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With AI building features, teams must shift from doing tasks to orchestrating them - PMs guide intent, engineers oversee systems, designers review output live, and QA builds self-healing processes.

When teams don’t share information, clash on priorities, or follow unclear processes, even simple tasks can drag on for months.

Building with LLMs is nothing like traditional software. If we want something that actually works in production, we have to test it, monitor it, and keep iterating on real customer data.

We’re past just making better tools: machines will do the repetitive coding, and humans will focus on guiding, judging, and architecture.

Ex-Tesla AI director now programs mostly in plain English with AI, calling it the biggest workflow change in 20 years.

Until now, AI could only advise and plan, never act. But MCP is finally letting it bridge the gap between thinking and doing.

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