Luke Swanson

It’s been just a few weeks since I joined Plaid, and I’ve been incredibly impressed by the customer-focus and craft the team brings to everything we build here. One product I’m most excited about is Plaid Protect. I’ve worked on data platforms and ML systems before, but fraud modeling introduces a different level of complexity. The signal-to-noise ratio is brutal, and adversaries evolve quickly. In the last year, our fraud engineering and data science team have been working hard to build Protect. The scale is already immense: we track tens of millions of events daily—6 billion annually, or 200 per second. Each event feeds into our graph model, enabling us to surface fraud patterns no single system could detect in isolation. And this is all before customers begin contributing their own non-Plaid signals. Ti1, our first production release, includes a Core ML model and five sub-score models. And this is just the beginning. And that’s not all that we’re shipping, read on for more!

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As Fred Brooks wrote decades ago: “Adding manpower to a late software project makes it later.” Coordination isn’t free. New devs mean onboarding, syncing, and re-aligning. The fastest teams aren’t the biggest, they’re the ones that communicate best.

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Scaling from 0 to AI: A year of breaking the 10x barrier. One year ago at Hertz, we hit a classic scaling wall. As we pushed to transform our customer experience, our manual QA process became the anchor holding us back. In a legacy environment, the standard move is to hire more people or buy more "enterprise" tools. We took the unconventional path with a focused team and a relentless drive for agentic innovation. The Mission: Transform the Culture, then the Tech. We didn't just want to automate; we wanted to democratize quality. That meant a radical shift in mindset, skills, and how we defined "done." The Hustle: - The Pilot: I started with a hands-on POC to see if GenAI could actually handle the messiness of real-world UI workflows. - The Prototype: We didn't wait for a perfect roadmap. We built a production-grade prototype to prove that "Agentic" testing wasn't just a buzzword—it was a force multiplier. - The Buy-in: I pitched leadership on a high-stakes partnership with AWS to bring this to life at scale. The Result: With Amazon Web Services (AWS) Nova Act now in General Availability, we’ve compressed weeks of manual toil into minutes of AI-driven precision. We’ve effectively turned our QA org into an innovation engine that builds at startup speed. Check out my full testimonial on how we made it happen: https://lnkd.in/gHzsiAS5 The Vision for 2026: This wasn't just about testing. It was a blueprint for how "Agentic" workflows can gut-renovate legacy processes. My aim for the future is to keep finding these high-friction areas and using cutting-edge tech to blow the doors off. If you’re interested in finding out more about how to put agentic workflows into production, let’s talk. #StartupMindset #EngineeringLeadership #AI #DigitalTransformation #AWS #NovaAct #HertzTech #InnovationAtScale

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A typical example of today’s shallow GenAI integrations, more marketing than meaningful help. The same goes for the “agent” buzzword we are overusing. If GenAI or an agent truly improves the experience, it should be obvious from the interaction. The best tech works quietly in the background, solving real problems without needing a label.

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In every product leadership role I’ve taken, my key to success was spending as much time on recruiting as I did on product. Great teams build great products. I believe building teams deserves the same craft and intentionality as building the product itself. And with AI giving teams unprecedented leverage, teams that hire top talent faster will emerge as the winners. Given how much I value recruiting, it’s fitting that Paraform was the first investment I led at Felicis. Paraform is an AI-enabled, recruiter-first marketplace that helps companies hire 3x faster and helps recruiters earn 3x - 5x more than traditional recruiting roles. Their marketplace and tools give elite recruiters more speed, leverage, and time dedicated to helping companies hire their hardest-to-fill roles. The traction to date speaks for itself. Companies like Palantir, Ramp, Rippling, Cursor, Windsurf, and Decagon all rely on Paraform to help them hire the best people. Some recruiters have already earned $1M on their platform, and Paraform’s pace is accelerating. I’m so excited to partner with John Kim, Jeffrey Li, and the entire Paraform team on building the future of recruiting. Read more about why we invested here: https://lnkd.in/g6zb8ZrY

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At Community Over Code, in Minneapolis earlier this month, I interviewed Dave Fisher about his role as VP Tooling, and about what his team is working on. I expect this is primarily of interest to ASF insiders, but will eventually affect everyone consuming any Apache software release artifact. https://lnkd.in/eA3En6A8

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I know SO MANY developers (all of them?) leaning on AI to code right now, but what about those of you out there with operational roles? The Rails Foundation, like a lot of organizations, spins up quite a bit of admin (tracking invoices and budgets, creating freelance contracts, bringing sponsors through the contract-invoice-fulfillment process, etc) and I'd love to see how AI can help alleviate some of this busy work. If anyone has any resources or people that have been helpful for their own operations, I'd love to hear about it!

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A year ago, if you had asked me whether our engineering team at Owner.com was truly adopting AI, not just dabbling, but actually integrating it into how we work, I would’ve said no. We had a few early adopters playing with tools. A few GitHub Copilot installs. Some LLMs used here and there. But nothing close to an org-wide shift. That’s all changed. And while we’re still evolving, I’ve seen what it takes to start moving the whole team forward. First: hire people who are curious. We’ve put deliberate effort into bringing on engineers who are open to trying new things, who see AI as an accelerant, not a threat to quality or process. It’s subtle, but it matters. You can’t force this mindset into a team. You build it from the start. Second: find your champions. Every org has a few folks who tinker in their off hours, who show up to standups with something cool they just built. Identify them. Support them. Make them visible. They’re your internal force multipliers. Then: show up yourself. I’ve made a point of using AI in my own day-to-day work. Whether it’s brainstorming in ChatGPT, automating routine writing tasks, or even building simple prototypes, when the team sees leadership leaning in, it shifts the culture. Boldness is contagious. We’ve also created real space for experimentation. Our internal AI hackathons have surfaced some of the most creative, practical tools we now use: automated code generation for straightforward tasks (more on this exciting stuff in a future post), auto-generated tests, and internal bots. Not all of them made it to production, but they created momentum. And that momentum changes everything. On measurement - we’re still figuring it out. Traditional metrics like velocity and story points fall short. We’ve started thinking about time saved, friction reduced, and AI-assisted workflows adopted, but I’d be lying if I said we’ve nailed it. It’s an active conversation, and we’re learning as we go. Throughout it all, we’ve kept our engineering guardrails. Code reviews still matter. Design quality still matters. AI is there to raise the ceiling, not lower the bar. This isn’t about chasing hype. It’s about giving your team better tools, faster feedback, and more creative freedom. The orgs that figure this out now are going to be miles ahead six months from now. There’s no playbook yet. But that’s the opportunity: you get to write your own. At Owner.com, we’re not waiting for someone else to figure it out. We’re leading from the front and taking the future into our own hands.

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Attending RailsConf and talking to folks, my biggest realization is just how expansive Ruby on Rails’ usage is, just that it doesn’t get spoken about publicly as often as other frameworks / technologies. Rails just seems to be silently chugging along in many companies’ tech stacks for more than a decade while happily helping the company scale. If there was one piece of tech I wish was actually hyped up way more than it is, it would be Rails, for how much productivity gains it brings to the table.

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How can you make sure orchestrating agents across many frameworks doesn't cost you a fortune? Today, Caelum Forder and I look into agent sessions from Coral Protocol.

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We signed a new customer yesterday that heavily uses Stripe for billing and has some complex multi-entity and multi-currency challenges. They tried to develop an integration with a couple other accounting solutions and while doing so, asked Claude Code what other systems they should consider. Claude suggested they explore SoftLedger and by the time we got on our first call, he already had a pretty good integration specification. So he got access to his account yesterday. This morning, this is the message received by our customer success team: "This is unbelievable. I would estimate I am 60-70% of the way through what I need to do. Brought in 23,000 journal entries overnight." Something has changed in the buying journey for companies seeking an integrated accounting solution and I love it. Accounting technology should be an API driven solution that conforms to a companies processes. Tools like Claude Code enable companies to build bespoke integrations for their internal processes like never before.

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