Coding Chats

Coding Chats episode 72 - Charles Humble and John Crickett explore why professional skills — communication, critical thinking, and documentation — are arguably more important than writing code itself. Drawing on his O'Reilly shortcut article series and a career that began with an English Literature degree, Charles makes the case that these so-called "soft skills" are actually core to the job, and that they can be learned through practice by anyone, regardless of background or natural talent.The conversation also digs into the seismic impact of AI on the software industry. Charles shares his nuanced take: while generative AI tools are reshaping how code gets written, the durable skills — understanding systems, debugging, domain knowledge, and clear communication — matter more than ever. Rather than panic or uncritical adoption, Charles encourages engineers to focus on what remains irreplaceable, and to approach an uncertain future with curiosity and a willingness to take shots on goal.Chapters00:00 The Importance of Professional Skills for Software Engineers06:24 Navigating the Impact of AI on Software Engineering12:09 The Evolving Role of Software Engineers17:50 AI for the Rest of Us: Bridging the Knowledge Gap25:43 The Ethical Implications of AI and Communication27:12 Ethics in AI Development31:04 Improving Communication Skills for Engineers38:00 Overcoming the Fear of Writing42:15 The Importance of Public Speaking50:17 The Journey of Continuous Learning54:30 Exploring Related ContentCharles's Links:https://www.linkedin.com/in/charleshumble/\https://bsky.app/profile/charleshumble.bsky.socialJohn's Links:John's LinkedIn: https://www.linkedin.com/in/johncrickett/John’s YouTube: https://www.youtube.com/@johncrickettJohn's Twitter: https://x.com/johncrickettJohn's Bluesky: https://bsky.app/profile/johncrickett.bsky.socialCheck 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"Soft skills" is a misleading term — Communication, critical thinking, and documentation aren't soft skills; they're literally the job.Non-technical skills can be learned — You don't need natural talent. Like anything, they improve with deliberate practice.Career success often comes from non-coding skills — Charles found his own progression was driven more by presenting to executives and systems thinking than by programming ability.Communication becomes critical as you progress — From mid-level upwards, working with stakeholders, mentoring, and documentation determine who makes it to senior and beyond.Nobody knows what programming will look like in two years — Even Kent Beck acknowledges the deep uncertainty ahead.AI has shifted engineers from "extract" to "explore" — Programmers who felt settled in well-defined work have been thrown into a messier, less certain phase by generative AI.The durable skills are the same ones that always mattered — Debugging, domain knowledge, system design, and communication are as valuable now as ever — arguably more so."Coding is dead" is nonsense — Software engineering has always been mostly about understanding what to build and why. Writing code was always a small part of it.Try things and see what happens — No grand plan needed. If you don't kick the ball, you're guaranteed not to score.

Coding Chats episode 71 - Anita Kalmane-Boot talks to John Crickett about neurodiversity, its spectrum, strengths, challenges, and how organizations can foster inclusive environments, especially in software teams. Discover practical strategies for recruitment, team building, and accommodating neurodivergent individuals to enhance innovation and productivity.Chapters00:00 Understanding Neurodiversity03:32 The Spectrum of Neurodivergence06:30 Strengths of Neurodivergent Individuals09:08 Creating Inclusive Teams12:10 Improving Recruitment Practices15:00 Work Environment for Neurodivergent Individuals17:43 The Connection Between Neurodiversity and Software Engineering23:38 Exploring Neurodiversity in Engineering24:39 The Impact of AI on Neurodivergent Workers27:08 Inclusive Recruitment Practices32:57 The Role of Managers in Hiring38:46 Disclosing Neurodivergence in Job Interviews44:11 The Future of Neurodiversity in the Workplace46:11 Exploring Related ContentAnita's Links:https://www.linkedin.com/in/anitakalmane/John's Links:John's LinkedIn: https://www.linkedin.com/in/johncrickett/John’s YouTube: https://www.youtube.com/@johncrickettJohn's Twitter: https://x.com/johncrickettJohn's Bluesky: https://bsky.app/profile/johncrickett.bsky.socialCheck 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.TakeawaysNeurodiversity covers a wide spectrum — including ADHD, autism, and dyslexia — not just a single condition.Neurodivergent individuals often have exceptional strengths like pattern recognition, deep focus, and creative problem-solving.These traits make neurodivergent thinkers particularly valuable in software engineering and tech roles.Traditional hiring processes can unintentionally screen out neurodivergent candidates.Small recruitment adjustments — like sharing questions in advance or allowing written responses — can open the door to better talent.Managers are key to creating environments where neurodivergent employees can thrive.Many neurodivergent people struggle with whether to disclose during interviews — psychological safety reduces that burden.AI has the potential to reduce friction for neurodivergent workers, but also brings new challenges.Embracing neurodiversity isn't just ethical — it leads to stronger, more innovative teams.

Coding Chats episode 70 - Aaron LeClair discusses the top five mistakes startup CTOs make, covering everything from misunderstanding development pipelines to failing to make the leadership identity transition. The conversation explores AI adoption parallels, team diversity, hiring pitfalls, the "move fast and break things" mantra, and why a CTO's first team should be the C-suite — not the engineering team.Chapters00:00 Scaling the Pipeline: Common Mistakes of CTOs03:13 Understanding the Development Environment05:59 The Importance of Team Diversity09:03 Building Effective Teams11:53 Hiring for Fit: The Cost of Misalignment14:36 The Role of Leadership in Team Dynamics33:52 Building Effective Teams as a Leader37:35 Transitioning from Engineer to Leader43:31 Hiring the Right Technical Leaders46:01 Understanding the Role of CTO in Start-ups54:40 The Balance of Speed and Quality in Development01:01:24 Exploring Related ContentAaron's Links:https://www.linkedin.com/in/aaronleclair/John's Links:John's LinkedIn: https://www.linkedin.com/in/johncrickett/John’s YouTube: https://www.youtube.com/@johncrickettJohn's Twitter: https://x.com/johncrickettJohn's Bluesky: https://bsky.app/profile/johncrickett.bsky.socialCheck 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.TakeawaysScaling your dev team without first fixing QA, product management, and stakeholder flow will create more problems than it solves.AI adoption falls into the same trap — faster code generation doesn't help if requirements, testing, and deployment are still bottlenecks.Invest in tooling, DevOps, and documented processes early, as poor systems frustrate great engineers just as much as poor management.Always ask why a process exists — the original reason may no longer apply, and changing it is often easier than expected.Build teams like an Ocean's 11 cast: diverse in skills, backgrounds, and working styles, not a clone army of specialists in the same stack.Hire generalists with depth in different areas who can flex as start-up needs shift, and reserve deep specialists for your true business differentiators.A failed hire is most often a leadership failure — you had more information than the candidate, so treat every miss as a learning opportunity.The most important things a CTO does are hiring and developing people — if a leader is still submitting PRs to a team of more than three, that's a red flag.A CTO's primary team is the C-suite, not the engineering team — treating engineers as "your team" creates an us-vs-them culture that damages the whole business.Match technical leadership seniority to your company stage — pre-product-market-fit you need a generalist head of engineering, not a full CTO."Move fast and break things" is valid pre-product-market-fit for validating hypotheses, but once you have real customers it becomes an excuse for poor process.

Coding Chats episode 69 - John Crickett and Sairam Sundaresan discuss the evolving landscape of artificial intelligence (AI) and its implications for learning, software development, and organizational culture. Sairam emphasizes the importance of bridging the gap between technical and business perspectives on AI, advocating for a hands-on approach to learning. They explore the hype surrounding AI, particularly large language models (LLMs), and the need for a cultural transformation within organizations to effectively adopt AI technologies. The discussion also touches on the future of software engineering in an AI-driven world, highlighting the blurred lines between roles and the necessity for continuous learning and adaptation.Chapters00:00 Bridging the Gap: Understanding AI for Everyone03:44 Learning AI: A Practical Approach06:29 The Evolution of AI: From Hype to Reality09:33 Generative AI: The Current Landscape and Future Directions12:35 Transformative Use Cases: Beyond Basic Applications15:23 The Art of Questioning: Engaging with AI Effectively18:36 Navigating Large Codebases: AI as a Tool for Engineers21:24 Writing and Coding: Learning from the Masters27:42 Harnessing Subagents for Efficiency29:48 Bridging the Gap Between Business and Tech31:35 Cultural Transformation in AI Adoption34:22 Understanding AI Fundamentals for Better Collaboration36:11 The People Problem in AI Implementation39:26 Evolving Roles in Software Engineering42:26 The Resurgence of Software Engineering44:37 Leading an AI-First Organization49:16 Learning by Doing in AI52:03 Navigating the Landscape of AI Research and Publications54:05 Exploring Related ContentSairam's Links:Book- AI for the Rest of Us:https://www.amazon.com/dp/B0F29THNLTSubstack Gradient Ascent: https://newsletter.artofsaience.comJohn's Links:John's LinkedIn: https://www.linkedin.com/in/johncrickett/John’s YouTube: https://www.youtube.com/@johncrickettJohn's Twitter: https://x.com/johncrickettJohn's Bluesky: https://bsky.app/profile/johncrickett.bsky.socialCheck 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.TakeawaysAI is essential for modern products and services.Bridging the gap between business and engineering is crucial.Learning AI requires a hands-on approach, not just theory.Cultural transformation is necessary for successful AI adoption.Understanding the basics of AI is vital for all roles.The hype around AI often overshadows other important areas.Software engineering is evolving with AI technologies.AI tools can enhance productivity but require thoughtful use.Continuous learning is key in the fast-paced AI landscape.The roles within organizations are becoming more integrated.

Coding Chats episode 68 - Paulina Dubas shares her experiences and insights on the importance of public speaking at conferences, the challenges engineers face in communication, and the benefits of networking within the tech community. She discusses the significance of understanding AI in the workplace, the ongoing issues of gender balance in tech, and the value of an MBA for engineers transitioning into business roles. The conversation emphasizes the need for inclusivity and the importance of sharing knowledge and experiences to foster growth in the industry.Chapters00:00 The Benefits of Speaking at Conferences05:07 Overcoming Public Speaking Challenges09:04 Key Lessons for Aspiring Speakers10:49 Navigating AI in the Workplace14:48 The Gender Balance in Tech22:07 Creating Inclusive Workplaces24:48 Consulting vs. Product Roles27:32 The Value of an MBA for Engineers34:28 Exploring Related ContentPaulina's LinksLinkedIn : https://www.linkedin.com/in/paulinadubas/website : https://paulinadubas.com/YouTube : https://www.youtube.com/@PaulinaDubasJohn's Links:John's LinkedIn: https://www.linkedin.com/in/johncrickett/John’s YouTube: https://www.youtube.com/@johncrickettJohn's Twitter: https://x.com/johncrickettJohn's Bluesky: https://bsky.app/profile/johncrickett.bsky.socialCheck 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.TakeawaysIt's beneficial to be involved in the community and put yourself out there.Public speaking helps deepen your understanding of topics.Overcoming the fear of public speaking can enhance communication skills.Networking at conferences can lead to valuable connections.You don't need to be an expert to speak at conferences.Starting small can build confidence for larger speaking engagements.AI tools need proper processes and training for effective use.Banning AI tools is a temporary solution that can lead to bigger issues.Gender balance in tech starts from early education and cultural perceptions.Consulting roles provide diverse experiences that accelerate learning.

Matt Boyle, Founder/CEO building Ona, an AI software-engineer platform. He explains autonomous AI agents that parallelize work across isolated cloud dev environments. They discuss planning mode that turns tickets into specs, enterprise security inside customer VPCs, managed model supply, and automations that scan, fix, and open pull requests while you sleep.

Coding Chats episode 66 - Alex Garella discusses the current state of the Rust job market, highlighting its mixed nature amidst broader software development trends. He emphasizes the importance of specific skills and industry experience, particularly in emerging technologies like data infrastructure. The impact of AI tools on software development and hiring practices is explored, along with strategies for breaking into the Rust market, including open source contributions and leveraging LinkedIn effectively.Chapters00:00 The Current State of the Rust Job Market03:15 Skills in Demand for Rust Developers05:46 Emerging Domains for Rust Applications08:44 Rust's Role in AI and Machine Learning11:38 The Evolution of Interview Processes14:30 Challenges in Hiring Rust Developers17:28 Navigating the Job Market as a New Rust Developer20:27 Leveraging LinkedIn for Job Opportunities23:21 Final Tips for Aspiring Rust DevelopersAlex's Links:https://rustjobs.dev/https://scalajobs.com/John's Links:John's LinkedIn: https://www.linkedin.com/in/johncrickett/John’s YouTube: https://www.youtube.com/@johncrickettJohn's Twitter: https://x.com/johncrickettJohn's Bluesky: https://bsky.app/profile/johncrickett.bsky.socialCheck 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.TakeawaysThe Rust job market is currently mixed, with both opportunities and challenges.Experience in specific industries is often more valuable than tool-specific knowledge.Emerging technologies, especially in data infrastructure, are driving demand for Rust.AI tools are changing the landscape of software development and hiring.Hiring managers need to adapt their interview processes to account for AI usage.Open source contributions can significantly enhance a developer's profile.Tailoring CVs too specifically can raise red flags for recruiters.Remote work options can broaden the talent pool for Rust developers.Developers should not limit themselves to Rust when seeking jobs.Persistence and passion for Rust can lead to job opportunities.

Coding Chats episode 65 - Mike Rispoli discusses his experience of building a Loom replacement through vibe coding, the economic implications of AI for small agencies, and the evolving landscape of software engineering. He emphasizes the importance of hand coding, the challenges of interviewing in the age of AI, and the necessity of clear requirements when working with AI tools. The discussion also touches on the future demand for software engineers and the role of UX in AI-generated code.Chapters00:00 Building a Loom Replacement in 30 Minutes03:40 The Challenges of SaaS Pricing Models06:29 AI's Impact on Small Businesses and Enterprises09:19 Interviewing in the Age of AI11:59 The Future of Coding and AI Integration26:45 The Importance of Clear Requirements28:31 Navigating AI in Development31:31 Feature Creep and Planning32:30 The Evolving Role of Engineers34:34 Workflow and Planning with AI38:45 Iterative Development and Feedback42:28 Leveraging AI for UX and Design45:59 The Future of Software EngineeringMike's Links:https://www.linkedin.com/in/michael-rispoli-ctohttps://x.com/michael_rispolihttps://www.instagram.com/mike_rispoli_ctohttps://michaelrispoli.com/John's Links:John's LinkedIn: https://www.linkedin.com/in/johncrickett/John’s YouTube: https://www.youtube.com/@johncrickettJohn's Twitter: https://x.com/johncrickettJohn's Bluesky: https://bsky.app/profile/johncrickett.bsky.socialCheck 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.TakeawaysMike built a Loom replacement in just 30 minutes using vibe coding.AI tools can significantly enhance productivity for software engineers.The SaaS pricing model can be complicated for small agencies.It's acceptable to pass on good candidates but not to hire the wrong ones.AI is likely to amplify the demand for software engineers rather than replace them.Feature creep is a common challenge in software development.Clear requirements are essential when working with AI tools.The future of software engineering is promising and exciting.AI can help engineers improve their design capabilities.Navigating the evolving landscape of software engineering requires adaptability.

Coding Chats episode 64 - Jakob Sagatowski discusses his unique collaboration with YouTuber Mark Rober to build a robot goalie that plays against Cristiano Ronaldo. He delves into the technical challenges of motion control and computer vision, the role of software engineers in industrial automation, and the importance of real-time systems. Jakob emphasizes the need for better software development practices in the industrial automation sector and shares insights on how aspiring engineers can break into this field.Chapters00:00 Introduction to the YouTube Collaboration Project03:22 Challenges in Motion Control and Computer Vision06:29 Trial and Error in Robotics Development09:15 Understanding Industrial Automation12:05 Programming Languages in Industrial Automation14:31 The Role of Real-Time Systems17:49 Constraints in Real-Time Programming21:22 Understanding Hardware Constraints in Industrial Automation24:46 The Role of PLCs in Industrial Control Systems28:45 Challenges in Software Development Practices35:32 Breaking into Industrial Automation CareersJakob's Links:Website: www.sagatowski.comPLC-programming course: https://www.youtube.com/playlist?list=PLimaF0nZKYHz3I3kFP4myaAYjmYk1SowOUnit testing framework for Beckhoff PLC’s (the course talks about this), if you want to apply TDD in industrial automation:www.tcunit.orghttps://github.com/tcunitJohn's Links:John's LinkedIn: https://www.linkedin.com/in/johncrickett/John’s YouTube: https://www.youtube.com/@johncrickettJohn's Twitter: https://x.com/johncrickettJohn's Bluesky: https://bsky.app/profile/johncrickett.bsky.socialCheck 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.TakeawaysJakob collaborated with Mark Rober on a robot goalie project.The project involved significant motion control and computer vision challenges.Real-time systems require deterministic execution within strict time frames.Industrial automation is evolving, integrating more software engineering practices.Software engineers are increasingly needed in industrial automation roles.The development environment in industrial automation is often proprietary and closed.AI's impact on industrial automation is still developing, with challenges in integration.Real-time programming constraints differ significantly from web development.PLCs are essential for controlling industrial processes and machinery.Aspiring engineers can learn about industrial automation through online resources and experimentation.

Coding Chats episode 63 - John Crickett and Rob Bowley discuss the evolving role of the CTO, emphasizing the importance of strategic leadership that integrates people, process, and technology. They explore the challenges and opportunities presented by AI and other technological trends, highlighting the need for adaptability and effective communication within leadership teams. The discussion also touches on the significance of assessing technology teams and strategies to ensure successful outcomes in software development and organizational growth.Chapters00:00 Introduction to the CTO Role02:49 The Misconceptions of the CTO Position05:05 The Importance of Feedback and Adaptability11:50 Navigating AI and Emerging Technologies19:08 Testing Hypotheses in Technology Implementation22:19 The Transformative Potential of AI in Software Engineering27:09 The Economic Impact of Generative AI29:24 Concerns Over AI Subscription Costs31:32 Adoption Challenges in Software Development35:14 Assessing Technology and Team Effectiveness38:44 The Future of Software Engineering and AI50:12 Exploring Related ContentRob's Links:Blog: https://blog.robbowley.net/LinkedIn: https://www.linkedin.com/in/robertbowley/Bluesky: https://bsky.app/profile/robbowley.netCompany URL: https://www.pragmaticpartners.co.uk/John's Links:John's LinkedIn: https://www.linkedin.com/in/johncrickett/John’s YouTube: https://www.youtube.com/@johncrickettJohn's Twitter: https://x.com/johncrickettJohn's Bluesky: https://bsky.app/profile/johncrickett.bsky.socialCheck 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.TakeawaysThe role of a CTO is a strategic leadership position that intersects people, process, and technology.CTOs should focus on understanding their strengths and how to leverage them within their organization.Effective communication and collaboration with the senior leadership team are crucial for a CTO's success.Many misconceptions about the CTO role stem from a focus on technical skills rather than strategic business outcomes.Adaptability and awareness of one's strengths are key attributes of good leadership.Feedback from peers and team members is essential for recognizing gaps in skills and performance.Learning from failure is a critical aspect of leadership growth.The integration of AI into products should be approached with caution and thorough exploration.Organizations must focus on proven, common technologies rather than chasing every new trend.The assessment of technology teams should prioritize people and their capabilities over just the technology itself.