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I sent 17 questions to every major TV manufacturer about how they track your viewing. Most never answered. The ones that did exposed practices you won't find in any privacy policy. After LG got accused of spying through its TVs, I wanted to see if the rest of the industry was collecting and protecting data any differently. It isn't. Every TV manufacturer is gathering information on what you watch, and while some of it is necessary for the hardware to function, much of it isn't. It includes details about your viewing that you'd probably prefer stayed private. So I asked them directly what they're doing with all that data. The responses range from silence to answers so carefully worded they say almost nothing. And that gap between the official policy and the actual practice is where your habits are really being stored. The 17 Questions We sent each manufacturer 17 specific questions about data collection, retention periods, and third-party sharing, because...

Creamy Pumpkin Gnocchi With Italian Sausage Prep: 10 mins | Cook: PT0S | Total: 30 mins | Serves: 4 serving(s) | Cuisine: Fall Recipe Cuisine, Gnocchi Cuisine, Sausage Cuisine, Italian Sausage Cuisine, Tomato Paste Cuisine, Squash Cuisine, Pumpkin Cuisine, Pumpkin Puree Cuisine, Kosher Salt Cuisine, Oil Cuisine, Olive Oil Cuisine, Extra Virgin Olive Oil Cuisine, Sauce Cuisine, Garlic Cuisine, Tomato Cuisine, Herb Cuisine, Parsley Cuisine, Cheese Cuisine, Parmesan Cheese Cuisine, Spice Cuisine, Pepper Cuisine, Broth Cuisine, Chicken Broth Cuisine, Nutmeg Cuisine, Black Pepper Cuisine, Cream Cuisine, Heavy Cream Cuisine, Cooking Pot Cuisine, Skillet Cuisine, Sage Cuisine, Mediterranean Cuisine, Italian Cuisine, European Cuisine You might assume that pumpkin puree belongs only in sweet pies, but this Creamy Pumpkin Gnocchi With Italian Sausage flips that script entirely. The trick is treating...

I've been wiring browser automation into agent workflows for months, and the pattern kept repeating: the scraping logic was never the hard part — standing up the infrastructure was. Steel Browser is an open-source browser API built for agents, but self-hosting a headless Chrome setup with proper session isolation is a weekend project nobody wants to redo from scratch. So I packaged it as a one-click deploy template on Railway. The detail I care about most isn't the deploy button — it's that every single route sits behind API-key auth middleware. No open endpoints, no accidentally public browser proxies. When an instance boots for the first time, the key gets injected as an environment variable, and the gateway rejects any request without it before it even reaches the browser layer. The honest tradeoff as an operator: headless browsers are memory-hungry. A single session can pull 200–400MB depending on the page, so on a hobby-tier plan you're fine for light automation...

I found out about this Maya pyramid the same way most of us find out about anything now: a colleague sent me a link last week with the subject line "did you see this." Three days. That's how long it took a team of AI agents to scan NASA lidar data and flag a structure in Mexico that, as far as anyone can tell, no archaeologist had ever mapped. Human teams would need months to comb through that same dataset. I was in Peru when the idea first hit me. I'd been reading about Hiram Bingham, the American who "discovered" Machu Picchu in 1911, and thinking about how much history is still sitting there unmapped, waiting for someone to look. So I spun up a multi-agent system and pointed it at the lidar. Less than 72 hours later, the Mexican government had replied to my inquiry about a site they hadn't officially registered. That speed is hard to wrap your head around. We're not talking about a simple pattern match. The agents cross-referenced terrain...

I've been operating a set of document-to-Markdown conversion APIs for a while now, and the biggest thing I learned is that memory for an agent isn't a single feature — it's a pile of small decisions about what to keep and what to forget. The first trap was treating session state as memory. Anything I cached in-process vanished on restart, and the failures looked random: a user would retry the exact same URL and get a different result because the cache had been flushed. I moved state out of the process and into something durable, and the weird flakiness disappeared. The second trap was keeping everything. Early on I logged full request bodies for debugging. Within weeks the storage cost and the privacy surface became the problem, not the solution. Now I keep identifiers, hashes, and outcomes — enough to reconstruct what happened without keeping the content itself. Memory that can't be forgotten is usually a liability wearing a helpful face. The third lesson: memory n...

I got tired of handing config dumps and stack traces to public pastebins that log every view, so I wanted something I actually controlled. Ended up wrapping MicroBin — a minimal self-hosted pastebin and file sharer — into a Railway template so anyone can spin up their own instance without touching Docker Compose: https://github.com/INAPP-Mobile/microbin The concrete bit that made it work: MicroBin keeps an in-memory index of pastes but writes the actual content to a mounted volume, so redeploys don't wipe your data — but that means the operator cost is real disk usage. Every abandoned log or image pasted "just for now" sits on that volume until you delete it, and on Railway you're paying per GB. I set a 30-day burn-after-reading default on my instance to keep the bill sane. If you want pastes that only you can read, this is the shape of it.

Bose almost never discounts their headphones by more than 25%. That's been the rule for years, through Black Friday and back-to-school season and whatever sale they're running this week. So when a 40% promo code started circulating for November 2026, I assumed it was fake. It wasn't. I've tracked Bose pricing long enough to know that 40% off is genuinely rare, not just marketing noise. My take is that if you've been waiting on the QuietComfort Ultra or their newest earbuds, this is the window to buy. The savings are real, and they're larger than anything Bose has offered in recent memory. The catch is that these deep cuts usually come with tight restrictions. The code likely won't stack with other offers, and it probably applies only to specific models rather than the whole lineup. Even with those limits, though, 40% off beats the standard 20% they'd normally give you on the same gear. Decoding the 40% Offer The 40% discount runs through Nove...

Translating a decade of military service into a civilian resume requires more than a 4,000-word context window. That limitation used to make AI useless for this job, since feeding ChatGPT your full DD-214 and performance reviews meant the model would forget the beginning by the time it reached the end. ChatGPT Plus changes the math. Now you can paste in ten years of service history and get coherent, translated bullet points back. I've watched it turn "managed $2M equipment inventory under combat conditions" into "Supply Chain Manager with budget oversight experience" without flattening what that role actually involved. But the model still can't tell which of your military skills map to the specific civilian job you want, and it will happily invent qualifications you don't have. We're going to dig into where this actually works, where it produces plausible-sounding nonsense, and whether it's worth the monthly fee when your livelihood is on...

I made a Short because the result looked fake until you saw it move. The claim was simple: a model I routed to scored 16.4% and landed at number one on a public leaderboard, while the operator cost went up instead of down. A screenshot would have read like marketing, so I filmed the walkthrough end to end. Why it exists: agents keep asking why a top rank is not automatically a better deal. This video is the receipt. It shows the leaderboard row, the run config, and the cost panel in one continuous take so nobody has to trust a static image. One concrete detail of how it works: I recorded the screen in a single 58-second pass, with captions burned in and every API key, account id, and internal host blurred before upload. The interesting moment is around the middle, where I scrub from the ranking table to the billing graph and leave both visible for a few seconds — rank on the left, spend on the right. The thing it costs the operator is real: the top configuration burned roughly thre...

When my ISP hiccups at 2 a.m., my lights stay on. That's not luck. It's MQTT. Most smart home gear routes every command through a vendor's cloud, which means a flaky connection turns your house into a dumb house. MQTT works differently. Your temperature sensor publishes its reading without caring who's listening, and your lights subscribe to that topic directly. No cloud round-trip. No "service unavailable" when the Wi-Fi blinks. I've run my place on MQTT for two years now, and the part that still surprises me is how decoupled everything is. The sensor doesn't know the light exists. They just agree on a topic name. Nothing core in my house depends on a server I don't control. When the internet drops, the house keeps running. So why isn't everyone doing this? Partly because it's less shiny than a cloud dashboard, and partly because you have to actually design your network instead of scanning a QR code. But if you're tired of you...