ChatGPT Integration with InsideSpin
As a validation of AI-augmented article writing, InsideSpin has integrated ChatGPT to help flesh out unfinished articles at the moment they are requested. If you have been a past InsideSpin user, you may have noticed not all articles are fully fleshed out. While every article has a summary, only about half are fleshed out. Decisions about what to finish has been based on user interest over the years. With this POC, ChatGPT will use the InsideSpin article summary as the basis of the prompt, and return an expanded article adding insight from its underlying model. The instances are being stored for later analysis to choose one that best represents the intent of InsideSpin which the author can work with to finalize. This is a trial of an AI-augmented approach. Email founder@insidespin.com to share your views on this or ask questions about the implementation.
Generated: 2025-06-28 08:56:34
AI for Product Teams
Over the last 30 years or so, the number of coders has grown dramatically to accommodate professional needs. Starting below a million in the US in the early 90’s it is estimated there are well over 30 million professional software engineers as we head into 2025. That count does not include the millions and millions of web development tool users managing their own needs, with little formal coding training, relying on tools such as WordPress, HubSpot, Spotify, GoDaddy, and AWS to generate the templated code that is needed.
The Role of AI in Coding
For anyone who has used AI coding tools like CoPilot from GitHub, it is easy to see that AI tools thrive generating code. They are largely semantic language engines, after all. Given most coding languages are meant to be semantically unambiguous for a computer to execute the code properly, the sophistication AI embodies to understand and generate ambiguous spoken languages like English is largely left unneeded. Code-generating tools still suffer from garbage-in/garbage-out risks (as do AI chat tools like ChatGPT). This is where AI-augmented skills for human operators become critical to get the value you want to realize, and possibly, to preserve the jobs.
Implications for Product Managers
For Product managers, the essence of the Product role is the synthesis of streams of requirements (input) to create the output an Engineering team can use to economically build, and a business can take to market to generate revenue. The more unambiguous and consistent the output a Product team can produce, the more likely coders and sales teams will be able to meet the needs identified. While there is a general risk of homogenization of thought and approach as we become dependent on AI (as there was with spreadsheets in Finance long ago), the benefit for Product is alignment, consistency, and completeness of analysis from the generated artifacts produced over time.
Transforming the Workforce
Coders and Product managers are two of the areas most ripe to be transformed through comprehensive adoption of AI. As AI tools become more integrated into the daily workflow, it is essential for professionals in these fields to adapt and evolve their skill sets. Here are some strategies to consider for this transformation:
- Embrace Continuous Learning: Stay updated with the latest AI tools and technologies. Enroll in training sessions and workshops focused on AI applications in coding and product management.
- Develop AI Literacy: Understanding how AI works can empower Product managers and coders to leverage these tools effectively. Familiarity with machine learning principles and data analysis can provide a competitive edge.
- Collaboration with AI: Instead of viewing AI as a replacement, consider it a collaborative partner that can enhance productivity. Use AI-generated insights to inform decisions and improve project outcomes.
- Focus on Soft Skills: As technical tasks become automated, soft skills such as communication, leadership, and creativity will become increasingly important. Cultivate these skills to remain valuable in an AI-driven landscape.
The Future of Product Teams
The integration of AI into product teams is not merely a trend; it is a fundamental shift in how technology businesses operate. As more organizations adopt AI-driven tools, the ability to adapt will define the success of product managers and coders alike. While some roles may change or even disappear, new opportunities will emerge for those willing to embrace the evolution.
Conclusion
In summary, the rise of AI in coding and product management presents both challenges and opportunities. By understanding the implications of these technologies and adapting accordingly, professionals can enhance their roles and contribute to their organizations' success. The future of technology businesses is bright, and those who harness the power of AI will be at the forefront of innovation.
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