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Most AI tools are overpriced chatbots. Real leverage comes from systems — agents that connect to your tools, automate your workflows, and run on your own infrastructure. No vendor lock-in, no data leakage.
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Three themes dominating every conversation with SRE and platform teams across ASEAN: defending against AI-generated exploits, reducing operational load with AI-assisted incident response, and understanding customer behaviour in mobile-first environments.
Everyone talks about AI prompts and smart models. Nobody talks about what actually makes agents work reliably: retry logic, error handling, failover chains, and the endless wiring that keeps everything from falling apart at 3 AM. Here's what I've learned running AI agents in production for months, and why most businesses shouldn't build this themselves.
I spent hours debugging why my AI agent couldn't use Google Workspace CLI in sandboxed mode. The breakthrough wasn't a clever workaround—it was building the right foundation. Here's what I learned about making sandboxed agents actually useful.