What if the best way to get more from AI is to spend more time planning before you start?
In this episode of Decoding a Sane Mind, we sit down with Adam Rehman, Venture Builder at Noygear, to explore how better planning can help people use AI to dramatically improve productivity. Learn why simply giving AI a task is not enough, how front-loading your instructions can lead to better results, and why reviewing AI-generated work becomes even more important as these tools become more capable.
You'll also hear practical ideas for building AI workflows, running tasks more autonomously, organizing context, and using one AI model to review the work of another. Adam shares how he plans complex tasks before handing them to AI, how an autonomous coding run produced around 40 pull requests, and why clear instructions and structured review can save hours of active work.
In this episode, you'll learn:
Why better AI productivity starts with planning before execution
How front-loading context and instructions can reduce repeated back-and-forth
Why AI-generated work still needs careful review and validation
How AI tools have improved at building financial models and spreadsheets
Why strong-looking AI outputs can make careful auditing even more important
How Adam used AI to complete around 40 pull requests in one autonomous run
How a second AI model can help review and improve the first model's work
How tools like Claude, ChatGPT, Codex, and Obsidian fit into Adam's AI workspace
Why keeping your AI context accurate and up to date matters
How better planning can free up time for higher-value work
Adam also shares how growing up in Washington, D.C., attending Montessori and bilingual schools, studying finance with a minor in real estate at Tulane University, and taking on unfamiliar challenges helped shape his curiosity and approach to learning. He also reflects on the influence his mother has had on the analytical way he approaches problems and life.
Whether you are exploring AI for business, finance, engineering, or everyday productivity, this conversation offers practical ways to plan better, build stronger AI workflows, and get more useful results while keeping human review at the center of the process.
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