It’s tough to be a developer, especially in today’s world where the role is starting to be belittled by statements like “AI will replace most developers in 1 year” or “anyone can be a great developer now, just get on Cursor/Loveable/Replit and do some vibe coding.” 

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I’m all for more folks gaining exposure to coding. However, there’s a difference between building a site to play around with versus shipping and operating enterprise grade software that can withstand the pressures of global scale, security, and reliability. For this, senior developers will always be needed. If you ship code without an understanding of the underlying infrastructure or the upstream/downstream dependencies, no amount of “vibes” or AI assistants will be able to put out the fires that are sure to ignite at some point.

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During my time in the DevOps space, as Chief Commercial Officer at Lightstep and AVP of Cloud Observability at ServiceNow, I had the privilege of working with some of the world’s best engineering teams at companies such as Spotify, NVIDIA, Samsara, and Atlassian. Across the board, these teams were relentlessly focused on one goal: freeing up their engineers to build and ship great products. Yet despite best efforts, developers and their managers often found themselves bogged down by operational overhead, administrative friction, and tooling that didn’t keep pace with their ambitions.

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Now, with the wave of AI upon us, the potential distractions mount as development teams must consider the ways in which AI will be leveraged to positively, and negatively, impact workflows, products, and overall business. AI will fundamentally change the way in which software is developed, and thus the people and tools must adapt. 

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At Cowboy, we are spending time thinking about developer tools of the future to amplify the effectiveness and creativity of developers, rather than replace them. Here are some elements we hope to find in the next generation of tools for developers in the age of AI:

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• Helping developers adapt their practices, processes, and culture to embrace AI-native workflows
• Monitoring, inspecting, securing, and maintaining code generated by co-pilots, agents,  and other AI tools
• Accelerating the software development lifecycle  
• Reducing cost (compute, telemetry, tooling, etc.) 
• Automatically resolving low-impact, high-frequency issues while looping developers in when needed
• Fostering, or eliminating the need for, tighter collaboration across engineering, product, design, and IT operations
• Reducing, and ideally preventing, the accumulation of technical debt
• Minimizing context switching to enhance focus, flow, and execution

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We see lots of opportunity ahead for new products that support developers in the age of AI. If you’re working on solutions especially that touch on some of the above opportunity areas, please get in touch. We see lots of open trail ahead, and are excited to provide provisions, grit, and campfire stories.

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