Limitations of AI bots and the role of AI in teaching

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Teaching Code, Shaping Futures — John Crepezzi on Ruby, Bootcamps, and AI

Ruby for All

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CHAPTER

Limitations of AI bots and the role of AI in teaching

This chapter discusses the limitations of using AI bots for answering questions and the role of AI in teaching. It also explores the changing user experience in technology and the effectiveness of boot camps in teaching programming skills.

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Episode notes

In this episode, Andrew and Julie chat with guest John Crepezzi, a veteran in the Ruby community, founder of All Aboard Bootcamp, and currently a Software Engineer at Jane Street. Today, they discuss John’s experience running a coding bootcamp, share insights on teaching programming, and emphasize the importance of community in learning. Additionally, they explore functional programming in OCaml, highlighting how functional programming can be implemented in Ruby. Also, John dives into the potential impact of AI, particularly language models like ChatGPT, on education and software development, and there’s a discussion on resume writing for new coders and future trends in AI and automation. Hit download now to hear more!

[00:01:08] Julie introduces John, her former bootcamp instructor, and he tells us about himself and his extensive experience on the Ruby community.

[00:02:14] Andrew asks John about the gem he is most proud of creating, and he explains his pride in the “ice_cube gem” for recurring date math.

[00:04:30] John discusses the technical challenges and community contributions to ice_cube.

[00:05:25] Julie discusses her positive experience with All Aboard Bootcamp and how the bootcamp helped her connect different programming concepts.

[00:07:26] John describes his teaching philosophy for covering a broad amount of material quickly and he stresses the importance of learning to ask the right questions. He uses a metaphor from the movie “Tommy Boy” to emphasize teaching practical skills.

[00:11:26] John relates the approach to teaching with the usefulness of ChatGPT and Julie expresses her preference for receiving explanations in small chunks and using bullet points for clarity. John discusses how LLMs can assist in refining questions before providing answers.

[00:12:49] Andrew asks about AI’s role in teaching and its potential impact. John, an AI professional, offers his perspective on AI in the short and term, specifically its ability to understand and respond to human language. He speculates on the future of human computer interaction, where structured systems may become unnecessary as LLMs bridge the communication gap.

[00:16:03] Andrew agrees with John’s vision of the future, acknowledging the inefficiencies in current user flows. John compares the evolution from programming VCRs to using DVRs to the potential of LLMs simplifying interaction with technology.

[00:16:55] John describes the motivation behind starting a bootcamp and the realization of the industry’s selection bias towards already skilled programmers. He shares the story of how the high cost of bootcamps and their screening processes inspired him to teach a more accessible camp.

[00:21:10] Julie is impressed by John’s ability to manage the bootcamp alongside his full-time job, family responsibilities, and other commitments. She also talks about the final project of the bootcamp, where John acted as a project manager and provided structure and guidance.

[00:23:31] Andrew inquires about what John thinks is the number one mistake new programmers make on their resume. John emphasizes the importance of highlighting projects on a resume, especially for those transitioning from another industry, and advises focusing on the outcomes and transferable skills gained from previous experiences.

[00:25:35] John considers formatting critical for resumes, suggesting less content with more white space and a clear hierarchy can be more effective than too much information.

[00:26:44] Another thing John advises is keeping resumes to one page unless there’s a compelling reason for more, like academic positions or extensive project work.

[00:27:18] Reflecting on the bootcamp, John wishes he had sought more assistance with grading and feedback to reduce the workload.

[00:28:34] John praises the students, particularly Julie, for fostering a supportive community outside of the classroom.

[00:31:07] Discussing programming languages, John expresses his favor for OCaml and functional programming, arguing that functional patterns can be beneficial even in languages like Ruby.

[00:32:13] Find out where you can follow John online.

[00:32:58] We end with John reaffirming his love for Ruby and expresses enthusiasm for its future and mentioning his work with Eileen on Active Record and Rails’ influence on web frameworks in other languages.

Panelists:

Andrew Mason

Julie J.

Guest:

John Crepezzi

Sponsors:

GoRails

Honeybadger

Links:

Andrew Mason X/Twitter

Andrew Mason Website

Julie J. X/Twitter