Tag Archives: Technical Debt

LLMs adding to Technical Debt? Maintenance?

What is technical debt, and how does it apply to large language models? We dive into a really interesting conversation that goes from technical debt into system and code maintenance, which is probably a much better way to think about the challenges we have in maintaining the infrastructure systems, code, data and data lakes that we have to deal with on an everyday basis.

How do we maintain, store, track and update the LLMs themselves? How do we know and manage which model is being used when we retire a model?

References:
www.linkedin.com/pulse/how-google…h-debt-abi-noda/
devops.com/are-llms-leading-de…o-a-tech-debt-trap/

Transcript: otter.ai/u/ngUClgtMmLLKXCFalD…?utm_source=copy_url
Image: www.pexels.com/photo/anonymous-w…y-gloves-3846440/

Cloud2030LLMsChatGPTTechnical DebtMaintenanceCoding

Rob’s Hot Take:

In the Cloud 2030 podcast episode on August 17th, Rob Hirschfeld discusses the distinction between technical debt and system maintenance costs, emphasizing the importance of understanding the ongoing effort needed to maintain and improve systems. He points out that overlooking the maintenance costs while building a system leads to technical debt. Hirschfeld raises the question of whether large language models and AI can change the equation of system maintenance, a topic yet to be explored fully in the podcast.

AI And Technical Debt

We dig into a topic written about by Eric Norlin or SK ventures about technical debt and AI. In this episode, we discuss the consequences of generative AI could be radically transforming the way in which we generate code and deal with code that has been generated in technical debt.

We explore some fascinating concepts about how fast we can iterate, how we change the dynamics of building software, building automation, and the expertise required to architect systems. This leads pretty far down in the path towards disruptive thinking, and how this could reshape the entire industry.

Source: skventures.substack.com/p/societys-te…and-softwares
Transcript: otter.ai/u/MEtVkoNnZeCu0JHa30…?utm_source=copy_url
Image: www.pexels.com/photo/piggy-bank-…a-flower-4886900/

Rob’s Hot Take:

In a discussion on the Cloud 2030 podcast, CEO and co-founder of RackN, Rob Hirschfeld, highlighted the changing landscape of expertise in emerging technologies like AI. With the cost to build and iterate dropping significantly, expertise is no longer primarily applied during the building process, but integrated into design and testing sequences. The advent of generative AI has the potential to revolutionize how we design and build automation, software code, and technical systems, necessitating a redefinition of expertise in this rapidly evolving field.