u/Physical-Neat-5211

I cook rice and beans probably four times a week. Pasta with whatever vegetables are about to turn the other days. It works but everything ends up tasting the same and I got tired of it.

Recently started picking up random condiments when I spotted them cheap, grabbed gochujang, chili crisp, MSG, tahini, sesame oil from different sale events on tiktok over a few weeks. Most had a decent price cut and they're still half full months later because a little goes a long way.

So far what's been working for me:

Gochujang: chicken thighs in the oven with gochujang, soy sauce, bit of honey. Also mix a small spoon into cream cheese for bread when I'm too lazy to cook.

Chili crisp: fried egg topping every morning. Goes on buttered toast, instant noodles, leftover rice fried up with whatever is in the fridge.

MSG: tiny pinch in soup, pasta sauce, any stir fry. Makes everything taste like you tried harder than you did.

Tahini: thin it out with lemon juice and water, drizzle over roasted vegetables or use as a lazy salad dressing with a bit of mustard.

These completely changed how I feel about cooking the same cheap ingredients every week. What are yours? Looking for more stuff that punches above its price.

I was setting up a small model comparison in DeepSeek Harness when the preset selector suddenly stopped cooperating. Once the session had messages in it, the Web UI would not let me switch presets. I assumed I had hit an unfinished bit of the interface. I was already looking for a config-file workaround when I stopped and checked what the selector actually changes.

It turns out a preset is not just a label sitting above the model. It can change the tools, approval rules, system prompt, and agent loop. Switching that halfway through a conversation would leave the old tool calls in the transcript while a different runtime tried to carry on from them. The chat would look like one continuous test even though I had changed the test rig under the table. That is a bad setup for comparing models.

My experiment is much less ambitious. I only want to swap the model and leave the agent alone. An OpenAI-compatible API keeps the request shape steady, but that is not enough by itself. I still need the same prompt, tool schema, preset, sampling settings, and context limit. I also want two receipts after every run: the Harness trace should show the route I selected, and the gateway log should show which model and upstream provider handled it.

Harness accepts custom OpenAI-compatible providers, so for this test I can point it at ZenMux without waiting for a native integration. That gives me one API for multiple AI models, and I can start a fresh session for each configured model ID. After a run, I can put the Harness trace beside the gateway log and check that the route I asked for is the route that actually handled the request. The model can change. The rest of my test rig should stay boring.

Harness is still a developer preview, so this behavior may change. For now my rule is simple: same starting prompt, fresh session for every model route, and no preset changes mid-run. If I need a different preset, I will fork the session and call it a new experiment. That means a few extra tabs. Fine. Extra tabs are cheaper than discovering that half my runs used a different agent.

I used to think one label printer should handle everything. On my workbench, I ended up keeping two because shipping labels and workspace labels have very different jobs. My 4 x 6 direct thermal printer stays loaded with shipping stock, while I use a Niimbot M2 for thermal transfer labels that stay around the workspace. Size decides a few jobs, but where the label ends up matters more.

Anything that leaves with an order goes through the direct thermal printer. It is already connected to my shipping setup and has the right stock loaded, so there is nothing to change in the middle of packing. For my bench, that is the convenient and less expensive choice for a shipping label that only needs to travel with one parcel.

Drawer labels and reference tags are different. They stay in the workspace, get handled repeatedly, and may be there for a long time. I put those on the M2 because thermal transfer makes more sense to me for a label I expect to keep reading. Once the wording is settled, I would rather make one workspace label I plan to leave in place than treat it like another piece of temporary packing paperwork.

I also wait until the information has stopped changing. A shelf position I am still testing gets a handwritten note for a while. If the drawer name or reference wording becomes part of my normal setup, I print the final version on the M2. I still choose the label stock and adhesive for the surface, but that is a separate decision from which printer handles the job.

I still hesitate over project references that start as temporary and remain on the shelf months later. I leave the handwritten note alone while the project has an end date. If the reference quietly becomes part of the workspace, I replace the note with an M2 label. I still change my mind on those borderline jobs, but shipping and established workspace labels no longer compete for the same printer.