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: 2025-02-21 07:35:19
Challenges of Running a Technology Business
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, AWS to generate the templated code that is needed.
The Impact of AI on 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. AI tools can analyze vast amounts of data quickly, making them invaluable in software development environments where speed and efficiency are critical. 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. However, the effectiveness of these tools is still influenced by the quality of the input they receive, underscoring the importance of skilled human operators. Code generating tools still suffer from garbage-in/garbage-out risks (as do AI chat tools like ChatGPT). This reality necessitates a partnership between AI and skilled developers to ensure optimal outcomes, highlighting the importance of human oversight in the coding process. 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 the 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. Product managers serve as the bridge between technical teams and business stakeholders, ensuring that product development aligns with market needs. 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. However, there is also a risk associated with AI dependency, particularly the homogenization of thought and approach. Just as dependency on spreadsheets transformed Finance, AI could lead to a similar shift in Product management. 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.
Transformative Opportunities in Technology Roles
Coders and Product managers are two of the areas most ripe to be transformed through comprehensive adoption of AI. As AI continues to evolve, the nature of these roles will change, requiring professionals to adapt and upskill to remain relevant. Jobs will change, we'll explore how to migrate your talents to where AI drives them.
In conclusion, the technology sector is at a pivotal point. The rapid growth of the coding workforce, coupled with advancements in AI, presents both challenges and opportunities for entrepreneurs and professionals alike. Embracing these changes will not only enhance productivity but also allow businesses to remain competitive in an ever-evolving landscape.
Navigating these challenges effectively requires a proactive approach towards continuous learning and adaptation, ensuring that both technology and talent can thrive in the future.
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