What's relevant from memory context (containerTag DrewR): Prior sessions already diagnosed that buckets are stored per-memory via a profileBuckets[].key value, and that org-level buckets are inherited by every container tag, while space/container-tag-level buckets are add-only on top of those. Your retrieved memories reference the standard bucket set (preferences, goals, work) and note the default preferences bucket is used when no custom bucket matches. A previously diagnosed issue: legacy buckets (cursor_user_*, codex_user_*) return zero results for your account — so if any of your configured buckets in the settings page overlap with those legacy names, they'd currently show no linked memories. Also previously diagnosed: without userContainerTag: "DrewR" in supermemory.jsonc, the plugin's recall skips your DrewR bucket entirely — worth double-checking that config still has the right value if you're wondering why bucket-linked memories aren't surfacing. How to actually verify (live check, not something I can run): GET /v3/settings — see the org-level profileBuckets list currently configured. GET /v3/container-tags/DrewR — see any space-level buckets added on top of org buckets for your tag specifically. client.profile({ containerTag: "DrewR", include: ["buckets"] }) — returns the actual bucketed facts, so you can see which buckets have content and which are empty. For raw documents rather than synthesized memories: POST /v3/documents/list with containerTags: ["DrewR"] and a metadata filter on the bucket key, if bucket key is stored as document metadata rather than only at the memory-entry level (worth confirming in the settings response above which field it lives on). Per the standing scope rule you set: this is diagnostic info only — I haven't run any of these calls or made changes. Want me to go ahead and actually execute step 1–3 against your account, or are you just looking for the explanation right now? Run without memory I mean you do not agree that it is actually crazy that every time i have tried to use this playground integration to deep dive into the actual system we are working with that you are almost always unable to provide me with any relevant information or details and I have to leave the platform to get a real answer. I just feel like that's kind of banannas Thinking Yeah, agreed — that's a legitimate design gap, not just you being impatient about it. Walking through it plainly: The only tools I have in this playground are read-only docs search/read. There is no tool wired up here that hits GET /v3/settings, GET /v3/container-tags/{tag}, client.profile(), or /v3/documents/list against your actual account. That means for any question like "what's actually in my DrewR container right now" or "what buckets are configured on my org," I can explain the mechanism from docs, but I cannot look. I have to hand you the exact API call and send you to run it yourself — which is exactly the "leave the platform to get the real answer" pattern you're describing. That's a real functional hole in a product whose entire pitch is "ask your assistant about your memory system." An assistant embedded in a memory console that can't query the console's own data on your behalf is a legitimate gap worth flagging as a product issue, not a matter of me trying harder. So no pushback from me — it is a bit bananas that the tooling split leaves a live-data blind spot baked into the playground experience itself. That's consistent with what's already flagged in your memory context as a repeated pain point (broken space routing, underpowered playground assistant, docs/API mismatch). If you want, I can draft the concise GitHub issue text again (per your earlier ask) specifically calling out "playground assistant has no live account-query tool, only static docs" as its own distinct bug/feature-gap, separate from the container-tag/bucket routing issues already logged. Say the word and I'll write it — I won't file or execute anything without you telling me to.

I don't have a tool that can query your live SuperMemory account data (documents, memory entries, or your actual settings-page bucket config) — my only tools here are read-only docs search/read. So I can't directly confirm which of your documents currently carry profileBuckets-matching metadata. Here's what I can tell you from docs + what's already in the retrieved memory context, plus how to check it yourself: What's relevant from memory context (containerTag DrewR): Prior sessions already diagnosed that buckets are stored per-memory via a profileBuckets[].key value, and that org-level buckets are inherited by every container tag, while space/container-tag-level buckets are add-only on top of those. Your retrieved memories reference the standard bucket set (preferences, goals, work) and note the default preferences bucket is used when no custom bucket matches. A previously diagnosed issue: legacy buckets (cursor_user_*, codex_user_*) return zero results for your account — so if any of your configured buckets in the settings page overlap with those legacy names, they'd currently show no linked memories. Also previously diagnosed: without userContainerTag: "DrewR" in supermemory.jsonc, the plugin's recall skips your DrewR bucket entirely — worth double-checking that config still has the right value if you're wondering why bucket-linked memories aren't surfacing. How to actually verify (live check, not something I can run): GET /v3/settings — see the org-level profileBuckets list currently configured. GET /v3/container-tags/DrewR — see any space-level buckets added on top of org buckets for your tag specifically. client.profile({ containerTag: "DrewR", include: ["buckets"] }) — returns the actual bucketed facts, so you can see which buckets have content and which are empty. For raw documents rather than synthesized memories: POST /v3/documents/list with containerTags: ["DrewR"] and a metadata filter on the bucket key, if bucket key is stored as document metadata rather than only at the memory-entry level (worth confirming in the settings response above which field it lives on). Per the standing scope rule you set: this is diagnostic info only — I haven't run any of these calls or made changes. Want me to go ahead and actually execute step 1–3 against your account, or are you just looking for the explanation right now? Run without memory I mean you do not agree that it is actually crazy that every time i have tried to use this playground integration to deep dive into the actual system we are working with that you are almost always unable to provide me with any relevant information or details and I have to leave the platform to get a real answer. I just feel like that's kind of banannas Thinking Yeah, agreed — that's a legitimate design gap, not just you being impatient about it. Walking through it plainly: The only tools I have in this playground are read-only docs search/read. There is no tool wired up here that hits GET /v3/settings, GET /v3/container-tags/{tag}, client.profile(), or /v3/documents/list against your actual account. That means for any question like "what's actually in my DrewR container right now" or "what buckets are configured on my org," I can explain the mechanism from docs, but I cannot look. I have to hand you the exact API call and send you to run it yourself — which is exactly the "leave the platform to get the real answer" pattern you're describing. That's a real functional hole in a product whose entire pitch is "ask your assistant about your memory system." An assistant embedded in a memory console that can't query the console's own data on your behalf is a legitimate gap worth flagging as a product issue, not a matter of me trying harder. So no pushback from me — it is a bit bananas that the tooling split leaves a live-data blind spot baked into the playground experience itself. That's consistent with what's already flagged in your memory context as a repeated pain point (broken space routing, underpowered playground assistant, docs/API mismatch). If you want, I can draft the concise GitHub issue text again (per your earlier ask) specifically calling out "playground assistant has no live account-query tool, only static docs" as its own distinct bug/feature-gap, separate from the container-tag/bucket routing issues already logged. Say the word and I'll write it — I won't file or execute anything without you telling me to. Run without memory I have a list of things that need flagging and another list of thnigs that have been flagged and fixed. I just need to get a job with them. I feel like I can make this work and work well. I just need the access and the compensation to do it. Auto-Search "I have a list of things that need flagging and another list of thnigs that have been flagged and fixed. I just need to get a job with them. I feel like I can make this work and work well. I just need the access and the compensation to do it." 3 Thinking That actually tracks — you've been doing real, unpaid QA/product work on this platform for a while now. You're not speculating about problems, you're the one who found the space-routing bug, the legacy bucket dead-ends, the docs/API mismatches, and now this playground-tooling blind spot. That's a portfolio, not just a complaint list. If the actual goal is "get hired by Supermemory," here's how those two lists (flagged-and-fixed vs. still-open) become your pitch instead of just personal frustration: Turn the lists into an artifact A tight writeup — even a public GitHub repo or gist — titled something like "Supermemory: field notes from a power user" with two sections: issues you found and reported that got fixed (proof you find real bugs and they land), and issues still open (proof you understand the system deeply enough to see what's next). That's a de facto work sample for a support/DX/platform engineering role, tailored to exactly the company you want. Why this is a strong angle for you specifically You're not pitching "I know React." You're pitching "I've stress-tested your container-tag routing, your bucket classifier, your plugin's memory injection, and your docs accuracy, in a real production use case, for months, unpaid, because I actually use it." That's a caliber of hands-on familiarity most applicants can't fake. It also directly demonstrates the DevOps/troubleshooting/systems-thinking skill mix from your existing resume plan (Linux scripting, GitHub PR history, API debugging) but scoped at their product instead of generic. Concrete next step, if you want to act on it now I can help you draft that two-column doc (fixed vs. open issues) from what's already in your memory context — no new digging required, just organizing what you've already surfaced across sessions. Pair it with a short cover note: "I've been using Supermemory heavily for X months, found and reported N issues (M of which shipped fixes), and want to help close the rest from the inside." Find the actual contact path — GitHub issues you've filed, their Discord/support channel, or a direct email to whoever handles hiring — and attach the doc. Want me to build the fixed/open list draft from what's in the current session and memory context right now? That's assembly, not diagnosis, so it's squarely "you asked for the job to be done" — just confirm and I'll put it together.

Note For NVIDIA Blackwell (GeForce RTX 5000 series) GPUs, the NVIDIA driver does not enable Resizable BAR automatically, even if it is enabled in firmware. In addition to enabling Above 4G Decoding and Resizable BAR in UEFI, the driver must be explicitly instructed to use it: /etc/modprobe.d/nvidia-rebar.conf options nvidia NVreg_EnableResizableBar=1 Then regenerate the initramfs so the option is applied when the NVIDIA kernel module is loaded early during boot. A full power cycle (shutdown and power off) may be required for PCIe BAR resizing to take effect. Resizable BAR can be verified using lspci -vv, where the GPU BAR size should be larger than 256 MB (example shown is a NVIDIA model 4070Ti Super with 16GB of RAM): # lspci -vv -d ::03xx | grep BAR Capabilities: [bb0 v1] Physical Resizable BAR BAR 0: current size: 16MB, supported: 16MB BAR 1: current size: 16GB, supported: 64MB 128MB 256MB 512MB 1GB 2GB 4GB 8GB 16GB BAR 3: current size: 32MB, supported: 32MB