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: 2025-06-26 12:32:09
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 Rise 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 in generating code. They are largely semantic language engines after all. Given that 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 (you and me) become critical to get the value you want to realize and possibly to preserve jobs.
The Role of 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 identified needs.
Benefits of AI for Product Teams
- Alignment: AI can help ensure that the product development process aligns with business objectives, reducing misunderstandings and miscommunication.
- Consistency: AI tools can generate consistent outputs that can be used across different teams, enhancing collaboration.
- Completeness of Analysis: With AI's ability to analyze large data sets quickly, Product teams can derive insights that were previously time-consuming, leading to better decision-making.
Risks of Dependence on AI
While there is a general risk of homogenization of thought and approach as we become dependent on AI (similar to the reliance on spreadsheets in Finance long ago), the benefits for Product teams can outweigh these risks when managed correctly. A balance must be struck between leveraging AI tools and maintaining critical thinking and creativity.
The Transformation of Jobs
Coders and Product Managers are two areas most ripe for transformation through comprehensive adoption of AI. As AI continues to evolve, jobs will change. It’s essential for professionals in these fields to explore how to migrate their talents to where AI drives them.
Upskilling and Reskilling
To adapt to the changes brought about by AI, it is crucial for professionals to engage in upskilling and reskilling. This can include:
- Learning to work alongside AI: Understanding how to use AI tools effectively in daily tasks.
- Developing soft skills: Enhancing communication, teamwork, and problem-solving abilities to complement technical skills.
- Staying updated: Keeping abreast of the latest trends and developments in AI and technology to remain competitive in the job market.
Conclusion
As we look to the future, AI will play an increasingly critical role in shaping the landscape of technology businesses. Embracing AI not only enhances the efficiency of coding and product management but also creates new opportunities for innovation. By understanding and adapting to these changes, entrepreneurs and professionals can position themselves for success in an evolving digital landscape.
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