A multi-tool AI co-pilot built — and run in production for 12+ months — to handle the recurring ops queue. Same architecture we deliver on the AI Co-pilot tier.
Running a small consultancy meant 30+ recurring ops tasks eating evening hours: backup audits, scraper health checks, log triage, GitHub repo sweeps, EA backtest summaries, Telegram triage. None of them complex on their own — collectively, they consumed 6–8 hours every week.
Hiring an ops person wasn't justified at this scale. The right answer was a multi-tool AI co-pilot — but the off-the-shelf AI products that existed in 2025 were either too narrow (single-purpose chatbots) or too dangerous (general agents with full shell access and no guardrails). So we built one.
Front-end: Telegram bot, because that's where the operator already lives all day. No new UI to learn, no new tab to keep open.
Planner: Anthropic Claude as the reasoning layer — chosen for tool-use reliability and the ability to refuse ambiguous instructions instead of guessing.
Tool layer: a tightly scoped allowlist of shell commands and Python scripts. Anything destructive (file delete, repo force-push, system service restart) requires explicit operator confirmation in chat.
Permission model: two protected paths the agent can never touch, regardless of instruction — written into the system prompt AND enforced at the tool layer. Belt and braces.
Zero unauthorised actions in 12 months of operation. The permission boundary has caught the agent attempting to touch protected paths twice — both times it correctly stopped and asked for confirmation, exactly as designed.
"I built the first version as a weekend proof. A year later it's still the thing that runs my ops queue every morning. The architecture we now offer clients on the AI Co-pilot tier is the exact same one — battle-tested first on my own work."
— Founder, GetWebLabs