[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-e925b9f48e97039f-hermes-agent-self-improving-skills-beat-stateless-summary":3,"summaries-facets-categories":297,"summary-related-e925b9f48e97039f-hermes-agent-self-improving-skills-beat-stateless-summary":3882},{"id":4,"title":5,"ai":6,"body":13,"categories":271,"created_at":273,"date_modified":273,"description":274,"extension":275,"faq":273,"featured":276,"kicker_label":273,"meta":277,"navigation":278,"path":279,"published_at":280,"question":273,"scraped_at":281,"seo":282,"sitemap":283,"source_id":284,"source_name":285,"source_type":286,"source_url":287,"stem":288,"tags":289,"thumbnail_url":273,"tldr":294,"tweet":273,"unknown_tags":295,"__hash__":296},"summaries\u002Fsummaries\u002Fe925b9f48e97039f-hermes-agent-self-improving-skills-beat-stateless--summary.md","Hermes Agent: Self-Improving Skills Beat Stateless Agents",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","x-ai\u002Fgrok-4.1-fast",8535,2671,30951,0.00301985,{"type":14,"value":15,"toc":261},"minimark",[16,21,30,33,49,52,55,66,70,73,113,116,119,123,126,152,155,160,163,167,170,181,184,198,203,206,210,217,222,226],[17,18,20],"h2",{"id":19},"stateless-agents-waste-learned-workhermes-compounds-it","Stateless Agents Waste Learned Work—Hermes Compounds It",[22,23,24,25,29],"p",{},"Most AI agent frameworks treat every interaction as isolated: you give a task, it executes via tools like APIs or code, then forgets everything. This mirrors early web browsers in 1995—plenty of options, no standards. Nick Puru argues this statelessness limits real value, as agents never improve. Hermes, an open-source framework from Nous Research (v0.6.0, 19k GitHub stars, MIT license), flips this by capturing full execution \"trajectories\" (every API call, decision, tool sequence) and distilling them into reusable \"skills\"—LLM-generated functions stored as code in ",[26,27,28],"code",{},"\u002Fhermes\u002Fbackend\u002Fskills",".",[22,31,32],{},"For a first-time complex task like \"Pull Stripe revenue, cross-reference HubSpot pipeline, analyze in Python, generate chart, send Slack summary with 3 insights,\" Hermes chains 15-20 steps across 40+ tools (web search, terminal, browser automation, code execution, image gen, TTS, vision). Post-execution:",[34,35,36,40,43,46],"ol",{},[37,38,39],"li",{},"Records trajectory.",[37,41,42],{},"Analyzes: \"Can this be packaged as reusable?\"",[37,44,45],{},"If yes, generates\u002Ftests\u002Fstores skill.",[37,47,48],{},"Next similar request: Runs\u002Frefines skill (faster, cleaner).",[22,50,51],{},"Over time, it patterns your preferences (e.g., vague queries get context-aware nudges: \"You probably want skill X\"). Skills evolve per user—your Hermes shapes to workflows, unlike generic ChatGPT\u002FClaude resets. Puru: \"Hermes, it is designed to be getting better. It gets smarter the longer that it actually works with you.\"",[22,53,54],{},"This enables compounding: Week 1 manual 20-step revenue analysis → Week 4: Runs polished skill autonomously Tuesdays. Export trajectories to ShareGPT for fine-tuning your models via RL pipeline.",[56,57,58],"blockquote",{},[22,59,60,61,65],{},"\"Most agent frameworks, they just throw that away completely. Like the task is done, the memor",[62,63,64],"span",{},"y"," is gone, Hermes keeps it instead.\" — Nick Puru, explaining why trajectory capture changes agent architecture.",[17,67,69],{"id":68},"deployment-matches-any-infrastructurefrom-laptop-to-serverless","Deployment Matches Any Infrastructure—From Laptop to Serverless",[22,71,72],{},"Hermes avoids lock-in with 6 backends, suiting varied needs:",[74,75,76,83,89,95,101,107],"ul",{},[37,77,78,82],{},[79,80,81],"strong",{},"Local terminal",": Dev\u002Ftesting (your phone via Telegram).",[37,84,85,88],{},[79,86,87],{},"Docker",": Production isolation.",[37,90,91,94],{},[79,92,93],{},"SSH\u002FVPS",": Puru's choice ($5-10\u002Fmo, runs 24\u002F7 without idle costs).",[37,96,97,100],{},[79,98,99],{},"Singularity",": Research clusters (GPU).",[37,102,103,106],{},[79,104,105],{},"Daytona",": Persistent cloud dev.",[37,108,109,112],{},[79,110,111],{},"Modal",": Serverless (hibernates idle, wakes on message—pay-per-second).",[22,114,115],{},"Messaging gateways (12 platforms: Telegram, Discord, Slack, WhatsApp, Signal, email, etc.) ensure continuity—start CLI, resume Discord, no context loss. Python-heavy (92.5%) integrates seamlessly with LLM APIs\u002Ftransformers. Install: Single curl command (60s), handles Python\u002FNode deps.",[22,117,118],{},"Puru runs on VPS for always-on jobs without babysitting hardware: \"I just want to keep it simple and see if I like this first through a VPS.\"",[17,120,122],{"id":121},"trade-offs-learning-excels-for-personal-tools-not-speed-pipelines","Trade-offs: Learning Excels for Personal Tools, Not Speed Pipelines",[22,124,125],{},"Hermes prioritizes adaptation over raw speed\u002Forchestration (slower than CrewAI\u002FLangGraph for multi-step flows). Key caveats:",[74,127,128,134,140,146],{},[37,129,130,133],{},[79,131,132],{},"OS",": No native Windows (use WSL2; experimental PRs incoming)—blocks Windows-heavy enterprises.",[37,135,136,139],{},[79,137,138],{},"Learning scope",": Only complex tasks trigger skills; simple ones ignored. LLM-generated code may fail (needs tweaks)—\"not magic.\"",[37,141,142,145],{},[79,143,144],{},"Security",": Local backend allows terminal access (runs as you); docs mandate Docker\u002FModal for prod (container boundary). Dangerous command checks exist, PR tightening.",[37,147,148,151],{},[79,149,150],{},"Reliability",": Can loop\u002Fignore messages (v0.4+ fixes, but recurs). Gets stuck on interruptions.",[22,153,154],{},"\"If your use case is run this pipeline as fast as possible... those frameworks are going to be better. ... If ... build an agent that gets smarter the longer I use it, that's where Hermes is going to actually be much much better.\"",[56,156,157],{},[22,158,159],{},"\"Hermes it is trading speed for learning and that's the bet that they are essentially making.\" — Nick Puru, on why Hermes optimizes for long-term intelligence over immediate execution.",[22,161,162],{},"Best for Mac\u002FLinux shops building internal\u002Fpersonal agents (e.g., revenue analysis, custom workflows). Avoid for Windows-native, ultra-secure no-container, or latency-critical ops.",[17,164,166],{"id":165},"hermes-vs-openclaw-learning-depth-vs-ecosystem-breadth","Hermes vs. OpenClaw: Learning Depth vs. Ecosystem Breadth",[22,168,169],{},"OpenClaw (Peter Steinberger's 2025 weekend project: 300k+ stars in 4 months, 13k ClawHub skills, 2M MAUs, 24 platforms) is a TypeScript messaging gateway\u002Fcontrol plane—routes AI everywhere (iMessage to WeChat). Huge community\u002Ftutorials; human-maintained skills. No built-in learning: Memories via plugins (LanceDB vectors, lossless persistence)—manual config. No trajectory\u002FRL export.",[22,171,172,173,176,177,180],{},"Hermes (Python, Nous Research): Baked-in learning (autonomous skills, self-improvement). Fewer platforms (12), but cross-continuity shines. Infra edge: 6 backends vs. OpenClaw's Node\u002FDocker. ",[79,174,175],{},"Killer feature",": ",[26,178,179],{},"hermesclaw migrate","—one-command pulls OpenClaw's soul.md, memories\u002Fskills\u002FAPI keys\u002Fconfig.",[22,182,183],{},"Puru rejects \"which is better?\"—\"fundamentally different architectural bets.\"",[74,185,186,192],{},[37,187,188,191],{},[79,189,190],{},"OpenClaw",": Ops\u002Fplatform for customer-facing, multi-channel (e.g., 5 business channels Day 1).",[37,193,194,197],{},[79,195,196],{},"Hermes",": Personal\u002Fresearch for compounding knowledge\u002Fexportable training data.",[56,199,200],{},[22,201,202],{},"\"They're just completely different games. Pick the one that actually matches what you're going to be building.\" — Nick Puru, contrasting Hermes' learning focus with OpenClaw's distribution strengths.",[22,204,205],{},"Run both: Keep OpenClaw for breadth, Hermes for depth.",[17,207,209],{"id":208},"frictionless-onboarding-proves-the-value","Frictionless Onboarding Proves the Value",[22,211,212,213,216],{},"Setup demo: ",[26,214,215],{},"curl"," GitHub installer → auto-detects\u002Finstalls deps → ready. Live walkthrough: Config APIs\u002Ftools, chat via terminal\u002FTelegram. Phone access: Message anywhere, VPS handles compute. Ships 40+ skills; custom ones via agentskills.io (npm-like). Puru migrated OpenClaw setups seamlessly.",[56,218,219],{},[22,220,221],{},"\"One thing that I really like about Hermes is how simple this is to actually set up. So it's legitimately a few minute task.\" — Nick Puru, after live install, highlighting barrier-to-entry as a key adoption driver.",[17,223,225],{"id":224},"key-takeaways","Key Takeaways",[74,227,228,231,234,240,246,249,252,255,258],{},[37,229,230],{},"Target complex, repeatable workflows (e.g., multi-API analysis) to trigger skill creation—simple queries won't learn.",[37,232,233],{},"Start on VPS\u002FDocker for always-on without hardware; Modal for cheap serverless ($0 idle).",[37,235,236,237,239],{},"Expect LLM skill bugs: Review\u002Fedit ",[26,238,28],{}," code manually.",[37,241,242,243,245],{},"Migrate from OpenClaw with ",[26,244,179],{}," to test learning alongside breadth.",[37,247,248],{},"Use for personal compounding agents; pick CrewAI\u002FLangGraph for speed, OpenClaw for multi-platform ops.",[37,250,251],{},"Secure prod: Always containerize (Docker\u002FModal)—local terminal risks shell access.",[37,253,254],{},"Track evolution: Full-text search past convos\u002Ftasks for memory; patterns nudge suggestions.",[37,256,257],{},"Evaluate fit: Mac\u002FLinux internal tools yes; Windows\u002Fenterprise security no.",[37,259,260],{},"Compound via RL: Export trajectories to ShareGPT for custom model fine-tuning.",{"title":262,"searchDepth":263,"depth":263,"links":264},"",2,[265,266,267,268,269,270],{"id":19,"depth":263,"text":20},{"id":68,"depth":263,"text":69},{"id":121,"depth":263,"text":122},{"id":165,"depth":263,"text":166},{"id":208,"depth":263,"text":209},{"id":224,"depth":263,"text":225},[272],"AI Automation",null,"🤖 Transform your business with AI: https:\u002F\u002Fsalesdone.ai\n📚 We help entrepreneurs & industry experts build & scale their AI Agency: https:\u002F\u002Fwww.skool.com\u002Ftheaiaccelerator\u002Fabout\n🤚 Join the best community for AI entrepreneurs and connect with 16,000+ members: - https:\u002F\u002Fwww.skool.com\u002Fsystems-to-scale-9517\u002Fabout\n\nSign up to our weekly AI newsletter - https:\u002F\u002Fai-core.beehiiv.com\u002F\n\n🙋 Connect With Me!\nInstagram -   \u002F nicholas.puru  \nX - https:\u002F\u002Fx.com\u002FNicholasPuru\nLinkedIn - https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fnicholas-puruczky-113818198\u002F\n\n\n0:00 - Hermes Agent: the self-improving AI framework\n1:21 - What Hermes actually is\n2:38 - The learning system explained\n5:08 - How it's different from ChatGPT & Claude\n5:27 - Deployment options (6 backends)\n7:09 - How the learning loop works under the hood\n10:47 - Limitations & honest caveats\n13:52 - Hermes vs Open Cloud comparison\n18:09 - Built-in Open Cloud migration tool\n19:16 - Live setup walkthrough\n23:14 - Using Hermes from your phone\n26:15 - Final thoughts: learning vs breadth","md",false,{},true,"\u002Fsummaries\u002Fe925b9f48e97039f-hermes-agent-self-improving-skills-beat-stateless-summary","2026-04-05 18:44:44","2026-04-06 16:39:24",{"title":5,"description":274},{"loc":279},"e925b9f48e97039f","Nick Puru | AI 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Pitch Agent builds full branded pitch decks with comps, precedents, and LBOs over a weekend's work. Market Researcher outputs sector overviews, competitive landscapes, peer comps, and investment ideas. Earnings Reviewer processes call audio, press releases, and 10Qs to update models and draft notes. Model Builder runs live DCF, three-statement, and comps models in headless Excel (XLSX output). Middle-office agents like GL Reconciler trace ledger breaks for signoff, Month-End Closer manages accruals and variances, Valuation Reviewer applies firm templates to GP packages for LP reporting, Statement Auditor checks LP statements, and KYC Screener flags compliance gaps from onboarding docs. These replace $80k\u002Fyear junior roles in accounting and compliance, with human signoff required on all outputs.",[22,3901,3902],{},"Seven vertical skill bundles cover investment banking, equity research, private equity, wealth management, fund admin, operations, plus a core financial analysis bundle shared across agents. Eleven licensed MCP connectors integrate FactSet, S&P Global, Morningstar, Moody's, PitchBook, LSEG, Daloopa, Aiera, Chronograph, MT Newswires, and Egnyte—enabling data pulls only with valid subscriptions.",[17,3904,3906],{"id":3905},"plugin-architecture-enables-easy-customization","Plugin Architecture Enables Easy Customization",[22,3908,3909,3910,3913,3914,3917,3918,3921,3922,3925,3926,3929,3930,3933,3934,3937,3938,3941,3942,3945,3946,3949],{},"Each agent is a Claude Code plugin: an ",[26,3911,3912],{},"agent.md"," system prompt, ",[26,3915,3916],{},"skills\u002F"," Markdown files, ",[26,3919,3920],{},"commands\u002F"," slash commands, and ",[26,3923,3924],{},"mcp.js"," for connector permissions. Skills sync from vertical plugins via ",[26,3927,3928],{},"sync_agent_skills.py",". No build step—install in three commands on Claude's Cowork: add marketplace, install core financial analysis (includes connectors), cherry-pick agents\u002Fverticals. Deploy via ",[26,3931,3932],{},"deploy_managed_agent.sh"," to ",[26,3935,3936],{},"\u002Fv1\u002Fagents"," API or ",[26,3939,3940],{},"orchestrate.py"," event loop for handoffs. Security limits: no bash, web fetch, or undeclared connectors; GitLeaks scans secrets for terminal credentials. May 5 restructure moved verticals to ",[26,3943,3944],{},"plugins\u002Fvertical-plugins\u002F",", agents to ",[26,3947,3948],{},"plugins\u002Fagent-plugins\u002F",", added managed agent cookbooks, fund admin vertical, and tool grants.",[17,3951,3953],{"id":3952},"trade-offs-and-fintech-impact","Trade-offs and Fintech Impact",[22,3955,3956],{},"Connectors require paid licenses ($25k\u002Fyear Bloomberg precedent), so not turnkey—tune prompts and swap data sources for production. Agents are templates, not finished products, but publish full skill ladders: prompts, conventions, audit checklists absent from vendors for 20 years. Forks (1.5k) and stars (11.4k, #1 Python trend day of launch) show traction from years of commits, partner plugins (LSEG, S&P Global). For fintech SaaS builders or agent frameworks, this sets 2026 reference ceiling—prospects can self-host analyst stacks, shifting sales conversations. Apache 2.0 license accelerates community extensions.",{"title":262,"searchDepth":263,"depth":263,"links":3958},[3959,3960,3961],{"id":3895,"depth":263,"text":3896},{"id":3905,"depth":263,"text":3906},{"id":3952,"depth":263,"text":3953},[272],{"content_references":3964,"triage":3976},[3965,3970,3973],{"type":3966,"title":3967,"url":3968,"context":3969},"tool","Claude for Financial Services","https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services","mentioned",{"type":3966,"title":3971,"url":3972,"context":3969},"Cowork","https:\u002F\u002Fclaude.com\u002Fproduct\u002Fcowork",{"type":3966,"title":3974,"url":3975,"context":3969},"Managed Agents API","https:\u002F\u002Fdocs.claude.com\u002Fen\u002Fapi\u002Fmanaged-agents",{"relevance":3977,"novelty":3977,"quality":3977,"actionability":3977,"composite":3977,"reasoning":3978},4,"Category: AI Automation. The article discusses the release of open-source AI agents that can perform specific financial analyst tasks, addressing the audience's need for practical AI applications in product development. It provides concrete examples of agent functionalities and integration, making it actionable for developers looking to implement similar solutions.","\u002Fsummaries\u002Fec6591609db819d3-anthropic-open-sources-wall-st-analyst-agents-summary","2026-05-08 17:24:49","2026-05-09 15:32:49",{"title":3885,"description":262},{"loc":3979},"ec6591609db819d3","AI Summaries (evaluation playlist)","article","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=E4GNZxJQqfM","summaries\u002Fec6591609db819d3-anthropic-open-sources-wall-st-analyst-agents-summary",[290,291,293],"Anthropic released 10 end-to-end Claude agents mimicking Goldman Sachs analyst roles, with prompts, checklists, 11 licensed data connectors, and 7 vertical bundles—democratizing workflows once locked behind $25k terminals and bank secrecy.","Walkthrough of Anthropic's [financial-services repo](https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services), reading its README aloud and demoing the restructure into 10 finance-agent plugins (Pitch Agent, etc.) for workflows like IB decks and GL reconciliation, plus install via [Cowork](https:\u002F\u002Fclaude.com\u002Fproduct\u002Fcowork) and [Managed Agents API](https:\u002F\u002Fdocs.claude.com\u002Fen\u002Fapi\u002Fmanaged-agents). Covers architecture and recent commits but no hands-on runs.",[293],"WPKxqBiU9F-SwqNy4rXC6bS6TpNlS1bglsvFSrs6RTo",{"id":3995,"title":3996,"ai":3997,"body":4002,"categories":4030,"created_at":273,"date_modified":273,"description":262,"extension":275,"faq":273,"featured":276,"kicker_label":273,"meta":4031,"navigation":278,"path":4046,"published_at":4047,"question":273,"scraped_at":4048,"seo":4049,"sitemap":4050,"source_id":4051,"source_name":4052,"source_type":286,"source_url":4053,"stem":4054,"tags":4055,"thumbnail_url":4057,"tldr":4058,"tweet":4059,"unknown_tags":4060,"__hash__":4061},"summaries\u002Fsummaries\u002F39dde3bc67a5d66f-replay-logs-fail-agents-use-vm-snapshots-instead-summary.md","Replay Logs Fail Agents: Use VM Snapshots Instead",{"provider":7,"model":8,"input_tokens":3998,"output_tokens":3999,"processing_time_ms":4000,"cost_usd":4001},6744,1589,18772,0.0021208,{"type":14,"value":4003,"toc":4025},[4004,4008,4011,4015,4018,4022],[17,4005,4007],{"id":4006},"replay-model-breaks-for-long-running-agents","Replay Model Breaks for Long-Running Agents",[22,4009,4010],{},"Traditional replay durability—wrapping steps in a journal for replay on resume—built reliable async workflows like order processing without double-charging cards. It caches executed steps, provides audit trails, and enables resuming after human input or failures. But agents invert this: LLMs orchestrate tools in loops, turning every LLM call and tool into journal steps. After one turn, logs balloon; multi-turn interactions hit limits on entry count or size. Agent runtimes double every 4-7 months—from hours to days—making agents sessions, not transactions. Replay forces rigid, deterministic code outside steps, complicates versioning, and can't capture compute state like files, memory, or subprocesses (e.g., cloned repos, dev servers).",[17,4012,4014],{"id":4013},"split-durability-context-logs-execution-snapshots","Split Durability: Context Logs + Execution Snapshots",[22,4016,4017],{},"Agents need two states: context (append-only log of system\u002Fuser messages, tool calls\u002Fresults, assistant responses) and execution (VM state: files, memory, subprocesses). Store context in databases, object storage, or distributed filesystems—durable across code versions, crashes, scales well. For execution, snapshot\u002Frestore the machine: save when idle (user lunches), restore on next message. This preserves Git clones, installed packages, datasets cheaply vs. always-on VMs. Recover selectively: snapshot for LLM outages (retry after 15min), restart execution from context log for machine bugs\u002Fcrashes. Agents force shift from 30-year stateless compute (CGI 1993 → LAMP → Node\u002FServerless) to stateful compute.",[17,4019,4021],{"id":4020},"firecracker-snapshots-14mb-sub-second-ops","Firecracker Snapshots: 14MB, Sub-Second Ops",[22,4023,4024],{},"CRIU (2011) enabled userspace process checkpoint\u002Frestore via 'parasite' injection—transparent, container-compatible, but limited to single processes (no ffmpeg\u002FChrome), misses closed files, slow with registries. Firecracker microVMs snapshot entire machines, resuming subprocesses seamlessly. Naive 512MB RAM snapshots bloat storage\u002Ftransfer; compress with seekable format (decompress only accessed pages on restore), plus layering, yields 14MB tunable size. Results: snapshots \u003C1s, restores ~100-200ms. Open-source CLI 'fc-run' (docker-like) runs\u002Fsnaps\u002Frestores\u002Fforces VMs fast—15,000 starts\u002Fmin (30 FPS video equivalent), powers Trigger.dev's agent compute.",{"title":262,"searchDepth":263,"depth":263,"links":4026},[4027,4028,4029],{"id":4006,"depth":263,"text":4007},{"id":4013,"depth":263,"text":4014},{"id":4020,"depth":263,"text":4021},[272],{"content_references":4032,"triage":4042},[4033,4035,4037,4039],{"type":3966,"title":4034,"context":3969},"CRIU",{"type":3966,"title":4036,"context":3969},"Firecracker microVMs",{"type":3966,"title":4038,"context":3969},"fc-run",{"type":4040,"title":4041,"context":3969},"other","IBM mainframe checkpoint\u002Frestore",{"relevance":4043,"novelty":3977,"quality":3977,"actionability":3977,"composite":4044,"reasoning":4045},5,4.35,"Category: AI Automation. The article provides a deep dive into the challenges of replay durability in AI agents and presents a practical solution using VM snapshots, which directly addresses the pain points of developers working with long-running AI agents. It offers actionable insights on how to implement this approach, making it highly relevant for the target audience.","\u002Fsummaries\u002F39dde3bc67a5d66f-replay-logs-fail-agents-use-vm-snapshots-instead-summary","2026-05-10 20:00:06","2026-05-11 15:00:18",{"title":3996,"description":262},{"loc":4046},"39dde3bc67a5d66f","AI Engineer","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=svCnShDvgQg","summaries\u002F39dde3bc67a5d66f-replay-logs-fail-agents-use-vm-snapshots-instead-summary",[290,291,293,4056],"devops-cloud","https:\u002F\u002Fi.ytimg.com\u002Fvi\u002FsvCnShDvgQg\u002Fhqdefault.jpg","Replay durability constrains agent code with growing logs; split into context logs (DB durable) and execution snapshots (14MB Firecracker VMs, \u003C1s save\u002F100ms restore) for multi-day sessions.","Conference talk by Trigger.dev CEO [Eric Allam](https:\u002F\u002Fx.com\u002Fmaverickdotdev) contrasting replay journaling (step-wise LLM\u002Ftool logs for recovery) with OS-level snapshots on Firecracker microVMs for preserving agent execution state like files and subprocesses, plus DB logs for context. Includes backend history and recovery demos.",[293,4056],"VojlT4fEepnScoQLqNWr4Dm8ssvFRptLWxpXbhvMJUc",{"id":4063,"title":4064,"ai":4065,"body":4070,"categories":4115,"created_at":273,"date_modified":273,"description":262,"extension":275,"faq":273,"featured":276,"kicker_label":273,"meta":4116,"navigation":278,"path":4131,"published_at":4132,"question":273,"scraped_at":4133,"seo":4134,"sitemap":4135,"source_id":4136,"source_name":4137,"source_type":286,"source_url":4138,"stem":4139,"tags":4140,"thumbnail_url":4142,"tldr":4143,"tweet":4144,"unknown_tags":4145,"__hash__":4146},"summaries\u002Fsummaries\u002F589e4e6f244bb9b3-hermes-desktop-app-enables-easy-self-evolving-ai-a-summary.md","Hermes Desktop App Enables Easy Self-Evolving AI Agents",{"provider":7,"model":8,"input_tokens":4066,"output_tokens":4067,"processing_time_ms":4068,"cost_usd":4069},6802,1828,22602,0.0022519,{"type":14,"value":4071,"toc":4109},[4072,4076,4079,4082,4086,4089,4092,4096,4099,4102,4106],[17,4073,4075],{"id":4074},"hermes-evolves-through-persistent-memory-and-learning-loops","Hermes Evolves Through Persistent Memory and Learning Loops",[22,4077,4078],{},"Hermes Agent, built by Nous Research under MIT license, operates as a 24\u002F7 autonomous system that improves over time unlike static chatbots. It maintains cross-session memory retention, builds reusable skills from completed tasks via closed learning loops, and creates deeper user models using systems like Honcho. This enables self-nudges for capability growth and periodic knowledge updates, focusing on depth from experiences rather than broad tool access. Agents orchestrate multi-agent workflows, handle autonomous tasks, and retain understanding across sessions, making it suitable for ongoing infrastructure runs.",[22,4080,4081],{},"To generate outputs like full videos, Hermes integrates skills such as official HyperFrames for HTML-native control over scenes, layouts, animations, and rendering—demonstrated by autonomously creating the showcase video itself.",[17,4083,4085],{"id":4084},"superior-reliability-over-openclaw-for-daily-workflows","Superior Reliability Over OpenClaw for Daily Workflows",[22,4087,4088],{},"Users switch from OpenClaw due to Hermes' built-in long-term memory, self-improving loops, and higher reliability in production-like scenarios. While OpenClaw emphasizes breadth, Hermes prioritizes learning from tasks, leading to smarter performance over time. The Desktop App supports seamless migration of OpenClaw sessions, tools, skills, API keys, and configurations, preserving setups without rework. This bridges research prototypes to everyday use, outperforming CLI-heavy alternatives like early Hermes or Claude Code for non-terminal users.",[22,4090,4091],{},"Cross-platform support (Windows, macOS, Linux) ensures native performance without manual CLI management of memory, orchestration, or agents.",[17,4093,4095],{"id":4094},"one-click-setup-and-ui-for-local-or-remote-agents","One-Click Setup and UI for Local or Remote Agents",[22,4097,4098],{},"Download platform-specific installers (DMG for macOS, EXE for Windows) from GitHub releases; requires 2GB space for local install. Post-install, connect remote Hermes API (URL + optional key) or set up locally. Select providers like OpenAI, OpenRouter, Anthropic, or local models via Nous portal (free but lower performance). Paste API keys and start.",[22,4100,4101],{},"The contained UI eliminates CLI barriers: chat interface uses Hermes loop for tasks; left sidebar manages session logs, multi-profiles (agents for specific use cases), 3D office visualization for sub-agents, models\u002Fproviders (add local), personas (tone\u002Finstructions), memory (knowledge base), tools (web search, browser_use, terminal, file ops), cron jobs for scheduled tasks, gateways (Telegram, Discord, iMessage for phone control), and settings (themes, network). Add tool APIs like Fal.ai (images), Firecrawl (scraping), Exa AI (search) to expand skills.",[17,4103,4105],{"id":4104},"practical-use-cases-and-workflow-expansion","Practical Use Cases and Workflow Expansion",[22,4107,4108],{},"Deploy as self-improving wiki\u002Fsecond brain for workflows; generate blog posts, Expos; build 24\u002F7 assistants with Supabase CRM; financial analysts; app creators. Demos include recursive component use for Shadcn Finance dashboard (improves with latest components) and full CRM dashboards. Schedule tasks like Cloud Code\u002FCodeEx; orchestrate multi-agents in 3D sims. Outcomes: autonomous video gen, persistent productivity gains, and scalable local AI without cloud dependency—ideal for developers needing reliable, evolving agents.",{"title":262,"searchDepth":263,"depth":263,"links":4110},[4111,4112,4113,4114],{"id":4074,"depth":263,"text":4075},{"id":4084,"depth":263,"text":4085},{"id":4094,"depth":263,"text":4095},{"id":4104,"depth":263,"text":4105},[272],{"content_references":4117,"triage":4127},[4118,4121,4124],{"type":3966,"title":4119,"url":4120,"context":3969},"hermes-desktop","https:\u002F\u002Fgithub.com\u002Ffathah\u002Fhermes-desktop",{"type":4040,"title":4122,"url":4123,"context":3969},"Hermes Docs","https:\u002F\u002Fhermes-agent.nousresearch.com\u002Fdocs",{"type":4040,"title":4125,"url":4126,"context":3969},"Hermes Use Cases","https:\u002F\u002Fhermes-agent.nousresearch.com\u002Fdocs\u002Fuser-stories",{"relevance":3977,"novelty":4128,"quality":3977,"actionability":3977,"composite":4129,"reasoning":4130},3,3.8,"Category: AI Automation. The article discusses the Hermes Agent's capabilities, which directly relate to AI automation and self-evolving agents, addressing the audience's interest in practical AI tools. It provides specific details about the agent's features and setup process, making it actionable for developers looking to implement such systems.","\u002Fsummaries\u002F589e4e6f244bb9b3-hermes-desktop-app-enables-easy-self-evolving-ai-a-summary","2026-05-10 06:27:40","2026-05-10 15:17:43",{"title":4064,"description":262},{"loc":4131},"bbb378e0d4014800","WorldofAI","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=YBp_PXBbe80","summaries\u002F589e4e6f244bb9b3-hermes-desktop-app-enables-easy-self-evolving-ai-a-summary",[290,291,4141,293],"ai-tools","https:\u002F\u002Fi.ytimg.com\u002Fvi\u002FYBp_PXBbe80\u002Fhqdefault.jpg","Hermes Agent runs 24\u002F7 persistent, self-improving AI agents locally with long-term memory and closed learning loops; new Desktop App adds intuitive UI for setup, multi-agent management, and tools on Windows, macOS, Linux.","Quick demo and setup walkthrough for the [Hermes Desktop App](https:\u002F\u002Fgithub.com\u002Ffathah\u002Fhermes-desktop), a native UI wrapper for [Nous Research's Hermes Agent](https:\u002F\u002Fhermes-agent.nousresearch.com\u002Fdocs) that simplifies local multi-agent management, tool integration, and persistent memory on Windows\u002FMac\u002FLinux. Brief OpenClaw comparison and basic usage examples included.",[293],"dSvH3BXjeIno2NdmqCstaYUk2Sl-uAVagO_lvLgUed4",{"id":4148,"title":4149,"ai":4150,"body":4155,"categories":4723,"created_at":273,"date_modified":273,"description":262,"extension":275,"faq":273,"featured":276,"kicker_label":273,"meta":4724,"navigation":278,"path":4744,"published_at":4745,"question":273,"scraped_at":4746,"seo":4747,"sitemap":4748,"source_id":4749,"source_name":4750,"source_type":286,"source_url":4751,"stem":4752,"tags":4753,"thumbnail_url":4755,"tldr":4756,"tweet":4757,"unknown_tags":4758,"__hash__":4759},"summaries\u002Fsummaries\u002Ffe0a5dd69976e317-build-hermes-ai-agent-vps-setup-to-scaled-automati-summary.md","Build Hermes AI Agent: VPS Setup to Scaled Automations",{"provider":7,"model":8,"input_tokens":4151,"output_tokens":4152,"processing_time_ms":4153,"cost_usd":4154},8468,2608,33021,0.0029751,{"type":14,"value":4156,"toc":4720},[4157,4161,4164,4167,4198,4716],[17,4158,4160],{"id":4159},"hermes-core-five-pillars-for-self-improving-agents","Hermes Core: Five Pillars for Self-Improving Agents",[22,4162,4163],{},"Hermes Agent, an open-source project from Noose Research with 140k+ GitHub stars (MIT licensed), runs on your infrastructure (VPS, laptop, Docker, even Android via Termux). It excels at self-improvement via a loop that persists experience into memory, skills, and history. Unlike stateless LLMs, Hermes wakes with context from key files, enabling consistent, personalized behavior.",[22,4165,4166],{},"The five pillars form its foundation:",[34,4168,4169,4188],{},[37,4170,4171,4174,4175,4178,4179,4182,4183,4187],{},[79,4172,4173],{},"Memory",": Durable context across sessions via ",[26,4176,4177],{},"user.md"," (your preferences, style) and ",[26,4180,4181],{},"memory.md"," (projects, business context). Loaded at session start. Use session search (SQLite DB) for past conversations. Principle: Agents are amnesiac like in ",[4184,4185,4186],"em",{},"Memento","—feed holistic context upfront. Hermes auto-extracts\u002Fupdates these; manually reinforce with \"Chuck this into memory.md\" or \"Never do X again—add to user.md\". Avoid secrets or temp status here.",[37,4189,4190,4193,4194,4197],{},[79,4191,4192],{},"Skills",": Procedural playbooks in ",[26,4195,4196],{},"skills.md"," with YAML frontmatter for progressive disclosure (e.g., ```yaml\nwhen_to_use: \"For image generation\"",[4199,4200,4205],"pre",{"className":4201,"code":4202,"language":4203,"meta":4204,"style":262},"language-). shiki shiki-themes github-light github-dark","\n3. **Soul**: Shapes personality in `soul.md` (no YAML). Evolves with feedback for vibe (e.g., sarcastic but not rude for YouTube comments). Makes multi-agents distinct.\n\n4. **Crons**: Proactive scheduling turns reactive agent into autonomous worker. Natural language: \"Daily 6AM briefing.\" Creates isolated sessions; outputs to original chat\u002Ffiles. Flags: `context_from` chains jobs, `work_dir` for project tools, `--no-agent` for scripts. Safety: No recursive crons—prompts must be self-contained.\n\n5. **Self-Improving Loop**: Work → Learn → Persist (memory\u002Fskills\u002Fhistory) → Repeat. User corrects, saves, skill-ifies. Not magic—guide it.\n\nBonus: `agents.md` (global project goals, like Claude's `claw.md`). Use for multi-project terminal work.\n\n**Common Mistake**: Overloading context—keep files lean; let progressive disclosure handle skills. **Quality Check**: Does it repeat itself? Update memory. Feels impersonal? Tune soul.\n\n## Deployment: VPS Setup and Telegram Onboarding\n\nAssumes basic terminal comfort (SSH, git). No Mac Mini needed—use Hostinger VPS (code NATEHERK for 10% off annual).\n\n### Step 1: VPS Provisioning (16:30 timestamp)\n- Sign up Hostinger VPS (Ubuntu 24.04 recommended, 2-4 vCPU, 4-8GB RAM for Hermes).\n- SSH in: `ssh root@your-ip`.\n- Update: `apt update && apt upgrade -y`.\n- Install Docker: `curl -fsSL https:\u002F\u002Fget.docker.com -o get-docker.sh && sh get-docker.sh`.\n- Add user: `adduser hermes && usermod -aG sudo,docker hermes`.\n- Firewall: `ufw allow OpenSSH && ufw allow 80,443 && ufw enable`.\n\n### Step 2: Hermes Install\n- Switch to hermes user: `su - hermes`.\n- Clone repo: `git clone https:\u002F\u002Fgithub.com\u002FNooseResearch\u002FHermes.git && cd Hermes`.\n- Docker compose: Edit `docker-compose.yml` for models (e.g., Claude via API keys), volumes.\n- Secrets: Use `.env` for API keys (Anthropic, etc.)—**never** in memory files.\n- Start: `docker compose up -d`.\n\n### Step 3: Telegram Integration (25:30)\n- Create Telegram bot via @BotFather: Get token.\n- In Hermes web UI (http:\u002F\u002Fyour-ip:3000), onboard: Paste bot token, chat ID (msg \u002Fstart to bot, copy ID).\n- Test: Message bot—Hermes responds.\n\nHermes auto-builds initial `user.md`\u002F`memory.md` from chats. **Pitfall**: Expose only necessary ports; use Cloudflare Tunnel for security.\n\n## Skills, Crons, Backup, and Scaling\n\n### First Skill and Cron (33:00)\n- **Skill Example**: Paste Skills Hub URL: \"Install this generate-image skill.\"\n- YAML frontmatter ensures targeted loading.\n- **First Cron**: \"Create daily AI news briefing to Skool at 6AM.\" Hermes crafts cron.yaml, schedules via tools.\n\n### GitHub Backup (33:00)\n- Init repo: `git init`, add all (`git add .`), commit, remote: `git remote add origin your-repo`.\n- Cron backup: \"Daily GitHub push.\"\n- **Pro Tip**: Use Claude Code to manage multi-agent repos—sync skills\u002Fmemory across Hermes\u002FOpenClaw.\n\n### Best Practices & Security (46:30)\n- **Security**: API keys in `.env` only. Rate limits. No recursive crons. Isolate agents in subdirs.\n- **DX**: Terminal for deep work (Claude Code better); Telegram for mobile\u002Fproactive.\n- **Trade-offs**: Lighter\u002Ffaster than OpenClaw (350k stars, Nvidia NemoClaw fork); less breakage. Not for desk coding—pair with Claude.\n\n### Scaling Multiple Agents (50:30)\n- Subdirs per agent: `agents\u002Fyt-comments`, `agents\u002Fnews`.\n- Shared GitHub repo; distinct `soul.md`\u002F`memory.md`.\n- VPS: Multiple Docker instances or subdomains.\n- **Pitfall**: Context bloat—use `agents.md` for project silos.\n\n**Before\u002FAfter**: Raw request → poor video (bad spacing); feedback → Hyperframes install, polished output.\n\n**Exercise**: Install Excalidraw skill, generate pillar diagrams: \"Use Excal to diagram five pillars.\"\n\n## Comparisons and Workflow Fit\n\n| Tool | Use Case | Why Hermes? |\n|------|----------|-------------|\n| Claude Code | Desk\u002Fterminal coding (90% Nate's work) | Mobile, crons unlimited vs 15\u002Fday limit |\n| OpenClaw | Similar mobile, but heavier\u002Fbreaks more | Lighter, self-improving, OSS models ready |\n\nFits indie builders: On-the-go automations (YouTube replies, news briefs) without infra always-on.\n\n**Quotes**:\n1. \"Hermes probably understands it the best and it can also look up its own documentation so just ask it hey can you do this.\" (On troubleshooting.)\n2. \"Memory equals what to remember, skill equals how to do it again.\" (Pillar distinction.)\n3. \"Crons turn Hermes from reactive into a proactive scheduled automation.\" (Key value prop.)\n4. \"Automatic does not mean magic—the loop works best when the user corrects Hermes.\" (Self-improvement reality check.)\n\n## Key Takeaways\n- Start with VPS (Hostinger Ubuntu), Docker install Hermes, Telegram bot for instant access.\n- Prime memory\u002Fsoul files early; let Hermes auto-update but manually reinforce.\n- Build skills via hub or convos; use YAML for efficiency.\n- Schedule crons in natural language—self-contained prompts only.\n- GitHub backup everything; scale via subdirs for multi-agents.\n- Pair with Claude Code: Hermes for mobile\u002Fproactive, Claude for deep work.\n- Avoid: Secrets in MD files, recursive crons, ignoring feedback loops.\n- Test: Natural request → skill install → cron → iterate.\n- Resource: Free Skool guide for copy-paste setup.\n",").","Only loads full skill if relevant. Analogy: Recipes for consistent pancakes—prevents variability. Hermes auto-creates\u002Fpatches skills from workflows; pull 520+ from Skills Hub (e.g., Anthropic's Canvas, skill creator). Install via URL or command.",[26,4206,4207,4214,4219,4223,4228,4232,4238,4243,4249,4254,4260,4265,4271,4276,4282,4287,4293,4299,4305,4311,4317,4323,4329,4334,4340,4346,4352,4358,4364,4370,4375,4381,4387,4393,4399,4404,4410,4415,4421,4426,4432,4438,4444,4450,4455,4461,4467,4473,4479,4484,4490,4496,4502,4508,4513,4519,4525,4531,4537,4543,4548,4554,4559,4565,4570,4576,4581,4587,4593,4599,4605,4610,4616,4621,4627,4633,4639,4645,4651,4656,4662,4668,4674,4680,4686,4692,4698,4704,4710],{"__ignoreMap":262},[62,4208,4211],{"class":4209,"line":4210},"line",1,[62,4212,4213],{"emptyLinePlaceholder":278},"\n",[62,4215,4216],{"class":4209,"line":263},[62,4217,4218],{},"3. **Soul**: Shapes personality in `soul.md` (no YAML). Evolves with feedback for vibe (e.g., sarcastic but not rude for YouTube comments). Makes multi-agents distinct.\n",[62,4220,4221],{"class":4209,"line":4128},[62,4222,4213],{"emptyLinePlaceholder":278},[62,4224,4225],{"class":4209,"line":3977},[62,4226,4227],{},"4. **Crons**: Proactive scheduling turns reactive agent into autonomous worker. Natural language: \"Daily 6AM briefing.\" Creates isolated sessions; outputs to original chat\u002Ffiles. Flags: `context_from` chains jobs, `work_dir` for project tools, `--no-agent` for scripts. Safety: No recursive crons—prompts must be self-contained.\n",[62,4229,4230],{"class":4209,"line":4043},[62,4231,4213],{"emptyLinePlaceholder":278},[62,4233,4235],{"class":4209,"line":4234},6,[62,4236,4237],{},"5. **Self-Improving Loop**: Work → Learn → Persist (memory\u002Fskills\u002Fhistory) → Repeat. User corrects, saves, skill-ifies. Not magic—guide it.\n",[62,4239,4241],{"class":4209,"line":4240},7,[62,4242,4213],{"emptyLinePlaceholder":278},[62,4244,4246],{"class":4209,"line":4245},8,[62,4247,4248],{},"Bonus: `agents.md` (global project goals, like Claude's `claw.md`). Use for multi-project terminal work.\n",[62,4250,4252],{"class":4209,"line":4251},9,[62,4253,4213],{"emptyLinePlaceholder":278},[62,4255,4257],{"class":4209,"line":4256},10,[62,4258,4259],{},"**Common Mistake**: Overloading context—keep files lean; let progressive disclosure handle skills. **Quality Check**: Does it repeat itself? Update memory. Feels impersonal? Tune soul.\n",[62,4261,4263],{"class":4209,"line":4262},11,[62,4264,4213],{"emptyLinePlaceholder":278},[62,4266,4268],{"class":4209,"line":4267},12,[62,4269,4270],{},"## Deployment: VPS Setup and Telegram Onboarding\n",[62,4272,4274],{"class":4209,"line":4273},13,[62,4275,4213],{"emptyLinePlaceholder":278},[62,4277,4279],{"class":4209,"line":4278},14,[62,4280,4281],{},"Assumes basic terminal comfort (SSH, git). No Mac Mini needed—use Hostinger VPS (code NATEHERK for 10% off annual).\n",[62,4283,4285],{"class":4209,"line":4284},15,[62,4286,4213],{"emptyLinePlaceholder":278},[62,4288,4290],{"class":4209,"line":4289},16,[62,4291,4292],{},"### Step 1: VPS Provisioning (16:30 timestamp)\n",[62,4294,4296],{"class":4209,"line":4295},17,[62,4297,4298],{},"- Sign up Hostinger VPS (Ubuntu 24.04 recommended, 2-4 vCPU, 4-8GB RAM for Hermes).\n",[62,4300,4302],{"class":4209,"line":4301},18,[62,4303,4304],{},"- SSH in: `ssh root@your-ip`.\n",[62,4306,4308],{"class":4209,"line":4307},19,[62,4309,4310],{},"- Update: `apt update && apt upgrade -y`.\n",[62,4312,4314],{"class":4209,"line":4313},20,[62,4315,4316],{},"- Install Docker: `curl -fsSL https:\u002F\u002Fget.docker.com -o get-docker.sh && sh get-docker.sh`.\n",[62,4318,4320],{"class":4209,"line":4319},21,[62,4321,4322],{},"- Add user: `adduser hermes && usermod -aG sudo,docker hermes`.\n",[62,4324,4326],{"class":4209,"line":4325},22,[62,4327,4328],{},"- Firewall: `ufw allow OpenSSH && ufw allow 80,443 && ufw enable`.\n",[62,4330,4332],{"class":4209,"line":4331},23,[62,4333,4213],{"emptyLinePlaceholder":278},[62,4335,4337],{"class":4209,"line":4336},24,[62,4338,4339],{},"### Step 2: Hermes Install\n",[62,4341,4343],{"class":4209,"line":4342},25,[62,4344,4345],{},"- Switch to hermes user: `su - hermes`.\n",[62,4347,4349],{"class":4209,"line":4348},26,[62,4350,4351],{},"- Clone repo: `git clone https:\u002F\u002Fgithub.com\u002FNooseResearch\u002FHermes.git && cd Hermes`.\n",[62,4353,4355],{"class":4209,"line":4354},27,[62,4356,4357],{},"- Docker compose: Edit `docker-compose.yml` for models (e.g., Claude via API keys), volumes.\n",[62,4359,4361],{"class":4209,"line":4360},28,[62,4362,4363],{},"- Secrets: Use `.env` for API keys (Anthropic, etc.)—**never** in memory files.\n",[62,4365,4367],{"class":4209,"line":4366},29,[62,4368,4369],{},"- Start: `docker compose up -d`.\n",[62,4371,4373],{"class":4209,"line":4372},30,[62,4374,4213],{"emptyLinePlaceholder":278},[62,4376,4378],{"class":4209,"line":4377},31,[62,4379,4380],{},"### Step 3: Telegram Integration (25:30)\n",[62,4382,4384],{"class":4209,"line":4383},32,[62,4385,4386],{},"- Create Telegram bot via @BotFather: Get token.\n",[62,4388,4390],{"class":4209,"line":4389},33,[62,4391,4392],{},"- In Hermes web UI (http:\u002F\u002Fyour-ip:3000), onboard: Paste bot token, chat ID (msg \u002Fstart to bot, copy ID).\n",[62,4394,4396],{"class":4209,"line":4395},34,[62,4397,4398],{},"- Test: Message bot—Hermes responds.\n",[62,4400,4402],{"class":4209,"line":4401},35,[62,4403,4213],{"emptyLinePlaceholder":278},[62,4405,4407],{"class":4209,"line":4406},36,[62,4408,4409],{},"Hermes auto-builds initial `user.md`\u002F`memory.md` from chats. **Pitfall**: Expose only necessary ports; use Cloudflare Tunnel for security.\n",[62,4411,4413],{"class":4209,"line":4412},37,[62,4414,4213],{"emptyLinePlaceholder":278},[62,4416,4418],{"class":4209,"line":4417},38,[62,4419,4420],{},"## Skills, Crons, Backup, and Scaling\n",[62,4422,4424],{"class":4209,"line":4423},39,[62,4425,4213],{"emptyLinePlaceholder":278},[62,4427,4429],{"class":4209,"line":4428},40,[62,4430,4431],{},"### First Skill and Cron (33:00)\n",[62,4433,4435],{"class":4209,"line":4434},41,[62,4436,4437],{},"- **Skill Example**: Paste Skills Hub URL: \"Install this generate-image skill.\"\n",[62,4439,4441],{"class":4209,"line":4440},42,[62,4442,4443],{},"- YAML frontmatter ensures targeted loading.\n",[62,4445,4447],{"class":4209,"line":4446},43,[62,4448,4449],{},"- **First Cron**: \"Create daily AI news briefing to Skool at 6AM.\" Hermes crafts cron.yaml, schedules via tools.\n",[62,4451,4453],{"class":4209,"line":4452},44,[62,4454,4213],{"emptyLinePlaceholder":278},[62,4456,4458],{"class":4209,"line":4457},45,[62,4459,4460],{},"### GitHub Backup (33:00)\n",[62,4462,4464],{"class":4209,"line":4463},46,[62,4465,4466],{},"- Init repo: `git init`, add all (`git add .`), commit, remote: `git remote add origin your-repo`.\n",[62,4468,4470],{"class":4209,"line":4469},47,[62,4471,4472],{},"- Cron backup: \"Daily GitHub push.\"\n",[62,4474,4476],{"class":4209,"line":4475},48,[62,4477,4478],{},"- **Pro Tip**: Use Claude Code to manage multi-agent repos—sync skills\u002Fmemory across Hermes\u002FOpenClaw.\n",[62,4480,4482],{"class":4209,"line":4481},49,[62,4483,4213],{"emptyLinePlaceholder":278},[62,4485,4487],{"class":4209,"line":4486},50,[62,4488,4489],{},"### Best Practices & Security (46:30)\n",[62,4491,4493],{"class":4209,"line":4492},51,[62,4494,4495],{},"- **Security**: API keys in `.env` only. Rate limits. No recursive crons. Isolate agents in subdirs.\n",[62,4497,4499],{"class":4209,"line":4498},52,[62,4500,4501],{},"- **DX**: Terminal for deep work (Claude Code better); Telegram for mobile\u002Fproactive.\n",[62,4503,4505],{"class":4209,"line":4504},53,[62,4506,4507],{},"- **Trade-offs**: Lighter\u002Ffaster than OpenClaw (350k stars, Nvidia NemoClaw fork); less breakage. Not for desk coding—pair with Claude.\n",[62,4509,4511],{"class":4209,"line":4510},54,[62,4512,4213],{"emptyLinePlaceholder":278},[62,4514,4516],{"class":4209,"line":4515},55,[62,4517,4518],{},"### Scaling Multiple Agents (50:30)\n",[62,4520,4522],{"class":4209,"line":4521},56,[62,4523,4524],{},"- Subdirs per agent: `agents\u002Fyt-comments`, `agents\u002Fnews`.\n",[62,4526,4528],{"class":4209,"line":4527},57,[62,4529,4530],{},"- Shared GitHub repo; distinct `soul.md`\u002F`memory.md`.\n",[62,4532,4534],{"class":4209,"line":4533},58,[62,4535,4536],{},"- VPS: Multiple Docker instances or subdomains.\n",[62,4538,4540],{"class":4209,"line":4539},59,[62,4541,4542],{},"- **Pitfall**: Context bloat—use `agents.md` for project silos.\n",[62,4544,4546],{"class":4209,"line":4545},60,[62,4547,4213],{"emptyLinePlaceholder":278},[62,4549,4551],{"class":4209,"line":4550},61,[62,4552,4553],{},"**Before\u002FAfter**: Raw request → poor video (bad spacing); feedback → Hyperframes install, polished output.\n",[62,4555,4557],{"class":4209,"line":4556},62,[62,4558,4213],{"emptyLinePlaceholder":278},[62,4560,4562],{"class":4209,"line":4561},63,[62,4563,4564],{},"**Exercise**: Install Excalidraw skill, generate pillar diagrams: \"Use Excal to diagram five pillars.\"\n",[62,4566,4568],{"class":4209,"line":4567},64,[62,4569,4213],{"emptyLinePlaceholder":278},[62,4571,4573],{"class":4209,"line":4572},65,[62,4574,4575],{},"## Comparisons and Workflow Fit\n",[62,4577,4579],{"class":4209,"line":4578},66,[62,4580,4213],{"emptyLinePlaceholder":278},[62,4582,4584],{"class":4209,"line":4583},67,[62,4585,4586],{},"| Tool | Use Case | Why Hermes? |\n",[62,4588,4590],{"class":4209,"line":4589},68,[62,4591,4592],{},"|------|----------|-------------|\n",[62,4594,4596],{"class":4209,"line":4595},69,[62,4597,4598],{},"| Claude Code | Desk\u002Fterminal coding (90% Nate's work) | Mobile, crons unlimited vs 15\u002Fday limit |\n",[62,4600,4602],{"class":4209,"line":4601},70,[62,4603,4604],{},"| OpenClaw | Similar mobile, but heavier\u002Fbreaks more | Lighter, self-improving, OSS models ready |\n",[62,4606,4608],{"class":4209,"line":4607},71,[62,4609,4213],{"emptyLinePlaceholder":278},[62,4611,4613],{"class":4209,"line":4612},72,[62,4614,4615],{},"Fits indie builders: On-the-go automations (YouTube replies, news briefs) without infra always-on.\n",[62,4617,4619],{"class":4209,"line":4618},73,[62,4620,4213],{"emptyLinePlaceholder":278},[62,4622,4624],{"class":4209,"line":4623},74,[62,4625,4626],{},"**Quotes**:\n",[62,4628,4630],{"class":4209,"line":4629},75,[62,4631,4632],{},"1. \"Hermes probably understands it the best and it can also look up its own documentation so just ask it hey can you do this.\" (On troubleshooting.)\n",[62,4634,4636],{"class":4209,"line":4635},76,[62,4637,4638],{},"2. \"Memory equals what to remember, skill equals how to do it again.\" (Pillar distinction.)\n",[62,4640,4642],{"class":4209,"line":4641},77,[62,4643,4644],{},"3. \"Crons turn Hermes from reactive into a proactive scheduled automation.\" (Key value prop.)\n",[62,4646,4648],{"class":4209,"line":4647},78,[62,4649,4650],{},"4. \"Automatic does not mean magic—the loop works best when the user corrects Hermes.\" (Self-improvement reality check.)\n",[62,4652,4654],{"class":4209,"line":4653},79,[62,4655,4213],{"emptyLinePlaceholder":278},[62,4657,4659],{"class":4209,"line":4658},80,[62,4660,4661],{},"## Key Takeaways\n",[62,4663,4665],{"class":4209,"line":4664},81,[62,4666,4667],{},"- Start with VPS (Hostinger Ubuntu), Docker install Hermes, Telegram bot for instant access.\n",[62,4669,4671],{"class":4209,"line":4670},82,[62,4672,4673],{},"- Prime memory\u002Fsoul files early; let Hermes auto-update but manually reinforce.\n",[62,4675,4677],{"class":4209,"line":4676},83,[62,4678,4679],{},"- Build skills via hub or convos; use YAML for efficiency.\n",[62,4681,4683],{"class":4209,"line":4682},84,[62,4684,4685],{},"- Schedule crons in natural language—self-contained prompts only.\n",[62,4687,4689],{"class":4209,"line":4688},85,[62,4690,4691],{},"- GitHub backup everything; scale via subdirs for multi-agents.\n",[62,4693,4695],{"class":4209,"line":4694},86,[62,4696,4697],{},"- Pair with Claude Code: Hermes for mobile\u002Fproactive, Claude for deep work.\n",[62,4699,4701],{"class":4209,"line":4700},87,[62,4702,4703],{},"- Avoid: Secrets in MD files, recursive crons, ignoring feedback loops.\n",[62,4705,4707],{"class":4209,"line":4706},88,[62,4708,4709],{},"- Test: Natural request → skill install → cron → iterate.\n",[62,4711,4713],{"class":4209,"line":4712},89,[62,4714,4715],{},"- Resource: Free Skool guide for copy-paste setup.\n",[4717,4718,4719],"style",{},"html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"title":262,"searchDepth":263,"depth":263,"links":4721},[4722],{"id":4159,"depth":263,"text":4160},[272],{"content_references":4725,"triage":4741},[4726,4730,4734,4737,4739],{"type":3966,"title":4727,"author":4728,"url":4729,"context":3969},"Hermes Agent","Noose Research","https:\u002F\u002Fgithub.com\u002FNooseResearch\u002FHermes",{"type":3966,"title":4731,"url":4732,"context":4733},"Hostinger VPS","https:\u002F\u002Fwww.hostinger.com\u002Fvps\u002Fclaude-code-hosting","recommended",{"type":3966,"title":4735,"author":4736,"context":3969},"Claude Code","Anthropic",{"type":3966,"title":190,"author":4738,"context":3969},"Peter Steinberger",{"type":3966,"title":4740,"context":3969},"Skills Hub",{"relevance":4043,"novelty":3977,"quality":3977,"actionability":4043,"composite":4742,"reasoning":4743},4.55,"Category: AI Automation. The article provides a detailed, step-by-step guide on deploying the Hermes AI Agent, which directly addresses the audience's need for practical applications in AI automation. It includes specific instructions for setting up and scaling the agent, making it immediately actionable for builders.","\u002Fsummaries\u002Ffe0a5dd69976e317-build-hermes-ai-agent-vps-setup-to-scaled-automati-summary","2026-05-10 02:42:25","2026-05-10 15:22:01",{"title":4149,"description":262},{"loc":4744},"c931d1c171f90d29","Nate Herk | AI Automation","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=gb5TlGw6Uks","summaries\u002Ffe0a5dd69976e317-build-hermes-ai-agent-vps-setup-to-scaled-automati-summary",[290,291,4754,293],"automation","https:\u002F\u002Fi.ytimg.com\u002Fvi\u002Fgb5TlGw6Uks\u002Fhqdefault.jpg","Follow this step-by-step guide to deploy Hermes Agent on a VPS, integrate Telegram, create skills\u002Fcrons, backup to GitHub, and scale multiple agents for proactive AI assistance.","A hands-on 1-hour screen-share tutorial deploying open-source [Hermes Agent](http:\u002F\u002Fhostinger.com\u002Fnatehermes) to a [Hostinger VPS](https:\u002F\u002Fwww.hostinger.com\u002Fvps\u002Fclaude-code-hosting), connecting it to Telegram, adding your first skill and cron job, GitHub backup, plus comparisons to Claude Code\u002FOpenClaw and scaling tips.",[293],"b8Xn0iSSv145vSBXaAH2EG_xEHHkVmAAxa37Nzr0iH8"]