Agentic Infra Notes

Sanitized engineering notes on AI-assisted infrastructure, agentic workflows, LLMOps, and self-hosted automation control planes.

This repository documents architecture thinking, operating principles, safety boundaries, and workflow patterns from private R&D work. It does not expose production source code, credentials, private prompts, real endpoints, customer data, internal workflow exports, proprietary routing logic, or unpublished model weights.

Scope

This repository focuses on:

• AI-assisted engineering workflows
• Multi-agent development systems
• Self-hosted automation control planes
• Local AI/dev infrastructure
• Local fine-tuning infrastructure experiments
• Human-in-the-loop execution boundaries
• LLMOps observability and cost control
• Agentic workflow safety and operational review

Private R&D referenced

The following private projects are referenced only through sanitized notes:

• Agents-Core — multi-agent engineering workflow fabric
• Aegis-Forge — self-hosted AI engineering control plane
• Local-Core — local AI/dev infrastructure workspace
• BOTAIO — private AI-assisted R&D exploration around n8n workflow automation and local model fine-tuning
• OpenClaw / ZeroClaw Research — agentic systems risk review and isolated execution research
• n8n workflow patterns — reusable automation patterns with explicit safety boundaries
• Trustlayer — private product/R&D exploration, intentionally limited here

Documentation map

• private-rd/project-index.md
• case-studies/agents-core.md
• case-studies/aegis-forge.md
• case-studies/local-core.md
• case-studies/botaio-n8n-finetuning-lab.md
• model-cards/qwen2.5-coder-32b-n8n-finetune.md
• research/openclaw-zeroclaw-risk-review.md
• patterns/n8n-workflow-automation-patterns.md
• checklists/agentic-development-safety-checklist.md
• checklists/llmops-observability-checklist.md
• SECURITY.md

Disclosure boundary

This repository intentionally excludes:

• source code from private projects
• real system prompts or private instruction chains
• credentials, tokens, keys, cookies, or .env files
• real service endpoints, IP addresses, hostnames, ports, or internal URLs
• customer data or customer-specific workflows
• production architecture diagrams with implementation-level details
• exact model routing rules
• provider API keys, cost ledgers, or private usage data
• production n8n workflow exports
• private datasets and unpublished model weights
• exact local filesystem paths
• proprietary implementation details

Engineering principles

• Prefer reproducible setups over manual configuration.
• Keep automation observable, reviewable, and reversible.
• Separate planning, execution, review, and operational ownership.
• Use local or lower-cost models for routine tasks where safe.
• Reserve stronger models for reasoning-heavy work.
• Require human approval for destructive, credential-related, financial, production, or externally visible actions.
• Treat context, cost, memory, hardware/runtime compatibility, and operational risk as first-class engineering constraints.

Status

Active notes repository. Content is intentionally sanitized and incomplete by design.