Flux

Here's a 90-day plan for implementing DORA metrics with no dedicated DevOps budget and no platform team: what to track manually in weeks 1 through 4, which two metrics to automate first and why they're the easiest, and how to sequence change failure rate and recovery time after that. Full breakdown, phase by phase in this post: https://askflux.co/3TnVK1x #DORAmetrics #EngineeringLeadership

This month we're looking at new research on AI-generated code, $5M in funding, a customer story highlighting code-first visibility in practice, and industry highlights.

AI code generation is moving faster than most engineering review processes. In a recent survey of 309 engineering leaders, nearly 80% said their teams are using AI to generate code. Yet 1 in 3 organizations still haven't shipped AI-generated code to production. What's causing the gap? Join Flux CEO Ted Julian and Aaron Beals as they unpack the survey findings, discuss the biggest risks engineering teams are encountering, and share the practices separating organizations that are shipping AI-generated code with confidence from those still stuck in pilot mode. 📅 July 29 | 10 AM PT Reserve your seat: https://lnkd.in/gqNeXKKq

Where does AI-generated code stand today? Calibrate portfolio company Flux sponsored independent research with Dimensional Research to get a clear picture, and they recently published the results. One clear finding: AI has solved the code creation problem faster than most organizations have solved visibility and control. More on the AI Code Generation Reality Check report at https://lnkd.in/g9Px9VzF 

🐻🚀 Big Red Startups: in the past month, 11 startups raised VC funding, 2 were acquired, 1 IPO'd on the NASDAQ 🚀 2026-06-19, Seed: Vali Health - Serena Dang ’15 - AI assistant for home care 🚀 2026-06-18, Series C: HyperLight - Kevin Luke, PhD ’16 - Optical circuits for optical data 🚀 2026-06-15, Series C: AttoTude - Dave Welch, PhD ’85 - Faster processing in data centers 🚀 2026-06-14, Seed: Ploy - Will Gao ’22 - Website for business growth 🚀 2026-06-11, Series B: Coram AI - Ashesh Jain, PhD ’16 - AI software for security cameras 🚀 2026-06-10, Seed: Ovelle - Travis Potter ’05 - Fertility egg production 🚀 2026-06-10, Seed: Flux - Ted Julian ’92 - Coding team intelligence 🚀 2026-06-10, Seed: F2 - Don Muir ’15 - AI platform for private market 🚀 2026-06-09, Pre-Seed: Orbital - Space Data Centers - Euwyn Poon ’04, JD ’07 - AI data centers in space 🚀 2026-06-09, Series A: Infinity Constellation - Francis Pedraza ’11 - AI-native service companies 🚀 2026-06-08, IPO: Factorial Energy - Siyu Huang, PhD ’12, MBA ’14, Alex Yu, PhD ’14 - Safe, high performance batteries 🚀 2026-06-04, Acquired: Leapfin - Raymond Lau ’03, Erik Yao ’05 - Financial accounting software for revenue transaction data 🚀 2026-06-03, Acquired: Kumo - Jure Leskovec, PostDoc ’09 - Query large scale data warehouses 🚀 2026-06-02, Series A: Layup Parts - Zack Eakin, MEng ’06 - Manufacturing for composite parts #startups #venturecapital

Thanks for the invitation Keith Cline! Super fun recording this with you. I hereby propose a Keith Cline episode of VentureFizz and volunteer to interview you. What do you say people of LinkedIn?

Most DORA implementations fail for three predictable reasons, and they tend to happen in a specific order: 1. automating before you've defined what counts as a deployment 2. chasing a perfect measurement pipeline before collecting a single data point 3. using the metrics to rank teams instead of understand systems. Here's what to do at each stage instead, with the reasoning behind each one. https://askflux.co/3TnB5dW #DORAmetrics #EngineeringLeadership

Flux sponsored independent research with Dimensional Research to get a picture of where AI-generated code stands today, and now we're publishing the results. 309 engineering leaders. Five continents. A clear signal: AI has solved the code creation problem faster than most organizations have solved visibility and control. 44.7% have AI-generated code in production. Another 35% are writing it but haven't shipped it. Just 3.6% say AI-introduced issues never reach production. The AI Code Generation Reality Check covers adoption patterns, the widening gap between code velocity and review capacity, which risks are reaching production and how often, and what high-performing teams are doing differently. Download the report: https://lnkd.in/gwZy8dSX

Flux sponsored independent research with Dimensional Research to get a picture of where AI-generated code stands today, and now we're publishing the results. 309 engineering leaders. Five continents. A clear signal: AI has solved the code creation problem faster than most organizations have solved visibility and control. 44.7% have AI-generated code in production. Another 35% are writing it but haven't shipped it. Just 3.6% say AI-introduced issues never reach production. The AI Code Generation Reality Check covers adoption patterns, the widening gap between code velocity and review capacity, which risks are reaching production and how often, and what high-performing teams are doing differently. Download the report: https://lnkd.in/gwZy8dSX