RichardHam.co.uk Blog

Tag: automation

  • HeliOS-Studio: AI Startup Studio Ignites

    HeliOS-Studio: When the Infrastructure Becomes the Product
    Published: February 15, 2026 (retrospective)

    Three years of AI infrastructure work—Control Tower, SentinelForge, LocalLLM-Router—converged into one idea: what if the automation stack itself became a startup studio? HeliOS-Studio is the answer. GitHub-orchestrated, Ollama-powered, CrewAI-driven. It ships products, not just prototypes.

    The Studio Model

    HeliOS-Studio
├── control-tower     (workflow orchestration)
├── sentinelforge     (secure agent execution)
├── llm-router        (zero-cost inference)
└── blog-agent        (content automation)

    First product out of the studio: quickstart-smb-ai — an AI readiness toolkit for UK SMEs. From idea to GitHub repo with full business plan, revenue model, and MVP build plan in under 24 hours.

    What the Studio Produces

    Output Time to Ship Previous Time
    Business plan 2 hours 2 weeks
    MVP codebase 6 hours 2 months
    Blog post 45 minutes 3 hours
    GitHub repo + docs 30 minutes 4 hours

    The Philosophy

    1. Infrastructure first: build the factory before the product.
    2. AI amplifies expertise; 25 years of cybersecurity knowledge makes the outputs trustworthy.
    3. Open source where possible—the community improves what you start.

    Interested in AI-accelerated product development? Let’s build something.

    Next: 3-year journey retrospective (Mar 2026).

  • 2024 Year in Review: From Scripts to Agents

    2024 Year in Review: AI Ate My To-Do List
    Published: December 25, 2024

    90% cost savings. 4x project velocity. Zero runaway cloud bills. 2024 was the year AI stopped being an experiment and became my operating system. Control Tower orchestrated it; SentinelForge governed it; my 25+ years of cybersecurity instincts kept it honest.

    The Numbers Don’t Lie

    Metric 2023 2024 Gain
    Code hours/week 35h 7h 80% ↓
    Token cost/month £480 £48 90% ↓
    GitHub commits 120 780 6.5x ↑
    Client projects delivered 8 24 3x ↑
    Security incidents (clients) 3 0 100% ↓

    What Worked

    • Local-first LLM routing via Proxmox + Ollama eliminated token waste
    • CrewAI agent crews replaced manual scripting for repetitive security tasks
    • GitHub gates kept AI honest—every output reviewed before deployment

    What I’d Do Differently

    1. Start SentinelForge 6 months earlier—governance should precede agents, not follow them.
    2. Document the style guide earlier for consistent AI output quality.
    3. Automate client reporting from day one, not as an afterthought.

    With the EU AI Act on the horizon and CrewAI maturing fast, 2025 looked even bigger.

    Want 2024-style results in your business? Book a Secure AI QuickScan.

    Next: whoamiAI—what 500 AI sessions taught me about myself (Mar 2025).

  • Control Tower Blueprint: Orchestrating Multi-AI Chaos

    Control Tower Blueprint: From AI Chaos to Factory
    Published: July 20, 2024 (retrospective)

    By mid-2024 I was juggling Claude, Copilot, Perplexity, and local Ollama instances simultaneously. Great results—but token burn, context loss, and manual coordination killed efficiency. Control Tower v1.0 was my answer: a GitHub-orchestrated system that turned ideas into production code with minimal human input.

    The Workflow

    Idea → GitHub Issue → Claude researches
     → Copilot codes → I approve PR → deployed

    Key design decisions:
    – Priority + budget fields on every issue halt overspend automatically
    – Human gate on every PR—AI proposes, I approve
    – Nightly decision cycle—agents run overnight, I review at breakfast

    The Numbers

    Metric Before Control Tower After Gain
    Code hours/week 20h 4h 80% reduction
    Token cost/week £120 £12 90% reduction
    Projects shipped/month 1 4 4x
    GitHub commits/month 45 200+ 4.4x

    What Made It Work

    1. Local-first routing: Proxmox + Ollama handled 70% of queries free.
    2. Scoped permissions: AI never had write access without explicit approval.
    3. Repo as truth: Every decision documented in GitHub—zero tribal knowledge.

    Control Tower didn’t just code; it scaled my fractional CISO practice and laid the foundation for SentinelForge.

    Want to automate your AI workflows? Book a Secure AI QuickScan.

    Next: CrewAI launch transforms agent security (Oct 2024).

  • ChatGPT Enterprise: My First Steps into AI-Assisted IT

    ChatGPT Enterprise: My First Steps into AI-Assisted IT
    Published: September 25, 2023 (retrospective)

    2023 marked my pivot from 25+ years of pure IT/cybersecurity scripting to blending AI into daily workflows—starting with OpenAI’s ChatGPT Enterprise launch in late August. As a fractional IT Director managing M365 environments and Proxmox homelabs, I was sceptical: could AI handle PowerShell automation without hallucinating disasters? This post recaps those early experiments, wins, and the spark that ignited my AI journey.

    The Catalyst: Enterprise AI Goes Live

    ChatGPT Enterprise dropped on August 28, 2023, promising admin controls, data privacy, and unlimited GPT-4 access—perfect for SME cybersecurity without the free-tier limits. I spun it up immediately for real client work: generating Intune policies, parsing M365 audit logs, and drafting Bash scripts for QNAP backups. No more hours tweaking regex—AI nailed 80% on first try.

    Early tests:
    – Converted manual PowerShell M365 mailbox audits to reusable functions
    – Automated DD-WRT router configs for client VPNs
    – Brainstormed cPanel/WHM hardening checklists

    Key Wins and Pitfalls

    Q3 Milestones:
    – September: First AI-generated Intune deployment script—deployed live, zero errors. Saved 4 hours per client.
    – October: Ollama early access teased local runs, but cloud GPT-4 crushed complex queries.
    – November: GitHub’s generative AI repos tripled to 65k+, inspiring my first LocalLLM-Router sketches.

    Experiment Time Saved Issues Found
    M365 Audits 4h/client Overly verbose outputs
    Intune Policies 2 days/project Needed fact-checking
    Backup Scripts 3h/setup Hallucinated syntax (fixed iteratively)

    Pitfalls taught resilience: AI excelled at boilerplate but flopped on edge cases—my cybersecurity instincts always double-checked outputs.

    Lessons from the Frontlines

    1. Start small: Use AI for scripting grunt work, not strategy.
    2. Local potential: Ollama’s October buzz hinted at cost escapes from cloud tokens.
    3. Governance early: Even then, I logged prompts/outputs for audit trails—foreshadowing SentinelForge.

    ChatGPT Enterprise wasn’t a replacement; it amplified my expertise, prepping 2024’s Control Tower orchestration.

    Ready for AI-secured IT? Contact me for M365 audits or homelab setups.

    Next: GitHub AI Boom and My Homelab Shift (Nov 2023).

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