Coding Chats episode 62 - John Crickett engages in a deep conversation with James about personal branding, building in public, and the challenges of launching a product. James shares his journey of using LinkedIn to build his personal brand, emphasizing the importance of transparency and community feedback in his projects. He recounts how his social network gained 20,000 users in the first 24 hours due to his public approach, which not only helped him secure jobs but also fostered a sense of community around his work.

The discussion also touches on the significance of mental health awareness and the need for open conversations in the workplace, particularly in the tech industry.As they delve into James's latest project, Bearly Fit, they explore the balance between creating a minimum viable product and ensuring quality. James reflects on the expectations that come with building in public and how he has navigated the challenges of app development while maintaining a connection with his audience. The conversation wraps up with insights on the role of AI in coding and the importance of mentoring junior developers, highlighting the need for a supportive environment in tech.

Chapters

00:00 The Power of Personal Branding

06:35 Agility in Development: Lessons Learned

18:29 Building in Public: Success and Challenges

26:08 Streaming and Job Search: A Double-Edged Sword

35:36 The Importance of Mentoring New Developers

40:22 Building in Public: The Journey of Barely Fit

52:58 Challenges and Expectations in App Development

58:54 Leveraging AI in Development

01:05:39 Final Thoughts and Future Plans

01:06:06 Exploring Related Content

James's Links:

https://linktr.ee/mahybe

https://bearly.fit

John's Links:

John's LinkedIn: https://www.linkedin.com/in/johncrickett/

John’s YouTube: https://www.youtube.com/@johncrickett

John's Twitter: https://x.com/johncrickett

John's Bluesky: https://bsky.app/profile/johncrickett.bsky.social

Check out John's software engineering related newsletters: Coding Challenges: https://codingchallenges.substack.com/ which shares real-world project ideas that you can use to level up your coding skills.

Developing Skills: https://read.developingskills.fyi/ covering everything from system design to soft skills, helping them progress their career from junior to staff+ or for those that want onto a management track.

Takeaways

Building in public can lead to unexpected success.

Transparency in struggles fosters community support.

Personal branding is crucial for career advancement.

Quality matters in app development, especially when building in public.

Mentoring junior developers is an investment in the future.

Coding Chats episode 61 - John Crickett interviews Austen about his new book and the significance of behavioural interviews in the hiring process, especially in today's competitive job market. Austen shares insights on what interviewers look for, how to tailor preparation for specific companies, and the importance of storytelling in interviews. He emphasizes the impact of AI on the interview process and discusses how candidates can effectively present their experiences, particularly in conflict resolution scenarios. The conversation also covers the different expectations for candidates at various career stages and the importance of preparation and practice in mastering behavioural interviews.

Chapters

00:00 The Importance of Behavioral Interviews

02:43 What Interviewers Look For

05:32 Understanding Company Expectations

07:48 Austen's Background and Expertise

09:59 The Impact of AI on Interviews

12:10 Behavioral Interviews Beyond Big Tech

14:11 Crafting Your Introduction

18:55 Selecting Stories for Interviews

24:32 Creating Compelling Interview Stories

28:38 The Difference Between Junior and Senior Engineers

29:50 Crafting Compelling Stories for Interviews

31:28 Timing and Length of Stories in Interviews

33:34 Selecting the Right Story for the Interview

37:05 The Importance of Scope and Relevance in Storytelling

37:52 Using the Menu Technique for Story Selection

40:37 Enhancing Conflict Resolution Stories

43:48 The Drama in Conflict Resolution

48:12 Improving Conflict Resolution Narratives

55:00 The Role of Escalation in Conflict Resolution

58:11 The Big Three Questions in Behavioral Interviews

59:54 Understanding Interview Dynamics

01:03:08 The Importance of Asking Questions

01:06:56 Feedback Loops in Behavioral Interviews

01:12:04 Navigating Different Career Stages

01:17:52 Adapting Stories for Different Organizations

01:23:02 Leveraging Personal Projects in Interviews

01:24:41 Key Takeaways for Interview Success

Austen's Links:

https://thebehavioral.substack.com/

https://www.amazon.com/dp/B0G6CM9T87

John's Links:

John's LinkedIn: https://www.linkedin.com/in/johncrickett/

John’s YouTube: https://www.youtube.com/@johncrickett

John's Twitter: https://x.com/johncrickett

John's Bluesky: https://bsky.app/profile/johncrickett.bsky.social

Check out John's software engineering related newsletters: Coding Challenges: https://codingchallenges.substack.com/ which shares real-world project ideas that you can use to level up your coding skills.

Developing Skills: https://read.developingskills.fyi/ covering everything from system design to soft skills, helping them progress their career from junior to staff+ or for those that want onto a management track.

Takeaways

Behavioral interviews are crucial for differentiating candidates in a competitive job market.

Understanding what interviewers are looking for can significantly improve your chances of success.

Tailoring your preparation to the specific company and role is essential.

Your past experiences and stories are likely more valuable than you think.

Practice and preparation are key to performing well in interviews.

Coding Chats episode 60 - John Crickett and Paul discuss the transformative impact of AI on software engineering, exploring topics such as spec-driven development, the importance of small batches, and the challenges of requirements gathering. They delve into the evolving role of AI tools, the need for effective communication, and the balance between productivity and code quality. The discussion also touches on the future of AI in development, the significance of ownership in coding, and the potential for specialized AI agents to enhance workflows. Paul shares valuable tips for leveraging AI in software engineering, emphasizing the importance of joy, working in small units, and maintaining humility in the face of rapid technological change.

Chapters

00:00 AI in Software Engineering: A New Era

03:36 The Revelation of Prompt-Driven Development

06:08 Spec-Driven Development vs. Waterfall

09:16 The Importance of Small Batches in AI Development

12:05 Ownership and Responsibility in AI-Generated Code

14:57 The Challenges of Outsourcing and Communication in Software Development

20:15 The Future of Programming and Communication

23:38 AI Tools and Upstream Bottlenecks

27:18 Understanding JetBrains' AI Integration

31:40 User Experience and AI Interaction

35:42 Opinionated Workflows in Software Development

37:24 Finding Joy in AI-Assisted Engineering

Paul's Links:https://buildermethods.com/agent-os

John's Links:

John's LinkedIn: https://www.linkedin.com/in/johncrickett/

John’s YouTube: https://www.youtube.com/@johncrickett

John's Twitter: https://x.com/johncrickett

John's Bluesky: https://bsky.app/profile/johncrickett.bsky.social

Check out John's software engineering related newsletters: Coding Challenges: https://codingchallenges.substack.com/ which shares real-world project ideas that you can use to level up your coding skills.

Developing Skills: https://read.developingskills.fyi/ covering everything from system design to soft skills, helping them progress their career from junior to staff+ or for those that want onto a management track.

Takeaways

AI is revolutionizing software engineering practices.

Spec-driven development formalizes the way we instruct AI agents.

Small batches improve productivity and maintain context.

Ownership of code is crucial for long-term success.

Quality of code generated by AI is more important than quantity.

Effective communication is key in AI-assisted development.

Specialized AI agents will enhance the development process.

JetBrains is evolving its tools to integrate AI effectively.

Developers should find joy in their work, even with AI assistance.

Humility is essential as we navigate the future of AI in programming.

Coding Chats episode 59 - Josh discusses the AI agent framework Rig, its functionalities, and the benefits of using Rust for its implementation. He explains the concept of agents and embeddings, their applications, and the importance of managing context windows in AI models. Josh shares his journey of learning Rust, transitioning from a technical content writer to a co-maintainer of Rig, and the challenges faced while building a coding agent. He emphasizes effective prompting strategies and the importance of concise communication with AI models. The conversation concludes with insights on contributing to Rig and the future of AI frameworks.

Chapters

00:00 Introduction to Rig and AI Frameworks

02:56 Understanding Agents and Embeddings

05:24 Use Cases for Embeddings and Context Management

07:53 Benefits of Using Rig in Rust

10:10 Learning Rust and Overcoming Challenges

12:56 Transitioning to Rig and AI Focus

15:21 Building a Coding Agent: Challenges and Insights

17:45 Prompting Techniques and Best Practices

20:06 Contributing to Rig and Community Engagement

22:49 Final Thoughts and Future Directions

Josh's Links:

https://github.com/0xPlaygrounds/rig

https://www.rustnationuk.com/speaker/joshua-mo

https://www.linkedin.com/in/joshua-mo-4146aa220/

John's Links:

John's LinkedIn: https://www.linkedin.com/in/johncrickett/

John’s YouTube: https://www.youtube.com/@johncrickett

John's Twitter: https://x.com/johncrickett

John's Bluesky: https://bsky.app/profile/johncrickett.bsky.social

Check out John's software engineering related newsletters: Coding Challenges: https://codingchallenges.substack.com/ which shares real-world project ideas that you can use to level up your coding skills.

Developing Skills: https://read.developingskills.fyi/ covering everything from system design to soft skills, helping them progress their career from junior to staff+ or for those that want onto a management track.

Takeaways

Rig is an AI agent framework that simplifies AI integration.

Agents in AI are often misunderstood due to marketing hype.

Embeddings serve as data representations for various applications.

Retrieval augmented generation is a common use case for embeddings.

Managing the context window is crucial for effective AI performance.

Using Rust for Rig provides type safety and performance benefits.

Learning Rust can be challenging but rewarding with the right approach.

Josh transitioned from content writing to engineering at Rig.

Building a coding agent revealed the complexities of AI.

Concise prompts are essential to avoid overwhelming AI models.

In this special holiday episode of Coding Chats, John Crickett answers audience questions about software engineering careers, the impact of AI, programming languages, and the importance of leadership. He discusses how to rebuild an engineering career, the significance of meaningful projects, and the readiness of self-taught developers. The conversation also touches on insights gained from hosting the podcast and the evolving landscape of software development.

Chapters

00:00 Introduction to the Coding Chats Holiday Special

00:22 Rebuilding an Engineering Career in 2025

01:01 The Future of Software Engineering with AI

01:27 Learning Programming: Starting Points and Languages

02:27 Breaking the No Experience Loop for Developers

04:17 Meaningful Experience: Projects and Contributions

05:02 Self-Taught Developers: Readiness and Opportunities

06:07 Qualities of a Good Software Engineering Leader

06:52 Insights from 18 Months of Coding Chats

07:43 Architecture as a Strategic Concern in Engineering

John's Links:

John's LinkedIn: https://www.linkedin.com/in/johncrickett/

John’s YouTube: https://www.youtube.com/@johncrickett

John's Twitter: https://x.com/johncrickett

John's Bluesky: https://bsky.app/profile/johncrickett.bsky.social

Check out John's software engineering related newsletters: Coding Challenges: https://codingchallenges.substack.com/ which shares real-world project ideas that you can use to level up your coding skills.

Developing Skills: https://read.developingskills.fyi/ covering everything from system design to soft skills, helping them progress their career from junior to staff+ or for those that want onto a management track.

Takeaways

Leverage AI to find answers quicker than before.

Reading and curiosity are key habits for growth.

All parts of software engineering will survive AI advancements.

Focus on learning computer science fundamentals first.

Choose programming languages based on your interests.

Building personal projects can help you get noticed.

Self-taught developers can be just as capable as those with degrees.

Good leadership adapts to the situation and team needs.

The software development field is diverse and evolving.

Architecture should be treated as a strategic concern.

Coding Chats episode 58 - John Crickett and Melinda Fekete delve into the concept of feature ops, emphasizing the importance of managing code in production effectively. They discuss feature flags as a mechanism for safe testing and releasing of code, the challenges of managing feature flags, and the significance of user feedback in software development. The conversation also touches on deployment strategies like canary releases, learning from recent outages, and the benefits of testing in production. Additionally, they explore the role of feature flag providers and the trade-offs associated with adopting feature flags in software projects.

Chapters

00:00 Introduction to Feature Ops

02:46 Managing Feature Flags Effectively

07:41 Deployment Strategies: Canary Releases and Gradual Rollouts

12:23 The Importance of Dogfooding and User Feedback

15:05 Learning from Recent Outages

19:13 Testing in Production and Its Benefits

21:51 Managing Feature Flags at Scale

27:01 Feature Flag Providers and Their Benefits

30:50 Involving Product Teams in Feature Flag Management

31:45 Trade-offs and Downsides of Feature Flags

39:35 Exploring Related Content

Melinda's Links:

A guide on working with feature flags in code: https://docs.getunleash.io/guides/manage-feature-flags-in-code

Open-source repo: https://github.com/Unleash/unleash

John's Links:

John's LinkedIn: https://www.linkedin.com/in/johncrickett/

John’s YouTube: https://www.youtube.com/@johncrickett

John's Twitter: https://x.com/johncrickett

John's Bluesky: https://bsky.app/profile/johncrickett.bsky.social

Check out John's software engineering related newsletters: Coding Challenges: https://codingchallenges.substack.com/ which shares real-world project ideas that you can use to level up your coding skills.

Developing Skills: https://read.developingskills.fyi/ covering everything from system design to soft skills, helping them progress their career from junior to staff+ or for those that want onto a management track.

Takeaways

Feature ops focuses on managing code in production effectively.

Feature flags allow for safe testing and releasing of code without redeployment.

Managing the lifecycle of feature flags is crucial for maintenance.

Canary releases and gradual rollouts help mitigate risks during deployment.

User feedback is essential for improving software products.

Recent outages highlight the need for better feature management practices.

Testing in production can catch issues that staging environments may miss.

Feature flag providers offer tools for managing flags at scale.

Trade-offs exist when adopting feature flags, especially for smaller projects.

Effective management of feature flags can empower teams and improve deployment speed.

Coding Chats episode 57 - Owain Lewis and John Crickett explore the role of AI in software engineering, discussing the integration of AI into production systems and the challenges faced by AI engineers. They delve into the nuances of AI application, from building scalable systems to the importance of human oversight in AI-driven workflows.

Chapters

00:00 Defining the Role of AI Engineer

03:13 Exploring Large Language Models (LLMs)

06:15 Use Cases for LLMs in Business

09:22 The Non-Deterministic Nature of AI

12:12 AI in Software Engineering: The Future

15:11 The Role of AI in Code Review

17:53 The Bottleneck of Requirements Gathering

20:38 Leveraging AI Throughout the Software Lifecycle

29:53 Leveraging AI for Efficient Documentation

30:47 AI in API Design and Review

32:22 Spectrum Driven Development with AI

34:06 The Role of Requirements in Software Engineering

40:05 The Future of Programming Languages and AI

49:54 Understanding Context and Prompt Engineering

56:38 Exploring Related Content

Owain's Links:

Substack: https://newsletter.owainlewis.com/subscribe

AI Engineer: https://skool.com/aiengineer

John's Links:

John's LinkedIn: https://www.linkedin.com/in/johncrickett/

John’s YouTube: https://www.youtube.com/@johncrickett

John's Twitter: https://x.com/johncrickett

John's Bluesky: https://bsky.app/profile/johncrickett.bsky.social

Check out John's software engineering related newsletters:

Coding Challenges: https://codingchallenges.substack.com/ which shares real-world project ideas that you can use to level up your coding skills.

Developing Skills: https://read.developingskills.fyi/ covering everything from system design to soft skills, helping them progress their career from junior to staff+ or for those that want onto a management track.

Takeaways

AI engineering involves building software with AI, focusing on production systems.

AI engineers bridge the gap between AI model builders and software developers.

Understanding AI's unique paradigm is crucial for effective system architecture.

AI should be used minimally and where it makes sense, not everywhere.

Human oversight is essential in AI-driven workflows to ensure reliability.

Large language models (LLMs) are a significant focus in current AI trends.

AI can enhance business processes through automation and natural language interfaces.

AI's role in software engineering includes improving code quality and efficiency.

AI tools can amplify both good and bad engineering practices.

Experimentation and building real projects are key to learning AI engineering.

Coding Chats episode 56 - Paul Grenyer discusses his journey to writing a book on team leadership, sharing insights on the differences between leadership and management, common mistakes new leaders make, the importance of delegation, and building trust within teams. He emphasizes the need for curiosity in understanding both technical and business domains, and reflects on the role of AI in software development. The discussion culminates in insights from his book, which aims to guide new leaders in navigating their roles effectively.

Chapters

00:00 The Journey to Team Leadership

08:44 Leadership vs Management

10:33 Common Mistakes of New Leaders

15:58 The Importance of Delegation

19:46 Curiosity in Leadership

22:33 Insights from the Book

27:57 The Role of Technical Skills in Leadership

31:58 The Impact of AI on Software Engineering

Paul's Links:

Paul's website: https://paulgrenyer.com/

John's Links:

John's LinkedIn: https://www.linkedin.com/in/johncrickett/

John’s YouTube: https://www.youtube.com/@johncrickett

John's Twitter: https://x.com/johncrickett

John's Bluesky: https://bsky.app/profile/johncrickett.bsky.social

Check out John's software engineering related newsletters: Coding Challenges: https://codingchallenges.substack.com/ which shares real-world project ideas that you can use to level up your coding skills.

Developing Skills: https://read.developingskills.fyi/ covering everything from system design to soft skills, helping them progress their career from junior to staff+ or for those that want onto a management track.

Takeaways

Letting go of doing the work is crucial for leaders.

Listening to your team is essential for effective leadership.

Delegation is often the hardest skill for new leaders to master.

Building trust requires admitting mistakes and being approachable.

Curiosity about team members' experiences can lead to better solutions.

Technical knowledge helps leaders mediate and understand team dynamics.

AI can enhance productivity but requires careful implementation.

Leadership is about guiding a team towards a common goal.

Understanding the business domain is vital for effective leadership.

Encouraging a fun and open team culture fosters collaboration.