We Simulate Rockets. Why Not Our Lives? | Alissa Voutova of newl

What we talked about.

Sunny Ray talks with Alissa Voutova of newl about why people rehearse rockets and ad campaigns but not their own lives. Alissa spent about ten years in advertising planning for brands such as LEGO, Kellogg's and Heineken, replanning strategies repeatedly to maximize return on multi-million budgets. When she relocated from London to Bangkok, she found that a pros and cons list and chats with friends were her only decision tools. That gap led her to build newl, short for new life, which lets people pre-experience a possible future through simulation. She explains how she tested the idea with a manual pilot of 15 to 20 people recruited on LinkedIn, and how that pilot shaped the five wealths framework and a feature for chatting with a future self. Sunny pushes on how such predictions can be trusted, and Alissa describes her causal inference approach, small real-world experiments, and longitudinal data. The conversation closes with where listeners can find newl, which is currently live with career simulations.

We model rockets and cereal campaigns to death, yet make life's biggest choices with a pros and cons list. Alissa Voutova wants to change that.

The questions, and the answers.

What problem is newl solving?

We simulate big, expensive systems all the time, but we have no way to rehearse the most consequential system of all, our own lives. Before relocating, starting a business or launching a podcast, people wish they could see how each path might feel. newl lets you try on a new life in a simulation before you commit to it.

What did corporate scenario planning teach you that career decision tools were missing?

I spent about ten years planning ad campaigns for brands like LEGO, Kellogg's and Heineken. I once replanned one brand's strategy about 16 times to maximize return. Then I moved from London to Bangkok and my tools were a pros and cons list, some online research and chats with friends. That felt far too rudimentary for such a big decision.

How did you find the first people willing to test newl before there was software?

I went on LinkedIn and simply asked people if they wanted to be part of this crazy experiment. I targeted people considering career changes or relocations. I ran a manual pilot with about 15 to 20 people. Doing it by hand showed me how the simulation should work and what good looks like before I wrote any code.

What did running the simulations manually reveal that a product plan might have missed?

Originally I put people into a normal Tuesday in their new life. Users wanted to zoom into specific areas, like social life, physical health, or whether a job would stimulate them. That pushed us to expand our metrics into what we call the five wealths, and to add a feature where you can chat with your future self.

What has to be true before newl can model cause and effect rather than just a plausible future?

General LLMs rely on predicting the most probable next token, which is correlation and ignores your context. We are building a model based on causal inference, which is widely used in medicine, where individual context matters. We also collect data on how close simulations were to people's real experiences, which lets us validate and re-weight the model.

If the future is unpredictable, how can newl give a meaningful score?

We can never predict exactly what will happen. Instead we proxy each decision across five wealths: financial, social, physical, mental and time. We estimate how likely a new life is to improve or harm each one compared with your current state. We also attach small real-world experiments, which validate the model and help people go in with their eyes open.

How do you know a simulation improved a decision rather than just made someone feel more certain?

They are interlinked. Pre-living a normal Tuesday gives emotional cues, then the metrics give rational data, and small experiments move you into reality. Better decisions reduce the gap between expectation and reality, where unhappiness lies. We cannot live counterfactual lives, but we use academic research and longitudinal datasets of people who made similar moves.

Where can people learn more about you and newl?

I post regularly on LinkedIn about AI simulation and decision-making. The company is newl, which stands for new life, spelled n e w l, and the website is newl.app. We are live with career simulations because that is where demand is highest, so it suits anyone weighing a pivot, a business, or a relocation.