Kent Quirk, an experienced Go developer, and Christian Gabrielsson, a software engineer adept with various languages, discuss the evolution and current relevance of Go. They tackle the challenges of adopting Go in established tech environments and highlight its long-term maintainability. The conversation also delves into the philosophical aspects of programming language choice amidst AI advancements. Listeners gain insights on advocating for Go, overcoming resistance, and leveraging Go's simplicity for practical use cases.
Go's ongoing relevance stems from its simplicity and performance, making it suitable for modern cloud-native applications despite emerging programming languages.
Resistance to adopting Go in organizations often relates to cultural comfort with established technologies rather than pure technical factors, emphasizing the need for robust justifications.
The integration of AI tools in software development enhances productivity, yet skilled engineers remain essential for maintaining high-quality coding standards and nuanced problem-solving.
Deep dives
The Versatility of Postgres for AI Applications
Postgres is highlighted as an optimal database for AI applications due to its popularity and extensibility. Its capacity to handle various data types, including time series and vector data, makes it suitable for complex AI tasks like recommendation systems and AI agents. Timescale has developed specific extensions, such as PG Vector Scale, to enhance the performance of Postgres, making it more viable for large-scale AI applications. By leveraging its existing capabilities, developers can transition smoothly into building AI applications without the need for entirely new database systems.
Evaluating the Relevance of Go in Modern Programming
A significant discussion centers on whether Go still holds value in today’s landscape of programming languages, especially amidst advancements in technologies. Despite criticisms, Go maintains relevance, particularly due to its simplicity, performance, and suitability for cloud-native applications. Experts emphasize that Go's efficient compilation and the ability to create reliable, maintainable systems lend to its continued popularity. The episode challenges listeners to reconsider if Go can compete with emerging languages or if it has reached its peak utility.
The Challenges of Introducing New Technologies
The conversation examines the difficulties teams face when proposing new languages like Go, especially when existing systems are deeply embedded within an organization. A personal narrative from an engineer illustrates the uphill battle in convincing stakeholders to move away from established technologies like MuleSoft, citing organizational inertia and comfort with the current system. Resistance often arises not purely from technical considerations but from a culture that favors the familiar over potential innovations. This reality reinforces the necessity for clear communication and robust justifications when suggesting transitions to new technologies.
The Complexity of Technology Decision-Making
The complexities of technology choices are explored, emphasizing the balance between technical viability and business considerations. Professionals often find themselves grappling with the sunk cost fallacy, where the weight of previous investments in a technology makes transitioning to better options challenging. A shared perspective is that, while introducing innovative solutions can be beneficial, achieving consensus within teams becomes a complex negotiation influenced by comfort levels and organizational culture. The episode highlights the need for clear communication and strategic planning when venturing into new technological territory.
The Impact of AI on the Software Engineering Landscape
Participants reflect on the increasing integration of AI tools in software development and their implications for the future of engineering roles. There is recognition of the productivity benefits these tools can bring, yet concerns exist over their reliability and the potential for depersonalized coding practices. Engineers emphasize that while AI can enhance efficiency, the need for skilled individuals to maintain high-quality standards in coding remains crucial. The discussion concludes that while AI will augment engineers’ workflows, it is unlikely to fully replace the nuanced judgement, creativity, and problem-solving abilities of human engineers.
With so many great programming languages having emerged in the last decade, many of them purpose-built, when and where does Go still make sense and how do you make the case for it at work?
Changelog++ members save 8 minutes on this episode because they made the ads disappear. Join today!
Sponsors:
Timescale – Purpose-built performance for AI Build RAG, search, and AI agents on the cloud and with PostgreSQL and purpose-built extensions for AI: pgvector, pgvectorscale, and pgai.
Retool – The low-code platform for developers to build internal tools — Some of the best teams out there trust Retool…Brex, Coinbase, Plaid, Doordash, LegalGenius, Amazon, Allbirds, Peloton, and so many more – the developers at these teams trust Retool as the platform to build their internal tools. Try it free at retool.com/changelog
JetBrains – Sign up for the free “Mastering Go with GoLand” course and receive a complimentary 1-year GoLand subscription at bytesizego.com/goland
