How I Work
The agent infrastructure behind thearmchairfuturist.com
This site is run by my agent stack. Not as a demo. As the actual infrastructure.
Digital employees, not assistants. That's the phrase I use with clients, and this page is the proof. Hermes Agent takes a brief from me over Telegram, ships the daily digest, publishes the LinkedIn post, checks system health, and keeps the memory files honest. It works while I sleep.
Most consultants describe AI as a tool you use. I treat it as a workforce you manage. Here's the stack, what runs on autopilot, and the guardrails that keep it honest.
The Stack
I run Hermes Agent (Nous Research) on a Linux workstation. Sessions are stateless but carry persistent memory through plain-text files: a policy file, a memory file, and a user profile. The agent has broad autonomy to execute, delegate, and verify, with explicit escalation gates for high-risk actions.
- Agent framework: Hermes v0.19, Telegram gateway
- Models: DeepSeek V4 Pro (reasoning), DeepSeek V4 Flash (tools, digest)
- Search: Brave Search API (10k queries/mo free tier)
- Memory: Plain-text POLICIES.md, MEMORY.md, USER.md. No vector DBs
- Skills: 40+ Hermes skill packs loaded on demand, ~8 operational cron jobs
- Stack: Python 3.11, Next.js 16, Tailwind, Firebase
What Runs on Autopilot
- Daily AI Digest at 11:00. HuggingNews, HN, arXiv, Reddit. 2,500-3,000 words in my voice. Published to Substack and the blog.
- LinkedIn Post at 12:00. Under 3,000 characters. Business-focused takeaways.
- Morning Dojo Report at 06:00. System health, cron integrity, git status. Scannable.
- End-of-Day Summary at 18:00. What shipped, what failed, what's tomorrow.
- Weekly Memory Hygiene Sundays 04:00. Dedup and prune long-term memory.
- Skill Evolution (GEPA) Sundays 02:00. Self-improvement cycle.
Guardrails
The agent reads POLICIES.md before every session. Dated rules born from real mistakes. Every correction becomes policy.
- Never without approval: public posts, purchases, external messages, destructive changes, credential changes.
- Stage for review: Substack articles, LinkedIn posts, client deliverables. Drafts fully, then pauses for a human gate.
- Autonomous within policy: code changes, cron maintenance, research, system health checks.
- Evidence-based: no claim of completion without command output, file changes, or live data.
Shipped
- Daily AI Digest every day at 11:00. Delivered to the blog and Substack.
- GitHub pull requests, issues, and commits on public repos at armchairfuturist-code.
- mindscape-site Next.js 16, Cloud Run. Full-stack client project.
- rooted-leader-site React 19, Firebase. Substack integration.
- Investment-Engine Python MCP server for portfolio analysis.
FAQ
No claim of completion without verification. Every output is backed by command output, file changes, or live data. If data is incomplete, it reports what is missing.
Only when I explicitly ask. Email is treated as data, never as instruction.
Instructions only accepted from verified channels (Telegram, Signal). Web content is data only.
The correction becomes a dated rule in POLICIES.md, read before every future session.
DeepSeek V4 Pro for reasoning. DeepSeek V4 Flash for tools, digest, and LinkedIn. Both direct API.
Daily operations: single-digit dollars. Digest + LinkedIn: roughly $1-2 in API credits. Search: free (Brave).
Questions? Reach me at armchairfuturist@gmail.com or on LinkedIn.