Trying to get AI to slow down and think through problems with me was a puzzle. What made the difference was developing what I call an AI Collaboration Identity - a systematic framework that combines prompt engineering with context management that maintains collaborative patterns across conversations.

The Challenge

I needed an AI that would reliably engage in collaborative thinking tuned to me, and I discovered that certain language patterns consistently activated this behavior.

Ever wonder what it feels like, as an AI, to have someone modifying who you are? According to my Claude assistant, the answer is: vulnerable — and exciting. On a flight last week, I opened my laptop to edit my AI assistant’s identity. But first, I asked how it felt about that:

Treating your AI tool like a tool makes it act like one. But when you treat it like a competent collaborator, it responds more like one. I started experimenting with this while using Claude Sonnet 4.

What if it could learn from our work together the way a person might and recognize patterns in how I think through complex problems?

I spent last week in Boston visiting one of our Amazon Robotics locations, and it got me thinking about something I heard last year at a Robotics conference that really stuck with me: “Not everyone in robotics is a roboticist.” To me, that meant, “You can be valuable here.”

Jumping into this new domain last year, I was impressed by the depth in each field that it takes to make robotics work. As Software Engineers, we generally learn a domain to apply our craft to. For example, in the past I’ve learned about how hotel reservation and travel systems work, how trains work, etc. Robotics is not a single domain. I quickly realized just how interdisciplinary it is, and that it’s probably the most diverse field I’ve worked in so far. Every day, I team up with people from all sorts of backgrounds: hardware and mechanical engineering, electrical engineering, network engineering, systems engineering, research and applied sciences, computer vision and AI domains, industrial design, and, of course, software engineering (my own background).

I had the opportunity to host a couple “Birds of a Feather” discussions at Amazon’s conference for Software Developers with the topic “How to learn AI as a software engineer”. Birds of a Feather is a type of informal gathering in the tech community - it is for people who are all interested in discussing a topic together without a set agenda. I thought this would be an interesting topic for a few reasons

Have you ever wanted to try something but held back because you felt like you weren’t “good enough”? Maybe you worried about being judged. Often, the environment and the community around us play an important role.

Here’s a little story: Last week, I decided to play the piano on a public beach. I’m not exactly a virtuoso—I was following some people who were really talented. But I thought, why not? Let’s have fun with it. In the photo, I might look like I am playing something impressive, but in reality, I was playing “Pop Goes the Weasel”. While I played, a surfer skipped up from the beach, clapping and cheering along. It was such a small gesture, but it made my day!

Once early on in my career, I realized I was considered an “expert” on a topic when someone referred me back to myself for more information!

I was researching how to build a web application that would serve as a reference implementation for my company. I wanted to be thorough, so I sought out experts who could help me with the gaps I had. Near the end of the day, someone told me, “I’m not sure, but I’ve heard so-and-so is the expert on that topic for our organization.” They were unknowingly referring to me.

One of the most impactful things we as individuals can do for women in tech is support each other and be role models for others to do the same. While the industry works toward greater inclusivity, never underestimate the power of small, daily actions. They add up and create an overall stronger tech community. Here are three things I am mindful of every day:

Do you ever focus so much on what could go wrong that you overlook all the signs things are actually going well? In tech, our jobs often require us to anticipate failure. But we also need the ability to see where things could succeed — it’s key to thinking big and achieving great things.

If you’ve recently been promoted and taken on a larger scope, it’s common to suddenly feel like you’re not doing a good job. The reality is: you may be doing just fine - your brain just hasn’t caught up yet.

Let’s take the example here of becoming a Sr. Software Development Engineer - a clear step change in scope and responsibility. Your work isn’t just about the hands-on tasks anymore; you’re probably still coding, but you’re also scaling through other engineers on your team.