late there has been a lot of discourse about image watermarking on both sides, namely a) invisible image watermarks can be used to faciliate dystopian user tracking (https://news.ycombinator.com/item?id=48198291 ) and b) tools to strip AI image watermarks are unethical/antisocial (https://news.ycombinator.com/item?id=48200569), so overall I'm confused on the ethics of working with watermarking tools and I am concerned there could be a negative externality I am missing by making it more causally accessible. At the least, having only closed-sourced options for image watermarking isn't a good outcome.27:T470,I’m trying to understand how teams actually debug production issues in systems made up of multiple services and external integrations (e.g. Stripe, Twilio, internal microservices, queues, webhooks, etc.).

In practice, when something breaks, it seems like the workflow is usually:

an alert fires (Datadog/Sentry/CloudWatch/etc.)

or a customer complains

engineers then start checking logs, traces, dashboards across multiple systems

and eventually manually reconstruct what happened across services

What I’m curious about:

How do you actually trace a single failed request or transaction across multiple services today?

What tools do you rely on most in practice (not in theory)?

Where does it usually break down — logs, tracing, instrumentation, or just missing context?

How long does it typically take to go from “something is wrong” → “we know exactly why it broke”?

What part of this is still mostly manual stitching together of information?

Trying to understand what the real pain points are in practice, especially in systems with lots of external integrations and async flows.

If LLMs Have Human-Like Attributes, Then So Does Age of Empires II