Name: We Analyzed AI-Generated Code: Here's What You Should Know
Start: 2024-03-10T16:43:00Z
End: 2024-03-10T16:43:15.000Z
Location: BrightTALK
Rating: 2

Find the best resources on code quality, code security, AI, DevOps and more.

The developer tool landscape is becoming increasingly difficult to manage, in today's rapidly evolving technological landscape. With a multitude of developer tools available, and the technological landscape being noisier than ever, it’s no wonder that tool consolidation has emerged as a business critical strategy. 

On the one hand, multiple tools create a lot of noise and become expensive to keep, especially for mid-market companies. But on the other hand, companies who don't invest in code quality and security -- especially given the rise of AI -- are at risk and could pay an even bigger price. 

This dilemma leaves business leaders and software developers wondering, should teams bring more tools together? How can we define priorities to boost efficiency? 

Join us in this webinar as we discuss:  
-  Why we’re talking about tool consolidation now
-  How to plan a successful development tool consolidation strategy
-  The business benefits of tool consolidation
-  Why is tool consolidation essential in the era of AI
-  How to balance tool consolidation with application security -- can you have it all at once?
-  And much more!

Navigating Tool Consolidation: What Do You Need in Your Developer Tool Box?

Security is increasingly becoming a shared responsibility across all teams involved in software development and deployment. Having a solid DevSecOps stack that integrates security from the outset ensures that security doesn't become a bottleneck in the later stages, preventing last-minute scrambles and vulnerabilities.

But is this a realistic approach for smaller teams at startups and mid-size companies? What is the easiest, most cost-effective way for any Engineering Manager to raise the bar on code quality and security? How can small teams ensure that every app meets their code quality, security and testing standards, before code is ever pushed to production?

Re-watch our live talk from DeveloperWeek 2024, by Codacy CEO and Co-Founder Jaime Jorge.

Into the Breach: Business Survival in the Age of Accelerating Cyber Threats

Is it possible for engineering teams to reap the benefits of both these practices, and successfully juggle software experimentation without compromising on quality, security and timely product delivery?

In this panel, engineering leaders explore the balance of experimentation and code quality, and how these two cultures shouldn’t be a barrier to one another. They will share ways that leaders can leverage best practices of processes inherent to the SDLC such as testing, feedback and documentation, to manage risk and reduce technical debt in their quest to deliver high quality, truly innovative software. 

Key takeaways:

- Educate your teams on the importance of code security
- Explore what innovation looks like in your org, and how to do it safely 
- Create a safe space for your team to enhance their creativity and innovation skills

Balancing Innovation and Security in Software Development

In this webinar, Tobias Sjösten, Head of Software Engineering at Stim, tells the story of how they used Codacy to significantly improve and quantify code quality across teams and projects, especially when dealing with legacy code.

As a company that has existed for a century, Stim has a lot of legacy code, so it was important to ensure that every new build could stand the test of time.

Watch this webinar to dive deeper into their story, how they overcame some challenges and what challenges remain.

STIM Customer Story: Making Sure your Code Withstands the Test of Time

Coding tools powered by artificial intelligence (AI) can offer a huge productivity boost to developers, so much so that many software companies are already encouraging their teams to adopt these tools. But is the code created by AI assistants any good? Is it secure? Can it be trusted? These are some of the fundamental questions currently being asked as development teams continue to weigh the pros and cons of AI-assisted coding.

To understand the quality of AI-generated code better, our CEO Jaime Jorge asked the popular AI assistant, ChatGPT, to generate code from a simple prompt, then ran static code analysis on the code to understand what kind of quality issues and security vulnerabilities might emerge.

We Analyzed AI-Generated Code: Here's What You Should Know

coding

Developers

code review

DevOps

Software Development

Automation

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We Analyzed AI-Generated Code: Here's What You Should Know

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Codacy