Building your AI agents like products: A blueprint from POC purgatory to production

AI hype took off in 2023 with ChatGPT's rapid user growth, leading executives to demand proof of concepts and investment. This surge created pressure on teams to develop AI models, prompting concerns about ROI, integrations with legacy systems, and workflow impacts. To treat AI agents as core products, organizations must prioritize collaboration, align with customer needs, define success metrics, and mitigate risks. Building a dedicated team with the right skills is crucial for creating effective AI solutions that deliver value to organizational goals. Denys emphasizes the importance of mapping the AI product journey from business case to production, de-risking agents through checkpoints like user acceptance testing and private beta reviews, and measuring agent performance using metrics such as time-to-response and resolution rate/speed. By treating AI agents as core products and applying common product management principles, organizations can create useful and effective solutions that drive value and ROI.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.