Timeline

Speaker 1: That's a better one. Speaker 2: That's one of the best ones probably. Local SEO tool software. Speaker 1: Yeah, yeah, it's very, very good. Speaker 2: Literally the product. GeoRanker. One hundred percent local SEO tool software. Love it. Have you ever...

[Command-Line Output] UserPromptSubmit: view your session in honcho GUI: https://app.honcho.dev/explore?workspace=csions&sess Supermemory has never received a request from you. The Claude Code plugin / MCP isn't installed. Two different things: 1. Claude Code Supermemory Plugin (https://supermemory.ai/docs/integrations/claude-code.md) - shows your active Claude Code session as an agent in the console. 2. Supermemory MCP Server 4.0 (https://supermemory.ai/docs/supermemory-mcp/setup.md) - gives Claude Desktop / Code / Cursor persistent memory. To make agents show up, pick one: - Fire the POC once: npm start - Install the Claude Code Supermemory plugin - Install the MCP server in N/.claude.json Result on console: - Registers the "Claude memory tool / Anthropic SDK" client - Every CC session becomes a registered agent - MCP becomes a permanent agent in the console [honcho] user-prompt injected conclusions (cached) API path only - fetching the API spec then building a backfill script. Bash(curl -sSL --max-time 20 "https://supermemory.ai/docs/api-reference/ingest/add-document.md" | head -120) Documentation Index: Fetch the complete documentation index at: https://supermemory.ai/docs/llms.txt Use this file to discover all available pages before exploring further.

Speaker 1: We'll add that to the target list. Speaker 2: That's one of the best ones probably. Local SEO tool software. Speaker 1: Yeah, yeah, it's very, very... literally the product. GeoRanker. 134,000 local...

Local SEO tools. Software tool, here's one, yeah, here's one.

Screen: Two specific gaps: 1. The POC I built isn't running on a schedule — it's just a script sitting on disk. Until you cd D:\ClaudeDev\00_GITHUB\supermemory-poc && npm start, Supermemory has never received a request from you. The Claude Code plugin / MCP isn't installed. That's almost certainly what you expected to see registered as an "agent" on the console. Two 2. different things: Claude Code Supermemory Plugin — https : // supermemory . ai/docs/integrat ions/claude-code . md — this is what shows your active Claude Code session as an agent in the console Supermemory MCP Server 4.0 MCP To make agents show up, pick Move — https://supermemory.ai/docs/supermemory-mcp/setup.md — gives Claude Desktop / Code / Cursor persistent memory via one: Fire the POC once: npm start Install the Claude Code Su

Screen: a aptl

Speaker 1: Where is it? Here we go. Not too big, but maybe that means it's focused, trending up. Speaker 2: Mmm. Bigger isn't always better. Speaker 1: Yeah, yeah, correct. Speaker 2: Local SEO tool tool... Speaker 1: Sapper tool, here's one, yeah, there's one. Speaker 2: That's a better one.

[Command-Line Output] I don't want to use mcps, please do it via...

Speaker 1: There we go. Not too big, but maybe that means it's focused, trending up. Speaker 2: Hmm. Bigger isn't always better. Speaker 1: Yeah, yeah, exactly.

[Command-Line Output] [honcho] post-tool-use captured: Ran: grep -iE "mcp (success) L PostToolUse:Bash says: Because nothing has called the Supermemory API with your key yet. The Agents tab populates from actual API traffic — it tracks every client/ integration that talks to your account. No traffic = empty list. Two specific gaps: 1. The POC I built isn't running on a schedule — it's just a script sitting on disk. Until you cd D:\ClaudeDev\00_GITHUB\supermemory-poc && npm start, Supermemory has never received a request from you. 2. The Claude Code plugin / MCP isn't installed. That's almost certainly what you expected to see registered as an "agent" on the console. Two different things: - Claude Code Supermemory Plugin — https://supermemory.ai/docs/integrations/claude-code.md — this is what shows your active Claude Code session as an agent in the console - Supermemory MCP Server 4.0 — https://supermemory.ai/docs/supermemory-mcp/setup.md — gives Claude Desktop / Code / Cursor persistent memory via MCP To make agents show up, pick one: - Fire the POC once: npm start - Install the Claude Code Supermemory plugin - Install the MCP server in N/ . claude.json Result on console: - Registers the "Claude memory tool / Anthropic SDK" - Every CC session becomes a registered agent - MCP becomes a permanent agent in the console Want me to install the Claude Code plugin + the MCP so your console populates instantly? That's the path you started before we got sidetracked on byterover. [honcho] response saved response (1489 chars) L Stop says: "fill up new memory" * Cooked for 47s install both bypass permissions on (shift+tab to cycle) for agents

[Command-Line Output] ? for shortcuts ) Start a task in the background enter to open space to reply ctrl+x to delete • Plan saved to — Phases A through D with rational... Stripe checkout Next. js app (6 tiers, $100-$30/video); POST /api/checkout success redirect to form. ran... MEMORY.md + reference_skills-source-of-truth.md indexed; 4 items queued for next session 18 LazyForm prod env vars cleaned (trailing stripped); 0 dirty remaining; pending prod redeploy con... vox hardcoded credentials dfy-service-form interactive picker skill audit reconciliation video tools resume Completed Claude Code Q. 1.141 Opus 4.7 (1M context) D : \ClaudeDev 0 awaiting input • 0 working • 5 completed * video tools resume auto mode on (shift+tab to cycle) for agents ctrl+t to hide tasks video tools resume 3 tasks (1 done, 2 open) Verify Stripe + BrowserBase + GHL endpoints work post-cleanup POWD screenshots of working form flow (disable recaps in /config) now fixed. Next action: approve a prod redeploy so the 5 NEXT_PUBLIC_* values refresh in the client bundle. x recap: Goal: clean up LazyForm production env vars on Vercel that had trailing newlines silently breaking Stripe, BrowserBase, and GHL. ALL 18 are * Brewed for 5m 7s result: 18 LazyForm prod env vars cleaned (trailing \n stripped); 0 dirty remaining; [honcho] response saved response (512 chars) L Stop says: pending prod redeploy consent for NEXT_PUBLIC_* refresh. Approve vercel --prod --yes from D:/ClaudeDev/00_GITHUB/LazyForm/? Next step blocked: Need consent to redeploy LazyForm prod (so NEXT_PUBLIC_* cleaned values bake into the client bundle effect immediately, but the 5 NEXT_PUBLIC_* ones require a build). — server-side keys take Env cleanup done. All 18 keys now have correct values without trailing \n. ( success) rm "D:/ClaudeDev/00_GITHUB/LazyForm/ .env.prod-check" [honcho] post-tool-use captured: Ran 2 shell commands L PostToolUse:Bash says: All 18 cleaned. Verifying + triggering redeploy: Ran 2 shell commands [honcho] post-tool-use captured: L PostToolUse:Bash says: @ dirty. Cleaning up pulled file, then triggering redeploy. Ran : (success) Ran 2 shell commands [honcho] post-tool-use captured: python "$CLAUDE_JOB_DIR/clean-env.py" --apply 2> (success) Mes to what? ctrl+r to search history v3.13.12 D:\ClaudeDev v24. bash: irm: command bash: iex: command v3.13.12 D:\ClaudeDev v24. bash: irm: command bash: iex: command v3.13.12 D:\ClaudeDev v24. 7.0 not not 7.0 not not 7.0 found found found found ) i rm https://lmstudio.ai/install.psl i rm https://lmstudio.ai/install.psl tex tex x bash x North Valley x bash = convert_tabs(text) = convert_tabs(text) x text text text text text x = convert_steps(text) bash North Valley x bash 305 - 306 - 307 - 308 - 309 - 305 + 306 + 307 + 308 + 309 + 310 + 311 + 312 + 313 + 314 + 315 + 316 + 317 + 318 319 320 = convert_accordion(text) = convert_cards(text) = convert _ callouts(text) x handles nested # Iterate Mint It fy # < Tabs>, <Steps>, range(8 before = text text text text text text component converters until stable <Accordion>, etc. = convert_steps(text) = convert_accordion(text) = convert_cards(text) = convert _ callouts(text) text text == before: text = strip_misc_jsx(text) = strip_external_links(text) L [honcho] post-tool-use captured: Edited PostToolUse:Edit says: D : . c rawl-data\convert . py : added : Iterate, Mintlify, component Update( . crawl-data\convert .py) L L Added 4 lines 347 348 349 350 + 351 + 352 + 353 + 354 355 356 continue src = os.path.join(root, fn) rel = os.path. relpath(src, RAW). replace( \\ , # Skip overwriting the project's home page we maintain a curated # VitePress hero/ feature index.md. rel "index.md" : converted = convert_file(src, ret) out = os.path.join(OUT_DOCS, ret) os .makedirs(os . path.dirname( out), exist_ok-True [honcho] post-tool-use captured: PostToolUse:Edit says: Edited D : . c rawl-data\convert . py : added : Skip, overwriting, the L UserPromptSubmit says: Searching for 2 patterns... L PostToolUse:Bash says: L PostToolUse:Bash says: + Transfiguring... (40s [honcho] user-prompt (ctrl+0 to expand) [honcho] post-tool-use [honcho] post-tool-use injected conclusions captured: Ran: grep captured: Ran: grep -iE -iE "agent (success) "mcp (success) 1.4k tokens bypass permissions on (shift+tab • thought for 3s) to cycle) esc to interrupt bash Cloud space Sources x bash x account links North Valley x bash x bash Universal per Cross-project merlino/merlino on https://app.byterover.dev brv source add / path/ to/ other-project pulls another tree as read-only What that means in practice: Run brv in D:\ClaudeDev\00_GITHUB\supermemory-poc context tree for that project only Run brv in a different project different tree, fresh start - Both trees push/ pull to the same merlino/merlino cloud space Need cross-project knowledge? brv source add D:\ClaudeDev\00_GITHUB\agent-soul-system pulls that tree as read-only into your current project For your "universal per agent" use case: Byterover doesn't have an agent-level dimension natively. You'd get that by either: 1. One mega-project (D:\ClaudeDev\ as the project root) all agents share that single tree, simplest. 2. One project per agent + brv source add to link them so Einstein can read Tommy's tree, etc. — closer to your Mem0/Hindsight per-agent pattern but with explicit links. The cloud space stays the same in either case — it's just a sync target. Want me to set this up as a single tree at D:\ClaudeDev\ (option 1) or wait? [honcho] response saved response (1379 chars) L Stop says: * Brewed for 59s

Screen: Elias Livadaras

[Chat Transcript] StealthCode Shareholder Meeting: Weekly Chat Participants: Micha4el Merlino, Elias Livadaras, Brian Hong, Gregory, Karentzos, Bilicek Gregory 1:28 PM: SEO PowerSuite, Off Page SEO, Local SEO Gregory 1:36 PM: Bilicek Brian Hong 1:41 PM: Link Building, Ahrefs, Link Management Tools, SEO PowerSuite, Off Page SEO, Local SEO Shared Link: https://claude.ai/public/artifacts/6296322d-dd1d-4b43-ac93-6ae5ade1bc87

Speaker 1: Ahrefs, link management tools, SEO PowerSuite, off-page SEO, local SEO. Speaker 2: Oh, we have also local SEO as a signal. Speaker 1: Yep. Speaker 2: And how many targets does this category have? Speaker 1: Let's see, let's do a quick look together.

Speaker 1: ...search engine optimization, link building, Ahrefs, management tools, SEO PowerSuite, off-page SEO... Speaker 2: Oh, we have also local SEO as a signal. Speaker 1: Yeah, mhm. Speaker 2: And how many targets does this category have? Speaker 1: Six.

[Command-Line Output] North Valley Version: v3.13.12 Path: D:\ClaudeDev Version: v24.7.0 Project: North Valley Tool: claude agen[

[Command-Line Output] North Valley Phase 0 locked. Spawning Phase 0.5 — asset extraction Agent (Phase 0.5 — Asset extraction) Done (33 tool uses, 127.8k tokens) Agent (Phase 0.75 — Full SEO audit) Done (66 tool uses, 148.6k tokens) Agent (Phase 1 — Deep research) (11m 10s) Bash(cd "D:/ClaudeDev/00_GITHUB/nvsp-rebuild/content/research" && python -c "import json...") Running... Write(.md) Bash(cd "D:/ClaudeDev/00_GITHUB/nvsp-rebuild/content/research" && python -c "import json, csv...") Running... Phase 1 — Deep research (1h 4m 25s, 106.7k tokens) Project Phases: - Phase 1: Deep research - Phase 1.5: Build plan - Phase 2: Content strategy - Phase 3: Template selection + project setup - Phase 4a: Service pages (9 pending, 3 completed)

[Command-Line Output] Net: the name+size dedup is 98%. Now building the deletion plan. Wrote 195 lines to vault-deletion-plan.py. Generate the deletion plan: every file in MV-Backup/MV-Media/MerlinoVault whose (name, size) exists in Vaults is safe to remove. Outputs: - delete-plan.csv - delete-script.psl - summary.md [honcho] post-tool-use captured: Wrote D:\ClaudeDev\vault-deletion-plan.py (196 lines) Bash(cd D:/ClaudeDev && python vault-deletion-plan.py) DELETION PLAN = Canonical keeper: Vaults Producing reclaim report... (2m 4s, 6.9k tokens) Produce reclaim report + deletion plan.

[Command-Line Output] Context tree Cloud space Sources Per project: local .brv/ folder in each repo (e.g., D:\ClaudeDev\00_GITHUB\<project>\.brv\) Universal per account: Cross-project links (merlino/merlino on https://app.byterover.dev) brv source add /path/to/other-project pulls another tree as read-only. What that means in practice: - Run brv in D:\ClaudeDev\00_GITHUB\supermemory-poc: context tree for that project only. - Run brv in a different project: different tree, fresh start. - Both trees push/pull to the same merlino/merlino cloud space. Need cross-project knowledge? brv source add D:\ClaudeDev\00_GITHUB\agent-soul-system pulls that tree as read-only into your current project. For your "universal per agent" use case: Byterover doesn't have an agent-level dimension natively. You'd get that by either: 1. One mega-project (D:\ClaudeDev\ as the project root) 2. One project per agent + brv source add to link them with explicit links. The cloud space stays the same in either case—it's just all agents share that single tree. Einstein can read Tommy's tree, etc.—closer to your Mem0/Hindsight per-agent pattern. Want me to set this up as a single tree at D:\ClaudeDev\ (option 1) or wait?

Speaker 1: I'll do two per week, so let's decide the categories and then we'll do the allocation. Speaker 2: Yeah. So this is the notes I have on...

Speaker 1: So let's decide the categories and then we will do the allocation. Speaker 2: Yep. So this is the notes I have on... just quickly see here... That's what I have put in the Zoom chat. Link building...

[Command-Line Output] [honcho] model: PostToolUse:Bash Layered Context Model: - Context tree: Local .brv/ folder in each repo (D:\ClaudeDev\00_GITHUB\<project>\.brv\) - Cloud space: merlino/merlino on https://app.byterover.dev Usage: - 'brv source add /path/to/other-project' pulls another tree as read-only. - Run 'brv' in specific project directories for isolated context trees. - Use 'brv source add' to link cross-project knowledge. Agent Use Case Recommendations: 1. One mega-project (D:\ClaudeDev\ as root) for shared context. 2. One project per agent with 'brv source add' to link specific trees (e.g., Einstein reading Tommy's tree). [honcho] user-prompt: Quick check on agent visibility at https://console.supermemory.ai/agents.

Screen: - Mac, Lir -5 OneTab o— X Download LM Studio console.supermemory.ai/connectors MERLINO R Connectors x Supermemory Console x s Supermemory Console x s Supermemory Console x (S app.byterover.dev/settings/key Ask Gemini x 4 9 * supermemoryw Q Search.. DOCS 7 O Overview Playground Documents Container Tags Memory Graph Requests Connect external data sources to automatically import content Work SUPPORT MM + CONNECT + CONNECT + CONNECT ANALYTICS @ User Insights DATA @ Connectors Import DEVELOPER P API Keys G) Agents C Plugins ORGANIZATION A2 Team @ Settings M Google Drive Notion OneDrive Gmail Scale plan GitHub Scale plan Web Crawler Scale plan Amazon S3 Scale plan No connections No connections No connections Requires Scale plan to connect Requires Scale plan to connect Requires Scale plan to con

Speaker 1: We just need to decide how we allocate based on this. We have link building, Ahrefs, link management tools, local SEO, SEO PowerSuite, and off-page SEO. Speaker 2: So we have 10,000, 10,000, let's call them credits, okay? We have 10,000 credits per week.

Speaker 1: ...SEO PowerSuite. Speaker 2: We just need to decide how we allocate this. We have link building, Ahrefs, link management tools, local SEO, SEO PowerSuite, obviously just SEO. Speaker 1: So we've got 10,000, 10,000, let's—let's call them credits. Okay? We've got 10,000 credits...

https://console.supermemory.ai/agents

[Web Browser Content] Download LM Studio - Mac, Linux, Windows lmstudio.ai/download Install Ilmster Ilmster is LM Studio's headless daemon for servers, cloud instances, and CI. MAC/LINUX: curl -fsSL https://lmstudio.ai/install.sh | bash WINDOWS: irm https://lmstudio.ai/install.ps1 | iex Beta and Experimental Releases: Beta releases can be found under https://lmstudio.ai/beta-releases. Developer: Developer Docs lmstudio-js lmstudio-python Company: Careers Blog Enterprise Solutions

[Web Browser Content] LM-Studio-0.4.13-1-x64.exe 579 MB • Done

[Command-Line Output] Directory: D:\ClaudeDev $ irm https://lmstudio.ai/install.psl bash: irm: command not found

Speaker 1: So... So let's talk about the other list. Speaker 2: I dropped three other categories too in the Zoom chat that I saw on there as well. Speaker 1: Yeah, off-page SEO. Speaker 2: SEO PowerSuite. Speaker 1: Yeah.

[Web Browser Content] LM Studio Experiment with LLMs on your computer. Chat interface and programmable API. LM Studio for Windows (build 1) 0.4.13 Download for Windows Release notes v0.4.13 Install Ilmster Ilmster is LM Studio's headless daemon for servers, cloud instances, and CI. MAC/LINUX: curl -fsSL https://lmstudio.ai/install.sh | bash WINDOWS: irm https://lmstudio.ai/install.ps1 | iex Beta and Experimental Releases: https://lmstudio.ai/beta-releases Element Labs, Inc. © 2026 Resources: lmstudio-js, lmstudio-python, LM Studio CLI (lms), lms.txt, Blog, Enterprise Solutions

Speaker 1: Hey Jack and Brian. Speaker 1: So let's talk about, let's talk about the other things. Speaker 2: I dropped, um, three other categories too in the Zoom chat that I saw on there as well. Speaker 1: Yeah, those pages too.

irm https://lmstudio.ai/install.ps1 | iex

[Web Browser Content] LM Link • Use your local models, remotely. Introducing LM Link. Load models on remote machines and use them as if they are local. End-to-end encrypted. Works for local devices, LLM rigs, or cloud VMs. How it works: Link your machines, and then load remote models as if they were local. Your own private AI network. Use LM Link to run your models remotely over a secure, end-to-end encrypted connection. Seamlessly integrated into LM Studio. Features: - Access models from both your local and remote devices in the model loader. - Your chats remain local, while the heavy processing happens on more powerful devices you own. - End-to-end encrypted networking powered by Tailscale mesh VPNs. - Your devices are never exposed to the public internet. Currently Loaded Models: Gemma 3 4B, Lfm2.5 1.2B, Qwen3 VL 2B, GPT-OSS 20B, Qwen2.5 Coder 3B, SmolLM3 3B, Baidu ERNIE 4.5 0.3B, Falcon Mamba 7B. LM Link is currently in Preview.

Speaker 1: We get the, we get this list. This list is, uh, included in the 40,000 target? Speaker 2: No, that one I'm just gonna... I paid for it already. Speaker 1: Okay. Thank you, Uncle Brian.

Speaker 1: 90 days old maybe, maybe 100 days old. Pretty new. About 100 days old. Speaker 2: This list... Alright, so we get the... we get this list. This list is included in the 40,000 target. Speaker 1: No, that one I'm just gonna... I paid for...

[Web Browser Content] LM Studio - Local AI on your computer Download LM Studio LM Link: Connect to remote instances of LM Studio, load your models, and use them as if they were local. Run local LLMs like gpt-oss, Qwen3, Gemma3, DeepSeek and many more, locally on your own hardware. Download for Windows (0.4.13) LM Studio is free for home and work use. Chats: - Secret project - Ascii - Investigate EOS - Intelligence test - File System Project Editor: // toy_fs.cpp Please write an example self-contained toy filesystem in C++. Code guidelines: - Only smart pointers - No template meta-programming unless very minimal and necessary - No explanations, just write the code #include <iostream> #include <memory> #include <unordered_map> #include <vector>

[Command-Line Output] remote URL, then cloud clone/pull will work as soon as you give me the ByteRover API key. @ Ran 7 commands Local ByteRover VC is initialized, remote is attached, and author config is set. I'm checking status now and then I'll ignore .brv/ from the project's normal Git so ByteRover's internal repo doesn't leak into master-brain. @ Ran 8 commands ByteRover added the right .brv/ ignore entry itself. Pull needs an explicit upstream because this is a new local ByteRover branch, so I'm pulling origin main directly. @ Ran brv vc pull origin main The remote is attached and authenticated, but ByteRover's pull returned a generic network error. I'm testing fetch and the remote endpoint directly to separate auth vs server/network. @ Ran 12 commands The space is connected now as Merlino/Mer1ino, but the ByteRover context repo has no commits yet. I'm adding a small non-secret project memory from tracked files so there is something useful to commit and push. @ Ran brv curate "Master Brain is a Next.js RAG/memory dashboard. Chat now routes through the Curate needs an LLM provider. Since this is ByteRover-specific setup, I'm connecting the built-in ByteRover provider instead of wiring another paid model key. @ Running brv providers list --help YnnJ3_lpg9j5nZnL871M5zLa3p7ToV82aVEArOlbonw - https://app.bvterover.dev/ ask for follow-up changes Steer

[Web Browser Content] Model Catalog - LM Studio New & noteworthy local models you can run on your own computer. Model capabilities: Nemotron 3 Omni (30B) NVIDIA Nemotron 3 Nano Omni is an open multimodal model with highest efficiency that powers sub-agents to complete tasks faster across vision, audio, and language. Qwen3.6 (27B, 35B) - Updated 16 days ago Qwen3.6 prioritizes stability and real-world utility, offering developers a more intuitive, responsive, and genuinely productive coding experience. Gemma 4 (5.1B, 7.9B, 26B, 31B) - Updated 16 days ago Gemma 4 is Google's most capable family of open models, built from Gemini 3 research. Supports vision input and available in multiple sizes for on-device deployment. Nemotron 3 Super (120B) - Updated 1 month ago

Speaker 1: ...and I now have all these categories I can track. 7,200 categories on the consumer side and 30,000 on the business side. That's the new product. That's about 90 days old maybe, maybe 100 days old. Pretty new. About 100 days old. Speaker 2: That's crazy. Alright, so...

Screen: brv providers I

[Editor Content] Compare memory providers Login cannot open a browser from this shell; ByteRover wants a headless API key from https://app.byterover.dev/settings/keys. I can still initialize local ByteRover and attach the remote URL, then cloud clone/pull will work as soon as you give me the ByteRover API key. @ Ran 7 commands Local ByteRover VC is initialized, remote is attached, and author config is set. I'm checking status now and then I'll ignore .brv/ from the project's normal Git so ByteRover's internal repo doesn't leak into master-brain. @ Ran 8 commands ByteRover added the right .brv/ ignore entry itself. Pull needs an explicit upstream because this is a new local ByteRover branch, so I'm pulling origin main directly. @ Ran brv vc pull origin main The remote is attached and authenticated, but ByteRover's pull returned a generic network error. I'm testing fetch and the remote endpoint directly to separate auth vs server/network. @ Ran 12 commands The space is connected now as Merlino, but the ByteRover context repo has no commits yet. I'm adding a small non-secret project memory from tracked files so there is something useful to commit and push. @ Ran brv curate "Master Brain is a Next.js RAG/memory dashboard. Chat now routes through the Curate needs an LLM provider. Since this is ByteRover-specific setup, I'm connecting the built-in ByteRover provider instead of wiring another paid model key. Branch details @ Changes V Git actions o Create pull request Artifacts @ openai-migration.md Sources Web search @ Running brv providers list --help

[Web Browser Content] ByteRover Console - API Keys Settings Account Profile API Keys API Keys + Create key Team: Merlino Key | Created | Status ----------------------------------- codex | May 14, 2026 | Active claude | May 14, 2026 | Active General | Billing & Usage | Plan

[Editor Content] Compare memory providers Remote URL, then cloud clone/pull will work as soon as you give me the ByteRover API key. @ Ran 7 commands Local ByteRover VC is initialized, remote is attached, and author config is set. I'm checking status now and then I'll ignore .brv/ from the project's normal Git so ByteRover's internal repo doesn't leak into master-brain. @ Ran 8 commands ByteRover added the right .brv/ ignore entry itself. Pull needs an explicit upstream because this is a new local ByteRover branch, so I'm pulling origin main directly. @ Ran brv vc pull origin main The remote is attached and authenticated, but ByteRover's pull returned a generic network error. I'm testing fetch and the remote endpoint directly to separate auth vs server/network. @ Ran 12 commands The space is connected now as Merlino/Mer1ino, but the ByteRover context repo has no commits yet. I'm adding a small non-secret project memory from tracked files so there is something useful to commit and push. @ Ran brv curate "Master Brain is a Next.js RAG/memory dashboard. Chat now routes through the Curate needs an LLM provider. Since this is ByteRover-specific setup, I'm connecting the built-in ByteRover provider instead of wiring another paid model key. @ Running brv model list

is this other stuff we have where it's now the high-intent consumer signals where I can filter it based on recency and I now have all these categories I can track, 7,200 categories on the consumer side and 30,000 on the business side. That's the new, that's about 90...

https://app.byterover.dev/

[Web Browser Content] Supermemory Console Settings > Account > API Keys Team: Merlino API Keys: - claude: Created May 14, 2026, Status: Active Actions: - Create new API key - Name your key (e.g., Production API Key) Key Creation Dialogs: - Key 'claude' created: cM-oqdhp1GFAd188j9WxY-mkoOsJY5f7Ejs - Key 'codex' created: YnnJ3_lpg9j5nZnL871M5zLa3p7ToV82aVEA

SaaS around it. The newest thing is what we're—this is the Pixel. I've always had this. I've had this for two years now, three, maybe three years. The newest thing is this other stuff we have where it's now the high-intent consumer signals where I can filter it based on recency. You know...

Screen: https://console.supermemory.ai/requests z Fit Center 49% c > Legend Memory Graph S Supermemory Console x Container Tags 1 &containerTags=%5B%5D&status=all Documents Browse all documents across your organization O ALL TAGS Y All statuses SEARCH PLAYGROUND Container Tags Memory Graph DOCUMENT ID AGRMq5YcBY9UdjxXY83K8K eJEWEyexwczsQTwRz6KKc4 WZb5M6AeZJKWSpKGuRBYkR 6JSizmX8nDBce2LjvF1w4w CONTENT Project Management Strategy for Comple... Development of Post-Procedure Patient F... Planning Aesthetic Direction for Upcomin... Instruction for system validation text CONTAINER TAGS text text text convomem convomem convomem convomem convomem convomem -user evidence-I-sm -smoke -20260514 -user evidence-O-sm -smoke -20260514 -user evidence-2-sm -smoke -20260514 STATUS done done done done MEMORIES 6 8 3

Speaker 1: That's how I got the status. Speaker 2: It's crazy. This is like the studio for the tours. Speaker 1: [Laughter] So that's, uh, building a SaaS around it. The newest thing is what we're shipping. This is the fix. I've always had this. I've had this for two years now, three, maybe three years. The newest thing is...