BloodAndCode (u/BloodAndCode)

BloodAndCode commented on Show HN: Free audiobooks with synchronized text for language learning discovox.org/en/library... · Posted by u/floo

floo · 10 hours ago

thanks! none of the audio is AI generated, it's all human narration, mostly sourced from librivox. (credits show when clicking the info icon)

the idea of learning languages from AI didn't quite sit right with me. but that might be something to circle back to.

integrating learner dictionaries does sound like a fantastic idea. will definitely explore that!

BloodAndCode · 7 hours ago

ah that actually makes a lot of sense. human narration is probably better for learners anyway — pronunciation and rhythm matter a lot when you're trying to internalize a language. and good to hear the dictionary idea resonates. even simple definitions or example sentences can make a big difference when reading along.

really nice project overall.

BloodAndCode commented on Show HN: Run an Agent Council of LLMs that debate and synthesize answers github.com/JitseLambricht... · Posted by u/JitseLambrichts

BloodAndCode · 7 hours ago

this is a really interesting direction. i've been experimenting with “self-critique” style pipelines (plan → solve → critique) and they often help smaller models punch above their weight. the agent council idea is also appealing, although the cost/latency trade-off usually becomes the tricky part when multiple models run in parallel.

curious how often the judge actually disagrees with the first candidate answer in practice. does the council mostly refine reasoning, or does it sometimes lead to completely different conclusions?

BloodAndCode commented on Show HN: I built a tool that watches webpages and exposes changes as RSS sitespy.app... · Posted by u/vkuprin

vkuprin · 11 hours ago

Yeah, semantic anchors are definitely the right direction — [data-testid], aria-label, or text proximity tend to survive rebuilds much better than class paths. The picker leans towards CSS right now but that's something I want to improve.

The harder problem is auth-gated content — Instagram feeds, dashboards, paywalled pages. Browser Steps handles it today (you can script login flows), but honestly I think the real fix is AI-assisted interaction. A small cheap model that can find what you care about without needing a brittle selector at all. That's where I want to take this — less "maintain a CSS path", more "here's what I'm interested in, figure it out...

BloodAndCode · 11 hours ago

that direction makes a lot of sense. selectors always end up turning into maintenance work sooner or later.

the idea of a small model just identifying “the thing that looks like a price / status / headline” feels much closer to semantic detection than DOM-path tracking

curious though — would you run that model on every check, or only when the selector fails? seems like a nice hybrid approach to keep things cheap.

BloodAndCode commented on Show HN: I built a tool that watches webpages and exposes changes as RSS sitespy.app... · Posted by u/vkuprin

vkuprin · 11 hours ago

The selector is stored as a CSS path and matched against the fetched HTML on each check — so as long as the element's structure and nesting stay roughly the same, minor layout changes don't usually break it.

The fragile cases are sites that generate class names on every build (React/webpack/vite apps often do this) — those selectors will just stop working.

For semantic elements like price tags, availability text, or content blocks, they tend to be stable enough that it's not a real problem day-to-day. And if a filter stops matching entirely, the watch flags with error message it rather than silently giving you empty diffs.

BloodAndCode · 11 hours ago

that makes sense. the error flagging is a nice touch — silent failures are usually the worst part of these tools. i've also run into the “random class name” problem on a lot of modern frontends. have you experimented with more semantic selectors (text anchors, attributes, etc) as a fallback, or do you try to keep it simple on purpose?

BloodAndCode commented on Show HN: Free audiobooks with synchronized text for language learning discovox.org/en/library... · Posted by u/floo

BloodAndCode · 11 hours ago

really nice idea. i like the “read along” concept a lot — being able to replay the same word or sentence multiple times is super helpful when learning a language.

am i right that the narration is generated with AI? sometimes there might be small pronunciation quirks, but overall the quality already sounds pretty good from what i tried.

one thing that would make this even more useful for learning (at least for me) is word-level explanations. for example clicking a word and seeing a simple definition in the same language (like german → german explanations in learner dictionaries), not just translation. that really helps build intuition.

BloodAndCode commented on Show HN: I built a tool that watches webpages and exposes changes as RSS sitespy.app... · Posted by u/vkuprin

BloodAndCode · 11 hours ago

i've actually been looking for something like this. full-page change monitors get noisy really fast, especially on sites with lots of small UI changes.

being able to watch a specific element sounds way more useful in practice (price blocks, availability text, etc).

curious how fragile the element tracking is though. if the site slightly changes the DOM structure or class names, does the watcher usually survive or do you end up reselecting the element pretty often?

BloodAndCode commented on Show HN: VS Code Agent Kanban: Task Management for the AI-Assisted Developer appsoftware.com/blog/intr... · Posted by u/gbro3n

BloodAndCode · a day ago

ngl this actually makes a lot of sense. i've been running into the same “context rot” problem with copilot / claude sessions… you spend like an hour discussing architecture with the agent and a few days later the whole reasoning is basically gone. starting from scratch again... the idea of keeping the planning conversation as plain markdown in the repo is kinda neat. boring in a good way. no database, no hidden state, just files you can diff and commit. feels very git-native. also like the plan → todo → implement separation. forcing the agent to write the plan first probably saves a lot of token-wasting thrashing. curious though — how messy do those task md files get after a while? i can imagine long agent conversations turning them into pretty big logs.

BloodAndCode commented on Show HN: How I topped the HuggingFace open LLM leaderboard on two gaming GPUs dnhkng.github.io/posts/ry... · Posted by u/dnhkng

BloodAndCode · 2 days ago

Did you try repeating the same mid-layer block more than once?

If the gain comes from giving the model another pass over its internal representation, I'd expect some sort of diminishing-returns curve as you add more repeats. But if those layers form a spevific circuit, running it multiple times might actually break the computation.

It would be really interesting to see which of those regims the model falls into.