I’m a machine learning lead at Adobe. I got ahead by prototyping fast — and by embracing vulnerability.

• Surabhi Bhargava went from an entry-level role to a machine learning lead at Adobe in five years.

• She said that translating ideas into real products goes much further than just talking about them.

• Being vulnerable also helped Surabhi build connections and receive valuable support for her career.

This as-told-to essay is based on a conversation with Surabhi Bhargava, a machine tech lead at Adobe’s San Jose office. It has been edited for length and clarity. Business Insider has verified her employment.

In just five years, I went from an entry-level machine learning engineering role to a machine learning tech lead at Adobe. It’s been quite the journey.

What’s been key for me is that I always had the chance to work on Adobe’s most relevant AI projects.

AI has advanced rapidly over the last five years. I started with computer vision, moved to natural language processing, and now I’m focused on generative AI.

The key to my advancement has been consistently finding the right opportunities, being in the right place at the right time, and sometimes starting projects from scratch.

Share tangible ideas

A key aspect of working in this industry is translating ideas into real products.

You’ve probably heard the phrase “show, don’t tell.” People often share ideas but don’t usually have proof of concept or something tangible people can interact with.

Having something real that others can test goes much further than just talking about ideas.

I’ve always made it a point to translate my ideas into something people can try. I’d create initial prototypes and give them to product managers or senior folks. If they liked it, we’d move forward with developing the product.

If not, I’d get feedback and useful information to iterate it further.

It doesn’t need to be an entire product or have a shiny user interface — just something tangible they can engage with. A simple front-end that lets them test the backend tech works just fine.

This approach helps me build faster, get feedback faster, and share ideas more broadly, which builds credibility.

When people work on similar projects and need collaborators, you want to be the first person they think of. Having visible work behind you makes that much more likely.

Embracing vulnerability

Building connections at work is valuable, but it wasn’t natural for me to go up and talk to someone randomly.

I had to push myself out of my comfort zone. What I found was that the more vulnerable I was — whether talking about the challenges I was facing or the opportunities I was seeking — the more others opened up, too. This wasn’t just with my manager — it was across the company.

As a minority in tech, having a strong support system, like fellow women engineers, was also important.

Being open about my struggles and ambitions encouraged others to share their experiences and offer valuable help. The key was always bringing that advice back to my work and growth.

People don’t do that enough. You won’t always get what you ask for, but you definitely won’t get it unless you ask. This applies not only to career progression but also to life advice.

Vulnerability helps create those connections — people are more likely to support you when you let them in. Be open, reach out without hesitation, and help will come in unexpected ways.

Do you have a story to share about working in AI? Contact this reporter at cmlee@businessinsider.com.

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