This article is an impulse from Christian Ringwald, Senior Product Manager at SPREAD AI. Christian brings a background in data analytics, E/E integration, and product development at Volkswagen, combining deep engineering expertise with a passion for AI-driven innovation in automotive and defense.

Having spent years inside European OEMs one reality keeps surfacing: In the electric and software-defined vehicle era, innovation cycles have shrunk dramatically. 

While Chinese car manufacturers, like NIO, roll out new vehicle software features in as little as two weeks and Tesla releases over-the-air updates roughly every four weeks, their European counterparts often lag behind with lead times stretching into months. Falling behind on speed is not just inconvenient, it threatens market relevance and profitability. 

What's holding European car manufacturers back? 

European automotive manufacturers aren’t short on engineering talent, resources, or experience. So, what explains the difference in speed to market? 

The short answer: glacial feedback loops in software development. 

At the heart of every modern vehicle are millions of lines of code. But for most European car manufacturers, the process from writing a line of code to seeing it tested, integrated, and validated in a real vehicle is painfully slow and overly complex. Developers typically wait weeks or even months to receive feedback on their code's impact in a fully integrated environment. 

Compare that to leading Chinese car manufacturers, where rapid iteration is the default. Their edge isn't just agility: it's architecture, culture, and tooling. 

A broken feedback loop 

Let’s break it down: How does this feedback loop like (simplified) 

1. Step 1: Deploy new Software and get it tested: Fragmented toolchains and rigid architectures 
   Most legacy car manufacturers operate with disjointed software pipelines. Continuous Integration and Continuous Deployment (CI/CD) is patchy or nonexistent, and monolithic ECUs still dominate. 

1. Step 2: Getting Feedback back to developers is too slow
   A developer may write a feature or fix a bug, but receiving feedback on a line of code in the real-world context of a car often takes weeks. Feedback is slow, indirect, and delayed, which slows innovation to a crawl. 

Remember when you had to debug code you have written weeks ago? It is slow and error-prone.  

The Chinese model of Speed by Design 

Car manufacturers like NIO, XPeng, and BYD are blazing ahead using this recipe for fast feature delivery: 

• Service-oriented architectures that decouple software modules and enable targeted updates. 

• DevOps-first culture that treats vehicles like always-connected consumer technology, not static machines. 

• Fully automated continuous integration and development (CI/CD) pipelines as standard. 

• Integrated incident feedback loops, where real-world data is instantly actionable for development teams. 

This allows them to push fixes, improvements, or entirely new features into production in a matter of weeks - and sometimes even days. 

Why this urgently matters 

Speed isn’t a vanity metric, it’s about competitive survival. Here’s why: 

Customer expectations are shifting. Tesla and NIO customers are used to weekly software updates and surprise features. A slow-to-ship car update feels like a relic. 

Revenue and retention depend on software. Subscription features, digital experiences, and in-car apps are where the margins live. Miss the window, and you lose the customer. 

Regulations are changing fast: from cybersecurity compliance to green mandates, new requirements are hitting fast. Speed is not just a luxury; it’s a requirement to stay legal. 

The two non-negotiables for a way forward

If European car manufacturers want to stay relevant in the age of software-defined vehicles, they must fundamentally reshape their software delivery strategy. Two things are paramount: 

1. CI/CD for vehicle software

Implement continuous integration and deployment pipelines that allow changes to flow automatically from developer commits to fleet updates. This includes: 

• Automated build and test stages. 

• Deployment orchestration across multiple ECUs. 

• Simulation and virtual test environments that can catch issues early on component or system level 

CI/CD in automotive is table stakes.

2. Automated incident feedback to developers

Insightful Error logs & descriptions, telemetry & context information, and automatic root cause suggestions must be automatically surfaced to the relevant engineering teams. That requires: 

• Real-time observability infrastructure in vehicles. 

• Event correlation systems that pinpoint root causes. 

• Automatic rooting of Issues directly to the responsible engineering teams. 

Without this automating this loop, the time between pushing a new software and receiving feedback for developers will be too slow, so fix issues fast and iterate quickly. 

My take: Catching up is challenging, but still achievable 

While the gap may seem insurmountable, I believe European car manufacturers can still catch up. But not by launching massive transformation programs or multi-year platform overhauls. Instead, start small. 

The key is to build the feedback loop function by function, not vehicle by vehicle. Empower small, interdisciplinary teams made up of function owners, test engineers, and software developers to take end-to-end ownership of a specific feature or subsystem. Give them the tools to: 

• Build and deploy new code through a CI/CD-like workflow for their function. 

• Capture detailed runtime data and logs from test vehicles and simulation environments and store them in accessible interconnected with architectural information. 

• Automatically detect and root cause anomalies or regressions by combining architectural insights with runtime data from test vehicles. 

• Route those incidents directly back to the relevant software teams. 

Think of it as agile CI/CD with quick feedback on error Indications, with feedback flowing tightly between deployment and learning. 

Once this pattern works for a handful of key functions - say, ADAS lane keeping, energy management, or infotainment - you’ve proven the model. From there, scale it out. But let velocity grow from validated small wins, not bloated big-bang initiatives. 

This is exactly why I am focused on building products that close these feedback loops and give engineers faster, clearer technical insights. In my view, catching up will not come from doing more or adding more processes. It will come from learning faster, reducing the time between a line of code and its real-world impact, and making that knowledge immediately actionable for the teams who need it. 

With this mindset shift, the future is still within reach. At SPREAD, we see every day how shortening feedback loops accelerates delivery. Our platform enables teams to detect issues up to 75% faster and ensure SOP timelines are met. 

The lesson for Europe is clear: start small, prove speed in practice, and scale from there. 

To learn more about how SPREAD helps OEMs close feedback loops and accelerate delivery, visit our Solutions Page.