In this edition of Coffee with Calyptus, we sit down with Rachel Lawrie, a Software Engineer at Walmart and former leader at Coinbase. Rachel takes us through her career pivot from product management to engineering and shares insights on the challenges and rewards of building Web3 solutions. Rachel’s experience offers a unique perspective on problem-solving, systems change, and the future of engineering in the age of AI.
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You made a bold pivot from product to engineering at Coinbase, what motivated that move, and how has it reshaped how you think about building in Web3?
I realized I enjoyed the heads-down, technical problem-solving part of my job more than the business strategy, stakeholder management, and project management that made up the rest of my work. I started a full-stack software engineering bootcamp while working, and tasting the potential to program full-time made the transition irresistible!
There are still major technical challenges in processing throughput and making the user experience less technical that block Web3 from becoming mainstream. It’s exciting to now be able to work on those fundamental blockers in a concrete way.
You led Coinbase’s expansion into tough regulatory markets like Germany and Japan, what’s one insight from that experience that still influences your work today?
I learned how difficult it is to get clarity on emerging regulation and the importance of having close, local relationships with both the rule-makers and enforcers. Success requires an empowered local team, and you really have to trust them. I think the same concepts of trust and empowerment apply to specialized engineering teams.
At Verus, you were one of three founding engineers building a Stripe-for-compliance product, what was the hardest part of taking that from 0 to 1?
The hardest (but also most fun!) part was setting up the development environment, which I hadn’t done before, including modular Docker environments for dev, staging, and production, and the CI/CD pipelines. Building something useful for the customer was surprisingly straightforward.
You helped turn refugee labor mobility into a U.N.-backed solution, what did that journey teach you about systems change that still applies in the tech world?
In four years, our small team changed immigration policies in three different countries. The experience taught me how quickly years go by when you put your head down and focus on the work. Change is possible, even on something that seems impossible, like changing politically charged immigration policies.
You became an engineer during the time of AI, how do you think that has impacted you as an engineer?
AI has been an amazing learning tool, but I also think it’s been a crutch. I can get explanations for questions in a way that I understand, which I think means I’ve learned a lot faster than I could have without AI. But it’s also inhibited my learning of syntax and state changes because I’ve used AI to write a lot of my code.
As I learn more, I’m better at spotting my blind spots, and I’m now much more diligent about ensuring I understand 100% of the AI-generated code I use. I also code a lot without AI at this point to ensure I fully understand everything. I know it’s slower, but I think overall it evens out, because with my increased understanding, I can debug the problems AI gets stuck on more quickly, and I can also recognize when there are better approaches than what Cursor or Copilot suggest.
The environment changes so quickly, so I try to keep the big picture in mind and adapt my approach accordingly to ensure I’m becoming the best engineer I can be.
Solidity Challenge 🕵️♂️
What's wrong with this smart contract 😁.
Solidity Challenge Answer ✅
Answer: It's recommended to use the latest version of solidity in deploying new smart contracts.
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