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🚀 Exploring AI App Development – Looking for Guidance Hi everyone – I’m Tyson from Lean Enterprise Institute (LEI). We’ve been experimenting with AI-enabled applications to support Lean transformation (for example, problem-solving tools developed with Art Smalley). We know we want to keep developing in this space and build capability across our organization – but we’re at the “where do we even start?” stage when it comes to hiring developers. 👉 I’d love to connect with anyone here who has: • Experience hiring or leading small AI app dev projects (what skills/roles mattered most?). • Insights on how to scope a first hire or project in this area. • Or is simply open to sharing lessons learned from building AI products. If you’re open to chatting, please DM me here, reply in this thread, or come find me at the Summit. I’d really value your perspective. Thanks! – Tyson
Hi @theaton, I can relate to the ‘where do we even start?’ stage. I’m Laurence from Gaiwan, a software consultancy. You may know one of our clients, Gene Kim. https://gaiwan.co/hi-were-gaiwan/ I’d be happy to share my thoughts on this. From my experience, the key to boosting productivity with AI isn’t about using one tool, but about identifying workflow bottlenecks and applying the right AI solution to each specific problem. This perspective often helps clarify the first steps. Happy to chat more (I’m in UTC+8 but can adapt). • LinkedIn: https://www.linkedin.com/in/replware/ • Technical Blog Posts: https://gaiwan.co/tag/lambda-island/
I'll be floating around the event offering free affirmations. Come find me and get your unique unique affirmation to help you navigate the uncertainties of AI-driven software development. They won't promise 10x improvements, but they should at least brighten your day 😎
Hi everyone — I am Fawad Rashidi, CTO at Zest Dental Solutions, a med-device manufacturing company based 100% in Southern California, and backed by a PE-firm. In addition to software engineering, ITOps, and cybersecurity, I am also responsible/own revenue through digital marketing and eCommerce channels. Furthermore, I am responsible for all customer support. Before joining Zest, I was a technology instructor at Pepperdine University, ran a startup, and worked for Danaher Corp. You can find me on LinkedIn https://www.linkedin.com/in/fawadafr/ if you want to connect with me. I'm also walking around the conference and happy to meet up. Thanks
Hi @fawadafr , That’s quite a scope you’re covering at Zest! I’m Laurence from Gaiwan, a software consultancy (one of our clients is Gene Kim: https://gaiwan.co/hi-were-gaiwan/). I’ve mostly worked with VC-backed startups, and I often see CTOs juggling multiple responsibilities just like you. In those cases, setting up a solid Modern Data Stack and/or using some sharp tools (we use Clojure/Datomic) made a big difference in both speed and reporting. Curious how Zest is approaching that balance? LinkedIn: https://www.linkedin.com/in/replware/ Technical Blog Posts: https://gaiwan.co/tag/lambda-island/
Hi everyone! Excited to connect with you all 👋 As I’ve been chatting with folks, it sounds like budget season and AI are on everyone’s mind. I wanted to share a webinar that might be useful: DX CTO Laura Tacho (did you catch her talk with Bruno Passos this morning?) and CEO Abi Noda will be diving into enterprise spend trends, balancing current vs. future investments, and how to plan for tools that don’t even exist yet. 👉 https://getdx.com/webinar/planning-your-2026-ai-tooling-budget/ Or just swing by the booth and say hi, we’d love to see you!
I’d love to see and perhaps help publish/document some case studies of the 10x+ outcomes we heard about this morning. Whether startup, or larger company - what made this possible vs. the 20-50% speedup most teams are seeing on average. What verticals or conditions are required to get those kinds of outcomes? Are they sustainable? I’ve heard a number of high level allusions to this kind of productivity but it’s unclear whether it’s an early datapoint, or a sustainable outcome. If sustainable — what has to be true (team structure, tools, risk tolerance, workflow, etc.) for it to work reliably?
Awesome question. I’m Laurence from Gaiwan, a software consultancy. You may know one of our clients, Gene Kim. https://gaiwan.co/hi-were-gaiwan/ My take on the 10x outcome is that while it’s fascinating to discuss, from a practical standpoint, it reminds me a lot of the Theory of Constraints (TOC). You solve one bottleneck, and another one inevitably pops up. The real magic isn’t in finding a silver bullet, but in having a system in place to constantly identify and solve the next biggest problem. We’ve seen some pretty incredible, sustainable gains on our projects—not by chasing a mythical 10x, but by focusing on building flexible architectures that allow teams to consistently break through their own bottlenecks. I’d be happy to discuss this further. I’m in UTC+8, but I can adapt. You can also find some of my technical blog posts on our website. Curious to hear what others think about this. What’s the biggest bottleneck you’ve seen a team run into? Technical Blog Posts: https://gaiwan.co/tag/lambda-island/
My assumption, and that word is doing a lot of lifting here, is that the difference between that 20-30% and 10x pie in the sky, or the often-quoted 2 days instead of 2 weeks, has to do with the nature of the development work being done. The only thing that comes to mind for me would be a major change to the product due to some sort of emergent business need that would take an engineer a lot of time to sort out that AI is well-apt to accomplish in the hands of a skilled professional. E.g. if the software architecture wasn't forward-thinking around flexibility (solid, gang of four, etc) then you could easily end up with a significant redesign/rearchitecture effort that AI might make a lot easier.