The New Developer: Help Your Engineering Org Navigate Issues of Trust, Agency, & Skill Threat as They Adopt Generative AI from Pluralsight

In this breakout, we’ll tackle AI adoption inside of engineering organizations head-on. You’ll hear about original, empirically grounded research on how software engineers and leaders are thinking about—and rethinking—the role of the software practitioner during this new age of AI-assisted coding. But we’re giving you more than the research in this session. We’ll walk you through our generative AI Adoption Toolkit, which comes complete with a benchmarking assessment adapted from our research. This toolkit allows your org and teams to benchmark their AI adoption readiness and respond appropriately with tools that allow you to meet your teams and engineers where they’re at in their AI adoption journey.

But we’re giving you more than the research in this session. We’ll walk you through our generative AI Adoption Toolkit, which comes complete with a benchmarking assessment adapted from our research. This toolkit allows your org and teams to benchmark their AI adoption readiness and respond appropriately with tools that allow you to meet your teams and engineers where they’re at in their AI adoption journey.

What's inside

Syllabus

The New Developer: Help Your Engineering Org Navigate Issues of Trust, Agency, & Skill Threat as They Adopt Generative AI

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

This course is for engineering organizations looking to adopt generative AI

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in The New Developer: Help Your Engineering Org Navigate Issues of Trust, Agency, & Skill Threat as They Adopt Generative AI with these activities:

Review software development life cycle (SDLC)

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Refresh your knowledge of the software development life cycle to better understand how AI can be integrated into the process.

Browse courses on Software Development Life Cycle

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Review the phases of the SDLC
Identify the key activities in each phase
Consider how AI can be applied to each phase

Work through the Generative AI Adoption Toolkit

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Utilize the provided toolkit to assess your organization's AI adoption readiness and develop a tailored adoption strategy.

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Complete the benchmarking assessment
Review the provided resources
Develop an adoption plan

Create a presentation on AI adoption challenges

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Develop a presentation that outlines the challenges associated with AI adoption, both for software engineers and engineering organizations as a whole.

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Research the topic
Outline your presentation
Create the slides
Practice giving your presentation

One other activity

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Implement an AI solution within your engineering org

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Identify an area within your organization where AI can be applied, and develop and implement a solution using AI techniques.

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Identify a problem that can be solved using AI
Research and select an AI solution
Implement the AI solution
Monitor and evaluate the results

Career center

Learners who complete The New Developer: Help Your Engineering Org Navigate Issues of Trust, Agency, & Skill Threat as They Adopt Generative AI will develop knowledge and skills that may be useful to these careers:

Engineering Manager

This course can provide benefit to Engineering Managers. As Engineering Managers are likely to be the ones who are responsible for the adoption of generative AI in their teams, they will need to have an understanding of the issues surrounding that adoption.

See salaries and explore the career path for Engineering Manager

Technical Project Manager

Taking this course may benefit Technical Project Managers. As Technical Project Managers may be the ones in charge of evaluating generative AI adoption, this course will give them the tools to assess readiness, navigate issues with their teams, and understand the implications generative AI will have on team members and their work.

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Software Development Manager

This course may be of use to Software Development Managers. As Software Development Managers will be responsible for the adoption of generative AI in engineering teams, it will be essential that they complete this course to be made aware of the challenges and common pitfalls.

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Chief Technology Officer

This course may be useful to Chief Technology Officers. As Chief Technology Officers will be the ones who need to be able to champion generative AI adoption, this course will give them the tools to assess readiness, navigate issues across the organization, and understand the implications generative AI will have on all teams and their work.

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Software Architect

Software Architects may find this course to be useful. As Software Architects will be the ones responsible for evaluating the use of generative AI in their organizations, they will need to be aware of the challenges and common pitfalls.

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Systems Architect

This course may be useful to Systems Architects. As Systems Architects will be the ones responsible for evaluating the use of generative AI in their organizations, they will need to be aware of the challenges and common pitfalls.

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Machine Learning Engineer

Machine Learning Engineers may find this course useful. As Machine Learning Engineers work on tasks where generative AI could be leveraged, understanding how to use it and assessing its readiness for different use cases will greatly benefit their work.

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Data Architect

This course may be of use to Data Architects. As Data Architects will be the ones responsible for evaluating the use of generative AI in their organizations, they will need to be aware of the challenges and common pitfalls.

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Product Manager

Product Managers may find this course to be of use. As Product Managers work closely with engineering teams, they will need to understand the implications of generative AI adoption and how it may affect their teams, their work, and their products.

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AI Engineer

This course may be useful to AI Engineers. As AI Engineers work with generative AI, they will benefit greatly from understanding its strengths and weaknesses and being able to assess its readiness for adoption.

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Enterprise Architect

Taking this course may benefit Enterprise Architects. As Enterprise Architects will be the ones responsible for evaluating the use of generative AI in their organizations, they will need to be aware of the challenges and common pitfalls.

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Data Scientist

This course can help Data Scientists expand their use of generative AI in their work. As data science models become more complex, being able to leverage AI to assist in their coding can be of great benefit.

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Research Scientist

This course may be of use to Research Scientists. As Research Scientists continue to find new and innovative ways to use AI, including generative AI, this course will provide a great introduction to some of the challenges that their teams may encounter and how to overcome them.

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DevOps Engineer

This course may be useful to DevOps Engineers. As DevOps Engineers work closely with software engineers, they will need to understand how to leverage generative AI to achieve good results in their daily tasks.

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Software Engineer

This course may be of use to Software Engineers. This course can help Software Engineers make good use of generative AI in their daily coding tasks. As this technology continues to be adopted in the engineering realm, it will be essential for those wielding it to understand it well.

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