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Culture & Methods Trends Report March 2023
This article discusses the impact of the layoffs in tech on psychological safety, the emergence of large language models such as ChatGPT, responsible tech, project to product, the worth of an architect, team topologies, staff plus, hybrid work, workplace design, and DevSusOps. It also discusses the need for organisations to be deliberate about organisational culture and how to rebuild a generative culture. It suggests that organisations need to consider the potential impacts of their products, be aware of the risks of large language models, and take a responsible view when developing their products. Additionally, the article mentions that asynchronous work is becoming more accepted and organisations are adopting value stream management and evidence-based management. Lastly, it suggests that organisations should become good at onboarding new people and understanding the diverse needs of their organisational community.
What impact have the layoffs in big tech had on the industry?
The layoffs in big tech have had a dampening effect on psychological safety across the whole industry.
How can generative AI tools like Co-Pilot or ChatGPT increase developer productivity?
Generative AI tools like Co-pilot or ChatGPT can reduce the mundane tasks of coding, reduce the cognitive load, and allow the creative human to apply their energies to the areas of development where creativity is best applied.
What are the components of responsible tech?
Responsible tech goes beyond compliance with rules and regulations and includes considerations such as climate impact, social good, privacy, safety, diversity, equity and inclusion, and the impact of bias.
How is project to product/#NoProjects gaining traction?
Project to product/#NoProjects are gaining traction as more organisations shift from seeing their IT departments as an overhead cost to truly partnering as a value adding service essential to running the business effectively and meeting customers’ needs.
What are the implications of large language models like ChatGPT?
The implications of large language models like ChatGPT include legal battles around open source licensing and copyright, the potential for data privacy breaches, and the use of ChatGPT to generate malware.
👍 This article provides a comprehensive overview of the trends in culture and methods in the software engineering industry. It provides a wealth of information about the various topics discussed and is a great resource for further learning.
👎 This article is overly long and could have been written in a more concise manner. Some of the topics discussed are too detailed and could have been summarized in a shorter form.
Me: It's about some of the key trends in culture and methods in tech for the year 2023. It talks about the implications of the layoffs in big tech and the emergence of large language models like ChatGPT, as well as the need for responsible tech and hybrid workplaces. It also discusses the worth of an architect, team topologies, Staff Plus roles, and workplace design.
Friend: Wow, that's a lot to unpack! It sounds like the tech industry is really going through some changes.
Me: Yeah, it is. It's interesting to see how the industry is dealing with things like layoffs and the emergence of AI. It's also interesting to see how companies are adapting to the hybrid workplace and how they're supporting their employees during these changes. It'll be fascinating to see how these trends continue to shape the tech industry over the coming years.
- Research and understand the implications of large language models such as ChatGPT and the potential risks associated with using them.
- Develop a responsible technology strategy for your organisation, considering the potential impacts of the products you are building and how to actively prevent harm.
- Investigate team topologies that support rapidly evolving organisations and the remote/hybrid workforce, and develop processes for retooling teams to optimise for value delivery and minimising cognitive load.
- Psychological Safety
- A term used to describe a work environment where people feel safe to take risks and be vulnerable in front of each other.
- Generative AI
- Artificial intelligence that is able to generate new content, such as text, images, or audio.
- Responsible Tech
- Technology that is designed and developed with ethical considerations in mind, such as climate impact, social good, privacy, safety, diversity, equity, and inclusion.
- Asynchronous Work
- Working on tasks independently, without the need for real-time collaboration or communication.
- Hybrid Workplaces
- A combination of remote and in-person work.
- Large Language Models
- AI models that are able to generate large amounts of text, such as ChatGPT.
- Prompt Engineering
- The skill of crafting questions to ask AI models in order to get the desired results.
- A combination of DevOps and Sustainability, focusing on the social, environmental, and economic needs of stakeholders.
- Project to Product
- A shift from project-based working to product-based working.
- Value Stream Management
- A process used to visualise and optimise the development process in end-to-end DevOps implementations.
- Conway’s Law
- A law that states that the structure of a system will be determined by the structure of the organization that created it.
- Reverse Conway
- A technique used to align communication in order to be more effective.
- Team Topologies
- Patterns used to guide organisations in restructuring teams to optimise for value delivery and minimise cognitive load.
- Staff Plus
- A role that does not require people management, but instead focuses on technical skills.
- Evidence Based Management
- A process used to maximise value delivered and focus on business outcomes.
- Design Docs
- Documents used to describe the design of a system.
- Request for Comments, documents used to describe a proposed change to a system.
- Architectural Decision Records, documents used to record decisions made about the architecture of a system.