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What's a good mcp server for connecting to another local computer?
I'm setting up a few old computers to use to run local LLMs for subagents, is there a good MCP server to talk to them that people recommend or like?
Producing On-Brand Visual Content
This is for all the social media experts- What is your workflow to generate posters and creatives that stay consistent with existing brand assets? We constantly need new media for our company, including infographics, posters, new creatives, etc..
Reinventing the wheel? (Job search workflows)
Am I trying to reinvent the wheel for my first ICM project? I'm working on building job search tools/workflows to support my own job search. I've jumped in head first and: - I'm burning through my CLAUDE PRO tokens - why? My sense is I've setup my root CLAUDE.md file poorly. I switched from Sonnet to Haiku and never used Opus. (I know there are other ways to access LLMs, but I want to spend some time mastering the Claude Code extension interface before jumping into openrouter, Claude API, etc.) - I'm iterating the folder/workflow/skill design but still getting really poor draft outputs (I got better outputs just prompting in the free version of Claude) - I'm still learning the Classroom content and am hoping to get some insights as to any red flags for being newer to this (i.e. I'm just biting off too much for my first project) ## Workspace Structure ``` jobbot/ ├── CLAUDE.md ← You are here (always loaded) ├── CONTEXT.md ← Task router ├── _config/ │ └── story-bank.md ← Master STAR narrative library (shared across workspaces) │ ├── linkedin-optimizer/ ← Build and maintain LinkedIn presence + content │ ├── CLAUDE.md │ ├── CONTEXT.md │ ├── profile/ ← Profile optimization pipeline │ ├── content/ ← Content creation pipeline │ ├── growth/ ← Analytics and growth tracking │ └── _config/ ← Stable reference: profile, voice, keywords, pillars │ ├── resume-optimizer/ ← Master CV + JD-tailored resumes │ ├── CLAUDE.md │ ├── CONTEXT.md │ ├── master-cv/ ← Full CV maintenance pipeline │ ├── tailored/ ← Per-application tailored resume pipeline │ └── _skills/ ← 6 skills: audit, rewrite, jd-decoder, match, tailor, ats-check │ ├── cover-letter-optimizer/ ← Per-application cover letters │ ├── CLAUDE.md │ ├── CONTEXT.md │ ├── pipeline/ ← intel → narrative → draft → review │ ├── final/ ← Approved cover letters │ └── _skills/ ← 4 skills: company-intel, narrative-select, draft, review │ ├── application-engine/ ← Application prep, ATS forms, tracking, analytics
Guide me
I want to render cool visualizations of building and office floorplans...any idea what a good workflow or resource would be?
How do you like to brainstorm? (For writing)
Context: I want to pitch a few talks to conferences in my field (game audio), and its not something I do regularly so I don't have established workflow for it. I do write linkedin posts and prep for my DND sessions, but that output is significantly different than a 30m to 1hr talk. I've been doing one approach, which I'll outline below, but I'm wondering if others have done this and have a more efficient way of getting to a final result, the below took me 2 sessions both a few hours each, and I'd love to compress that. Wondering about other approaches or resources to help create a better framework. Current process (captured in a skill after finishing last submission): 1. Claude asks : "What could you talk about from memory right now, without looking anything up?" and "What do you know how to do, or think about, that most people in your field don't?" (this takes a long time) 2. feed it which conference, deadline, and format the talk submission is 3. Claude researches past accepted talks for fit and content 4. We lock in thesis, pillars, and target audience (this takes the longest) 5. we do a draft in this order: Description, takeaway, outline 6. Pre-submission review (this part is easy with humanizer and the conference form submission) Wondering if there are places I could improve? And how would others approach this?
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Clief Notes
skool.com/quantum-quill-lyceum-1116
Jake Van Clief, giving you the Cliff notes on the new AI age.
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