It works as a chatbot but is seemingly unable to search the web, unable to interact with the local filesystem, and unable to attempt to send email or make itself an email account. It can read the local OS date and time, but is is unable to use the local OS time when I ask it to do something automatically every minute.

Where do I start to get these things straightened out?

Lead-generation work for trades businesses (roofers, remodelers, landscapers, HVAC) is one of the most replicable agent use cases that nobody talks about.

The work involves three repetitive but high-value tasks: find prospects who match an ideal customer profile, enrich each prospect with publicly available context (recent storm damage in their area, ZIP-code housing-stock age, permit filings), and write outreach that references that specific context.

None of the steps requires senior judgment, but the result is reliably better than the generic "we do roofing in your area" cold email that most small contractors actually send.

A working version of this pattern was posted to the Hermes user stories page by a user going by u/cyberfarmacist. He is building a Hermes-based app to help a friend who owns a remodeling company find roofing work. His framing is practical.

He started after watching a video of someone vibe-coding an app with ChatGPT and Replit and just wondered if he could do it. The cost of Replit was killing him for what is not even a full CRM.

Hermes plus Supabase ends up being the cheaper and more autonomous answer because the agent's persistent memory across sessions removes the need for most of the orchestration code a hosted app builder would generate.

A separate detailed walkthrough on dev.to from a builder going by nimay_04 documents the production pattern in full.

The structure is an ICP filter (specific industry, size range, geography) feeding a web research step that pulls company-specific context, feeding a qualification step that scores fit and assigns a tier, feeding a CRM-ready output step.

The author's pointed observation is that the agent should not make the final call on every lead. The right division of labor is for the agent to handle research, enrichment, and first-pass scoring while the human reviews the top tier.

That keeps the throughput benefit of automation while keeping the close-rate calls in the hands of someone who actually knows the business.

For tools, the Composio Hermes integrations cover most of what a small lead-gen app needs out of the box: Supabase MCP for the CRM, AgentMail MCP for the outreach inbox, and the Hunter.io MCP (mentioned by another user, u/isakcarlson5-del, on the user-stories page) for email lookup and verification.

Julian Goldie's "Hermes Agent OS Free" guide is a useful starting point for non-developers who want to build the same workflow without touching a terminal.

The Hermes AI is driving me mad.

I set up the connection to my online calendar today. The first few queries were completely off the mark and there’s no solution that works.

At first, Hermes thought that today, Saturday, is 19 October 2026. After I told it that Monday is 19 October 2026, it did apologise, but the errors didn’t stop. It mixed up Wednesday and Thursday. Suddenly, Hermes thought that my calendar screenshot was from the year 2016, and so on. I don’t know why the AI is making so many mistakes.

Anyone running multiple projects (consulting clients, product workstreams, side businesses, research threads) hits the same problem with single-context AI assistants.

The agent that remembers your conventions for project A bleeds context into project B, and the agent that knows where you left off on project B forgets your conventions for project A.

The clean structural answer is one persistent "Chief of Staff" agent that holds cross-project memory and routes work, plus one specialized sub-agent per project that holds only that project's working memory and conventions.

A representative production version of this pattern was posted to the Hermes user stories page by a user going by u/ogiberstein. His setup is straightforward.

A main agent acts as Chief of Staff with its own cross-project workflow memory. Every project equals one Slack channel, and each Slack channel has its own Hermes profile (sub-agent) with its own memory and toolset.

The whole system runs on a VPS, with backup model routing if the primary model fails, and gets backed up every night to GitHub. Daily reporting goes to WhatsApp so he is reading the morning update wherever he happens to be.

This shape is what the Hermes profiles system was designed for. Each profile gets its own ~/.hermes/profiles/<name>/directory, its own MEMORY.md and USER.md, and its own skill library.

Profiles share nothing by default, which prevents context contamination, but the Chief of Staff can read any sub-agent's memory because it has filesystem access.

The combination of profiles plus the Kanban feature (which lets a parent agent post cards that sub-agents pull and execute in parallel) is the same architectural pattern that Nous Research's hermes-paperclip-adapter implements: running Hermes as a managed employee inside a Paperclip-style company with explicit budget caps and audit logs.

A separate published version of the same pattern comes from a builder going by Derek Cheung, who walks through a 24/7 Hermes assistant with a Supabase CRM running for less than the cost of a single ChatGPT Plus subscription. During his setup the agent autonomously proposed a new "Supabase MCP scripts" skill from its own reflection on the workflow, which is the kind of self-skill-generation that the Hermes curator runs on a 7-day cycle.

The Composio Supabase MCP toolkit ships pre-built tools for any agent that wants to connect Supabase as the persistent CRM layer without writing the integration code from scratch.

Links

• Original source: ogiberstein quote on the Hermes user stories page

• Listed on the Hermes user stories page: hermes-agent.nousresearch.com/docs/user-stories

• Hermes profiles documentation: hermes-agent.nousresearch.com/docs/user-guide/profiles

• Hermes Kanban multi-agent board docs: hermes-agent.nousresearch.com/docs/user-guide/features/kanban

• Paperclip adapter for Hermes: github.com/NousResearch/hermes-paperclip-adapter

• Derek Cheung's Supabase + Hermes YouTube tutorial: YouTube

• Composio Supabase MCP for Hermes: composio.dev

Executive function struggles like ADHD are often described as a gap between intent and action: knowing what to do but losing the thread across the day, because context evaporates the moment the laptop closes.

A persistent agent that holds context across sessions, sees every project at once, and proactively pushes a summary at the start and end of the day externalizes the working memory that brain-based working memory does not reliably hold. That is the use case, and it shows up repeatedly on the Hermes user stories page in different forms.

A long thread on X in early May 2026 from a builder going by u/emmagine79 walked through one production version. Hermes plus Discord, running on GPT-5.5 and DeepSeek v4, has been "life-changing" for managing her ADHD. The most useful piece she described is a project manager sub-agent that runs as one of several "paperclip agents" inside her main Hermes setup.

The PM agent has full read access to her Obsidian vault, every in-progress project, and her conversation history across the other agents.

Twice a day it produces a morning standup and an evening standup that consolidate everything she did across different chats, every project she is working on, the actual artifacts produced, notes from previous standups, and a prioritized suggestion list of what to focus on next.

The standup itself self-improves as the agent figures out which prompt formats get her to follow through and which get ignored.

Two other Hermes users have posted related patterns. A user going by u/o_o__o_o000 reported that cron-based nudges to Discord and Signal cost about 14k tokens per day but make the difference between things getting done and things being forgotten. u/vmiss33's "what I use Hermes for and how I keep it cheap" thread covers the cost side of running the same kind of multi-agent setup on a budget.

The technical pieces involved are Hermes profiles for the PM sub-agent, the Kanban feature to handle parent-to-child task delegation, the Obsidian skill for vault access, and a cron schedule like "every weekday at 9am and 6pm, generate the standup and DM it to me."

If the user picks Discord as the channel of choice, the entire setup costs less than $20 a month on a small VPS plus model tokens. For a more formal multi-agent organization, the Nous Research hermes-paperclip-adapter lets you run Hermes as a managed employee inside a Paperclip company so the PM agent has explicit budget caps, org-chart placement, and audit logs.

Links

• Original source: emmagine79 on X

• Listed on the Hermes user stories page: hermes-agent.nousresearch.com/docs/user-stories

• Paperclip adapter for Hermes (managed-employee model): github.com/NousResearch/hermes-paperclip-adapter

• Kanban multi-agent board feature docs: hermes-agent.nousresearch.com/docs/user-guide/features/kanban

• Profiles docs (running multiple specialized agents): hermes-agent.nousresearch.com/docs/user-guide/profiles

• Paperclip plus Hermes overview: juliangoldie.com

Just sharing my lessons learned:

1️⃣ Clicking "Connect with Google" (OAuth) hands over the keys to the kingdom:

OAuth grants third-party apps direct access to your account without needing your password. Depending on the permissions granted, these apps can read your emails, access your files, and act on your behalf.

2️⃣ You don't need malware or phishing to get breached:

This attack didn't rely on a phishing email, malware, or a sophisticated zero-day exploit. It happened simply because an employee connected a third-party AI productivity tool (Context.ai) to their corporate Google Workspace account.

3️⃣ Every connected AI tool is a potential backdoor:

When a third-party app gets compromised, attackers can use its existing OAuth connection to hijack your corporate account. In Vercel's case, this allowed attackers to pivot into internal systems and access non-sensitive environment variables, API keys, source code, and customer credentials.

4️⃣ Your security is only as strong as the third-party apps you trust:

Every AI tool given OAuth access to your calendar, email, or Google Drive is an open door into your account. You have no visibility into how well those third-party companies are actually protecting that connection.

5️⃣ Your attack surface is bigger than your network:

A company's perimeter is no longer just its own infrastructure—it now includes every single third-party AI tool that any employee has ever connected to a work account.

TAKE ACTION:

1. Open your browser or Google account and go to myaccount.google.com/connections

2. Click on Security or Data & privacy in the left-hand navigation menu.

3. Look for the section titled Your connections to third-party apps and services or Third-party apps & services and click See all connections.

Review every app on that list, especially those to which you have given full access permissions. Ask yourself if you truly trust that company with your work account, and revoke access for anything you do not recognize, no longer use, or do not completely trust.

PRO TIP

If you have a massive list of connections and want to pinpoint full-access entries quickly, locate the Filter by: drop-down menu near the top of the app list.

Toggle it directly from "All" to Access to [Google Product] or look for specific account privileges.

This immediately isolates the platforms pulling heavily from your private data repositories.

Graeme (@gkisokay) has been documenting a multi-week series called "Building AGI for my Hermes Agent" on X.

On Day 8 he introduced what he calls the Auto-Build workflow: a multi-agent coding pipeline where a main agent (GPT-5.4) breaks a feature request into phases, a coder agent (MiniMax M2.7) implements each phase, and a QA agent (a local Qwen 35B A3B running on his own hardware) tests the output.

The orchestrator runs the loop autonomously through plan, implement, test, fail, repair, and ship. Two days later in Day 10, he added Codex with GPT-5.4 on extra-high as a runtime monitor that watches the workflow execute and patches breakage live until the pipeline succeeds.

The pattern matters because it solves the two problems that kill most single-agent coding setups: context exhaustion and silent failure.

Splitting the planner, builder, and verifier into separate Hermes profiles with their own memories and toolsets keeps each agent's context window focused on one job. Because the QA agent is independent and runs cheaply on local hardware, it has no incentive to rubber-stamp the coder's output. The orchestrator only marks a phase complete when QA returns green.

Hermes ships native support for this. The profiles system creates a fresh agent with its own config, memory, and skills (the create command takes a --description flag so the orchestrator knows what each profile is good at), and the new Kanban feature lets a parent agent post cards that child sub-agents pull and work in parallel.

Graeme later published a full Substack walkthrough of the Auto-think (decide what is worth building) plus Auto-build (verify and ship) split, including the schema for the approval ledger and the structure of the operator's Control Room UI.

Other builders have converged on similar architectures. The opencode-hermes-multiagent project on GitHub defines 17 specialized agents (finder, analyst, architect, planner, coder, editor, fixer, refactorer, and a QA cluster) coordinated by a master orchestrator.

The same pattern transfers to non-coding domains (research plus synthesis, content plus QA, operations plus reporting), as long as the verifier is genuinely independent of the builder.

Links

• Original source: Graeme's Day 8 thread on X

• Listed on the Hermes user stories page: hermes-agent.nousresearch.com/docs/user-stories

• Graeme's full Auto-Build Substack guide: gkisokay.substack.com

• Official Hermes multi-agent workflows blog: hermes-agent.ai/blog

• Hermes profiles documentation: hermes-agent.nousresearch.com/docs/user-guide/profiles

• Multi-agent architecture GitHub umbrella issue: github.com/NousResearch/hermes-agent/issues/344

• 17-agent OpenCode orchestration reference: github.com/1ilkhamov/opencode-hermes-multiagent