This week on the Konvoy Newsletter audio edition, host Jason Chapman explores why version control for AI prompts is becoming a critical piece of modern software development. As AI becomes deeply embedded in everyday workflows, teams are discovering that prompts evolve just like code — and need new systems to track, evaluate, and optimize them.

From guiding AI outputs with precision to managing prompt history across teams, the future of software development will require tools purpose-built for this new workflow. Just as Git transformed how developers collaborate on code, new platforms are emerging to do the same for AI prompts — with evaluation data serving as the ultimate moat.

What You’ll Learn in This Episode:

• What prompt engineering is and why it matters
• How prompt version control differs from code version control
• Why non-technical users need a different collaborative workflow
• The role of evaluation frameworks like “negative examples” and “LLM as judge”
• How new tools can centralize API management, testing, and cost monitoring
• Why evaluation data could become the key differentiator in this market

Whether you’re building with AI, investing in next-gen infrastructure, or just trying to keep pace with the future of development, this episode breaks down the emerging world of prompt version control — and why the teams who get this right will gain a lasting advantage.

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