u/AriaSmith19

Honestly, when I was bra shopping for breastfeeding, I thought higher price = better quality. Nope. Learned that the hard way.After trying a few, here are 4 things that actually matter:1. Fabric stretchYour chest size can go up two cup sizes from pregnancy to nursing. So you need fabric that stretches well — think nylon + spandex with at least 100% stretch.I ended up liking Momcozy’s seamless Lycra fabric. It stretches about 1.5x without feeling like a torture device.2. One-hand buckleMiddle-of-the-night feeding with a crying baby? You’re not using two hands. The buckle needs to click into place clearly and smoothly, no pinching.Snap buttons work, but magnetic buckles feel way smoother — just pricier.3. Support that doesn’t hurtYour boobs get heavier when nursing. Rigid steel rings? Big no. Soft steel rings or gel strips are way safer and put less pressure on milk ducts.Also, those regular sponge pads? They warp fast. Not worth it.4. Breathability / sweat-wickingNursing makes you sweaty. Nylon or modal is great. Avoid pure cotton — it soaks up sweat but doesn’t dry. Gross.Look for a moisture vapor transmission rate above 800 g/m²/24h if you wanna get technical.Next time you’re bra shopping, just keep these in mind. Hope it helps!

I’m noticing a pretty annoying gap in my Norwegian. Bokmål reading is slowly improving, and I can recognize grammar when I see it, but saying even boring sentences out loud still feels fake. Like I know “jeg dro på butikken i går” is simple, but if I have to produce it quickly my brain starts translating word by word.

I live somewhere with basically zero Norwegian speakers nearby, so I’ve been trying to separate recognition practice from actual speaking practice. Anki helps me retrieve words, Duolingo/Babbel are fine for light structure, and Pimsleur or shadowing NRK clips/podcasts helps my mouth get used to the rhythm. But shadowing doesn’t train answering. Self-talk is private, but there’s no correction. italki is probably best for nuance, especially sounding less stiff, but I can’t schedule/pay for it constantly.

So my current small hack is: while making coffee or walking around the kitchen, I do 5 minutes of shadowing, then 5-10 minutes answering questions out loud. I’ve also been using Issen for 10 minutes of low-pressure speaking because there are no Norwegian speakers near me. Sometimes I use a random prompt, like summarizing this NPR piece in simple Norwegian:

https://www.npr.org/2026/05/11/nx-s1-5816161/will-sharpe-white-lotus-amadeus-mozart

The “research” part is not fancy, but the passive vs active vocabulary idea matches my experience: I recognize words days or weeks before I can actually use them naturally. My next problem is sounding less textbook-ish, especially little things like “da/a”, “ass”, and dialect exposure.

Do other people here deliberately split recognition practice and speaking practice? What has helped you sound more natural and less like you’re reading from a course dialogue?

So, I was pretty excited when I got my hands on one of those automated vacuums that everyone’s been hyping. The idea was simple: no more lugging out my old, heavy vacuum every time I need to clean. I set the thing up, programmed it, and let it do its magic while I got on with life. But after a few days of use, I’m not so sure anymore.

My floors look clean, but when I really pay attention, I find myself still sweeping up spots the robot missed. There’s dust in the corners, crumbs under the table, and the occasional hair strand hanging out. What’s the deal? I’m running this thing every day, hoping it’ll cut down on the need for manual vacuuming, but I feel like I’m just chasing the same clean spots over and over again. I mean, is this what I’m stuck with? A robot that just does the bare minimum?

I thought this would free up so much time for me, but now I’m spending just as much time dealing with missed spots as I was vacuuming manually. I still end up pulling out my old vacuum to finish the job after it’s done, and it’s just not working as I expected. Anyone else have the same experience? What am I doing wrong here? Should I just give up on the idea of completely automated cleaning?

for years i kept adding more stuff to my desk thinking it would make recording feel more "pro" but honestly half the time i just wanna turn on pc and record without routing nightmarebeen using this little BOYA caster x1 thing lately with a dynamic mic and its kinda nice for quick vocals / scratch ideas / youtube audio without opening 40 plugins firststill use bigger interface for actual sessions obviously but the simpler setup weirdly makes me record more oftenmaybe im just getting lazy with age idk

Lately I’ve been trying to repurpose webinar content into short-form videos, but I keep running into the same issue.Even when the original material is actually solid and shows real expertise in the topic, once I turn it into Shorts it just ends up feeling kind of flat and lifeless.I think a big part of the problem is that my current editing approach is pretty limited. I’m keeping the important parts of the content, but visually there’s not much going on. No real motion, no changes in pacing, nothing on screen that really helps hold attention.Because of that, I’m starting to feel like the editing style might actually matter more than which exact clips I choose.Curious how others are handling this kind of workflow these days. Are there any tools out there that actually help automate or improve this process, or is it still mostly manual work at this point?

idk if I’m overthinking this but I went down a rabbit hole with transcription tools recently and now I feel a bit weird about the whole thinglike before I never really questioned ityou upload audio → get text → doneand most of these tools say stuff like “encrypted” so I just assumed it’s all finebut then I randomly started reading some of the terms (not even that carefully) and started noticing the same kind of wording over and overthings like “used to improve the service” or “may be used for training” etcand yeah maybe it’s anonymized or whatever, but it still kinda changes how it feels when you’re uploading real conversationsespecially if it’s not just random audiolike calls, meetings, anything even slightly sensitiveI tried running stuff locally for a bit (Whisper and similar)it works, just slower and a bit annoying to set upbut at least you know where your data is going (or not going)then I went back to looking at cloud tools again but now I’m way more paranoid about what they actually say vs what they advertiseI stumbled across one called Vocova that seems to lean more on not using your data for training, but I haven’t used it enough to say anything definitivejust noticed the difference in how they talk about itanyway I’m probably late to this but curious what other people dodo you just not think about it and use whatever’s convenientor are you actually checking this stuff / running things locally?

One of the things that took me a while to appreciate about the TuyaOpen agent framework is how the tool system actually works in practice on Linux.On a microcontroller, MCP tools are things like "set the volume" or "take a photo" — hardware actions. On a Raspberry Pi running Linux, the tool surface is much larger.The VirtuaMate project ships with tools for file operations (read, write, edit, list directory, find path), time and scheduling (get current time, add/list/remove cron jobs), Linux shell execution (tool_exec), and PC collaboration over a gateway. The agent decides when to call these based on what you ask.In practice: you can ask the assistant to check what's in a directory, edit a config file, set a reminder that fires at a specific time, or run a shell command — and it does it, because those are registered tools the LLM knows about. There's no custom intent matching or routing logic. The model sees the tool list and picks the right one.The memory system is file-based: long-term memory in MEMORY.md, daily notes in timestamped markdown files. The agent reads and writes these directly using the file tools. Over time, context accumulates in files rather than in a context window.What I find most interesting about this design: adding a new tool means writing a function and registering it in tools_register.c. There's no middleware to configure. If you want the agent to control something new — a GPIO pin, a camera, a sensor reading — you write the handler and describe it in English for the LLM.Has anyone tried adding custom tools to this kind of framework on Pi? I'm thinking about camera integration specifically — whether it's better to implement it as an MCP tool that returns a file path, or as something that returns raw data directly to the model.Repo: https://github.com/tuya/VirtuaMate