Meet Amy Posten 🇺🇸! Amy was a veterinary technician for fifteen years before she decided to switch careers. First, she discovered freeCodeCamp while on maternity leave. Later, she joined a premium bootcamp but didn't feel quite ready to apply for coding jobs afterward, so she turned to Scrimba to polish her skills. Nowadays, she's a front-end engineer and instructor.

In this episode, you'll learn how to figure out what kind of job you want and what was a small change in her job-hunting approach that brought Amy immediate results. You'll discover what are the gaps in knowledge one might have after a bootcamp, and how you can make learning to code less lonely. Finally, Amy and Alex discuss generative AI tools and how you can use them in your job hunt.

🔗 Connect with Amy

• 👩‍💼 Linkedin

⏰ Timestamps

• How Amy became a Veterinary Technician (01:32)
• Maternity leave on freeCodeCamp, and a career change brought up by the pandemic (04:38)
• Why Amy likes JavaScript, HTML, and CSS (06:59)
• Why Amy decided to join a bootcamp (08:56)
• The importance of getting to connect with people (11:16)
• Social media break with Jan the Producer (12:43)
• How to make learning to code less lonely (14:12)
• Joining a bootcamp is like drinking from a fire hose (16:27)
• Amy discovered Scrimba through her bootcamp! (18:31)
• After the bootcamp, Amy also joined the Scrimba bootcamp (19:37)
• Why Amy decided to start from scratch on Scrimba (21:35)
• How Amy found her north star and became a teacher (24:48)
• Amy changed her approach to job applications and got immediate results! (28:26)
• Amy's reach-out strategy and how she got a job interview at the company she currently works at (31:52)
• How to figure out what kind of job you want (35:11)
• Amy's job interview (36:04)
• How to use AI tools in your job hunt (40:22)

🧰 Resources Mentioned

• Scrimba podcast: The State of React (and Should You Still Learn It in 2024), with Dev Agrawal
• Scrimba podcast: An expert guide to technical interviews with Ian Douglas
• Scrimba podcast: This Is How You Onboard: Actionable Tips for Developers On a New Job from Ian Douglas
• Learn React for free!
• Scrimba Bootcamp
• Scrimba's Discord community

⭐️ Leave a Review

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You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in 🙏 Or tell Jan he's butchered your name here.

Meet Chris Webster 🇬🇧! Chris is a full-stack developer based in Reading. In a past life, he taught Mandarin to both children and adults and obtained a master's degree in education. If you're guessing that this episode is about pedagogy, maintaining your mindset, and learning hacks, you're on the right track.

When Chris decided to switch careers, he enrolled in a premium London boot camp. Was it worth the money? Or the time? In this episode, Chris lays out the differences between a boot camp and learning to code by yourself online. He ended up on Scrimba afterward—sometimes even while at work at his first coding job—which helped him land his dream job. But that wasn't the only thing! It's the perseverance, strategies for successful adult learning, and knowing what to look for in the myriad of teaching methods available to us that paved Chris's path to success. In this podcast, you'll learn all about them!

🔗 Connect with Chris

• 👨‍💼 Linkedin

⏰ Timestamps

• How Chris discovered computers (but became a teacher and only later took up coding) (01:09)
• Was changing careers an easy decision? (03:57)
• What do bootcamps promise, and do they deliver? (06:32)
• How did Chris structure his learning? (06:46)
• Was Chris happy with what he got out of the bootcamp? (08:36)
• Did the marketing of the bootcamp match the actual offering? (10:41)
• Midroll with Jan the Producer: Tweet about us! (12:31)
• The appeal of a bootcamp: the path + the community (13:27)
• How Chris discovered Scrimba (14:34)
• The problem with many teachers nowadays (17:40)
• Chris's Number One Learning Hack (19:20)
• Don't keep hammering the problem (23:18)
• The system for problem-solving (25:52)
• The stigma of (not) working hard enough (27:18)
• Pomodoro technique vs being in the zone: there's a right time for both (29:30)
• How Chris found his first job (31:34)
• What's it like working for a consultancy (32:38)
• How Chris landed his dream job as his second job (34:33)
• Chris's LinkedIn strategy (36:37)
• Just be enthusiastic! (37:49)
• Chris's message to a recruiter on LinkedIn (38:35)

🧰 Resources Mentioned

• Learn React for Free! 
• Book: Thinking, Fast and Slow by Daniel Kahneman
• Book: How to Solve It by George Polya

⭐️ Leave a Review

If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in 🙏 Or tell Jan he's butchered your name here.

Meet Dev Agrawal 🇮🇳🇺🇸! With a name like that, how could he not become a developer? He's a software developer, developer advocate, and content creator. Moreover, he's a React expert deeply ingrained in the React community. That's why we invited him onto the show to shed light on the current state of affairs!

You've probably noticed certain discontent surrounding React recently. A basic React app has become significantly more complex. It has been quite some time since there has been a significant update to React, with the recent ones relying heavily on meta-frameworks. And what about the React core team? What's happening there?

All of this might sound disheartening. However, we're delving into whether these concerns hold true in this episode. Let's find out together!

🔗 Connect with Dev

• 👨‍💼 Linkedin
• 🌐 Website
• 🐦 Twitter

⏰ Timestamps

• How Dev became a dev (01:34)
• Teamwork is a skill you can learn! (07:06)
• Should you go to college or learn to code by yourself? (09:10)
• Studying coding can be a "choose your own adventure" game (11:04)
• Community break with Jan the Producer (12:42)
• How Dev landed his first role in tech (14:28)
• Disappointment with React: what's that about? (15:42)
• What are meta-frameworks, and why are they gaining traction? (18:55)
• React was originally all about the front end... And now? (20:55)
• GraphQL and React Server components (22:23)
• Pete Hunt, Rethinking Best Practices, and separation of concerns (23:09)
• History is repeating itself (24:24)
• The most common problem with server components (25:34)
• The battle of the frameworks (26:10)
• Is Next.JS in an advantageous position? (28:08)
• Most people nowadays are using Vue! (34:13)
• Should you have FOMO about server components? (36:37)

🧰 Resources Mentioned

• Niche Down to Blow Up: Scrimba Student Leo Reveals How to Land an Awesome First Dev Job

Meet Parul Singh 🇬🇧! Parul is a Tech Careers & Neurodiversity Consultant, ADHD advocate, board member at Manchester Tech Festival, Public Speaker, and a former recruitment marketing partner and tech recruiter. If you're familiar with the topic of neurodiversity in tech, you've probably come across her name. In this episode, we're speaking with Parul because her advice on how to stand out and land a role in tech is anything but ordinary. 

This episode contains refreshingly unique and honest insights and perspectives on hiring in tech, along with some new job platforms you can use to inspire or recharge your developer job search. Everybody's on LinkedIn, and that can be a blessing and a curse! In this episode, you'll learn about the best alternatives. Standing out as a junior developer can be challenging, but we'll discuss some ideas on how you can do it. What should your CV look like? Do you need a cover letter? To wrap things up, we'll learn from Parul why some recruiters don't advertise the salary range and what you can do when you see a job ad like that!

Plus: Why should tech recruiters know how to code, and is JavaScript more similar to a ham or a hamster?

🔗 Connect with Parul

• 👨‍💼 Linkedin
• 🌐 Linktree
• 🐦 Twitter

⏰ Timestamps

• How Parul became a tech recruiter (01:19)
• Java vs. JavaScript (03:18)
• How Parul learned to code (03:34)
• Why it's important to find a coding instructor and method you vibe with (05:35)
• Why tech recruiters should know how to code (06:36)
• Community break with Jan the Producer (08:42)
• How can a developer be recognized by a recruiter (10:08)
• Job platforms other than LinkedIn (11:12)
• Make sure your profile is up to scratch (12:08)
• Who swipes right? (12:49)
• How to stand out as an entry-level candidate: your CV (15:01)
• Send your CV using normal methods, but THEN follow up directly (17:40)
• Do recruiters really only spend a few seconds on each resume? (18:38)
• Is sending a cover letter necessary? (20:21)
• Should you apply on the weekends? (22:10)
• What should you do if you're applying for a job that doesn't list the salary? (23:07)
• Why we need to be good negotiators (26:23)
• We need empathy (32:59)

🧰 Resources Mentioned

• https://hackajob.com/
• https://cord.co/
• https://www.haystackapp.io/
• https://otta.com/
• https://wellfound.com/
• https://hired.com/

⭐️ Leave a Review

If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in 🙏 Or tell Jan he's butchered your name here.

Meet Shawn Wang (Swyx) 🇺🇸! Swyx is a developer, writer, and startup advisor. If you listen to our show regularly, you know him as the biggest advocate for learning in public! Today, he's the founder of smol.ai and a podcast host and teacher at Latent Space. Last summer, Swyx wrote a blog post titled The Rise of the AI Engineer, which quickly went viral.

In this episode, Swyx will revisit that blog post to see if anything changed. You will learn why AI engineers are a thing, the differences between AI and ML engineers, and why the demand for this specialization is larger than the supply. Swyx also reveals what defines an industry (and why it's not only about tools) and gives many good examples of successful products made using existing foundation models. Swyx and Alex also talk about the inner workings of AI and whether it's a good idea to run AI models on your own hardware.

🔗 Connect with Swyx

• 👨‍💼 Linkedin
• 🌐 Website
• 🌐 smol.ai
• 🏫Latent Space

⏰ Timestamps

• Swyx wrote a blog post about The Rise of the AI Engineer, and it went viral (02:32)
• The three-stage progression of an AI engineer (04:33)
• Can an AI agent become a CTO? (05:36)
• We can become AI engineers now. What changed? (07:50)
• We didn't invent AI foundation models; we discovered them (11:27)
• Are we evolving new intelligence? (14:20)
• AI researchers vs AI engineers (15:36)
• Why is AI engineering a specialization? (17:04)
• What's an inference API (20:50)
• What are weights (21:09)
• There's a lot of interest in small AI foundation models (24:27)
• Should you use the cloud or run your AI models locally? (25:37)
• Is there a demand for AI engineers? (27:26)
• What AI products do companies want to build? (29:40)
• Updated career advice for new developers (34:51)

🧰 Resources Mentioned

• The Coding Career Handbook by Swyx (30% discount applied when you use this link)

Meet Adam Broda 🇺🇸! Adam is a tech lead and career coach who helps career changers break into tech. He did the same - after a decade of working in aerospace engineering at Boeing, Adam now works at Amazon! Through his coaching business, Broda Coaching, Adam aids career transitioners in constructing personalized job search strategies.

In this episode, Adam unveils the four pillars of his framework: identifying your passions, skills, desired environment, and needed compensation. Alex and Adam also delve into the current state of the job market: have we moved beyond significant tech layoffs, are return-to-office policies contributing to attrition, and what implications do these factors have for software development jobs? Adam will also tech you about different phases of networking—short-term networking, advocacy networking, and engagement networking—detailing how to navigate each of them and which one is most effective.

🔗 Connect with Adam

• 👨‍💼 Linkedin
• 🌐 Website

⏰ Timestamps

• How Adam transitioned into IT (and became a career coach) after a long career in the aerospace industry (01:30)
• Adam's engineering background vs. his new roles (05:19)
• The tech industry changes frequently (08:32)
• How Broda Coaching came about (10:32)
• Fail fast! (14:22)
• The state of the tech job market (and should we be worried about layoffs (15:32)
• Why is there fewer junior roles? (18:12)
• Returning to the office forces attrition (19:41)
• Does social media give you a good overview of what's happening in the job market? (20:59)
• Before the pandemic, junior roles had a lower experience requirement (23:19)
• Adam's job-hunting strategy (23:51)
• Start with your why (25:14)
• Passions, skills, environment, and compensation (27:13)
• Is niching down limiting your opportunities? (28:02)
• Adam's three-phase networking approach (32:17)
• Demonstrate potential! (36:07)
• Go where you're passionate (39:50)

🧰 Resources Mentioned

• Broda Coaching

⭐️ Leave a Review

If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in 🙏 Or tell Jan he's butchered your name here.

🎙 About the episode

Meet Cassie Lewis 🇺🇸! Cassie has a fine arts degree, which turned out to be too fancy for the real world. After working in different fields, from photography to retail, she got interested in coding - and it turned out to be just the right fit with how her mind works! Cassie is fueled by curiosity, creativity, and challenges. And learning to code alongside a day job was certainly a challenge.

Two years into her learning path, Cassie realized she had hit a wall. In an attempt to get unstuck, she joined the Scrimba bootcamp. She also challenged herself to read more non-fiction and embarked on a path toward effective living. In this episode, Cassie explains effective living and how it can make you a more effective coder, too! You'll hear how Cassie defeated burnout, how she approached learning, and how she - only nine months after joining the bootcamp - landed her first dev job. This is a story about setting goals, establishing systems, frictionless networking (even if you don't live in a tech hub), and keeping your plans realistic. But also: this is also a story of creativity and exploration!

🔗 Connect with Cassie

• 🧑‍💼 Linkedin
• 🌐 Website

⏰ Timestamps

• How Cassie went from a fine arts degree to retail to coding (01:24)
• How Cassie chose her careers and roles and basically created her last retail position (03:35)
• Cassie originally discovered coding through WordPress (05:11)
• Is coding similar to making art? (05:47)
• Learning to code was a gradual shift (06:53)
• Why you should maintain some balance while learning to code (08:39)
• How Cassie managed her self-confidence (10:03)
• Community break with Jan the Producer (10:59)
• Resources Cassie used to help with her mindset during her coding journey (13:39)
• What is effective living (15:39)
• What did Cassie do to put herself back on track when she slipped? (19:32)
• Cassie's systems (21:13)
• Identify the key pillars in your life (23:07)
• How Cassie landed her first developer job (26:50)
• You never know who can help you (28:07)
• How's Cassie's new job going after three months? (34:15)
• Getting paid to learn on the job (35:54)

🧰 Resources Mentioned

• Scrimba Bootcamp
• How Johnny Learned Angular and Typescript in Three Days
• Cooking Up a Career Change: Overcoming Burnout and Finding Your Why, with Scrimba Student Jimmy
• Essentialism
• Atomic Habits

⭐️ Leave a Review

If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in 🙏 Or tell Jan he's butchered your name here.

🎙 About the episode

Meet Bob Ziroll 🇺🇸! Bob is Scrimba's Head of Education and one of the Internet's favorite React teachers. His latest course is on AI, but don't worry, there's React... I mean, ReAct in AI as well!

In the previous three episodes, we defined an AI engineer and demystified their tools. We explored foundation models and discussed how to personalize them through retrieval augmented generation and fine-tuning. We also delved into various use cases for incorporating AI models into your projects and explored why ChatGPT has brought a fundamental shift in how we perceive AI.

Today, Bob will guide us through the realm of AI agents, representing the future of automation. An AI agent is capable of perceiving its environment. What does that mean, and how can one create an AI agent? Also, will they eventually take over the world?

Bob will also give us actionable advice on how to stay ahead of the curve in the fast-changing world of AI models, and discuss his vision for the future of AI.

Bob's AI agents and automation course is part of Scrimba's brand-new AI path. Let's dive in!

This is the final episode of our series on AI engineering, introducing Scrimba's AI Engineer Path. This path is your gateway to unlocking the full potential of AI for your projects.

🔗 Connect with Bob

• 👨🏼‍💼 Linkedin
• 🐦 Twitter

⏰ Timestamps

• Nowadays, Bob teaches both React and AI (01:34)
• AI is moving even faster than the front end (02:16)
• What's new in the world of AI and coding (02:46)
• ChatGPT vs. the GPT foundation model (04:15)
• What is an AI agent (05:45)
• The Terminator! (09:33)
• We didn't invent AI; we discovered it (10:29)
• Midroll! (11:56)
• Prominent examples of AI agents today (12:35)
• Will AI agents replace people (15:25)
• Why you shouldn't fear nor ignore AI (18:12)
• Any predictions about AI are temporary and short-lived (21:36)
• How can you build your own AI agent? (24:34)
• React... and REact (31:26)
• Advice on how to stay up-to-date without getting totally overwhelmed (35:58)

🧰 Resources Mentioned

• The AI Engineer Path
• AgentGPT

⭐️ Leave a Review

If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in 🙏 Or tell Jan he's butchered your name here.

🎙 About the episode

Meet Guil Hernandez 🇺🇸! He is a developer and educator with over 15 years of experience in tech. He's also a Scrimba teacher who is a part of the team bringing you the AI Engineer Path, and in this episode, he's helping us understand retrieval-augmented generation.

In the previous episode, Tom Chant helped us understand the world of AI models. Today, Guil will further teach us how these models work under the hood. AI models don't understand the world like we do. When we interact with them, they turn our inputs into mathematical representations known as embeddings. By creating our own embeddings, we can teach AI to do what we want it to.

Today, we're getting an introduction about making a model aware of your own data source so that that data can be considered for the AI output. For example, using the techniques you'll learn from Guil in this episode, you could connect a model to your customer support conversations so that the model knows what is necessary to answer unique questions about your (or your client's) business.

This is the third episode of our series on AI engineering, introducing Scrimba's AI Engineer Path. This path is your gateway to unlocking the full potential of AI for your projects.

🔗 Connect with Guil

• 🐦 Twitter
• 🌐  Website
• 👩‍🚀 Github

⏰ Timestamps

• Guil focuses on RAG and embeddings (01:42)
• RAG makes a foundation model aware of your data (03:14)
• Spotify has been using RAG since 2014 (05:56)
• How embedding works: embedding model + vector database + generative model (09:00)
• You're enhancing content retrieved from a database with a generative model (10:26)
• A foundation model can't just understand text (10:34)
• What's a vector database? (12:35)
• Can we make an AI chatbot for the Scrimba podcast? (15:05)
• You can chunk the files directly at OpenAI now! (16:49)
• OpenAI's Assistants API (17:33)
• AI is evolving quickly (19:07)
• Assistants API does RAG (19:55)
• What is fine-tuning? (20:39)
• Differences between RAG and fine-tuning (21:14)
• Community break with Jan the Producer (23:58)

🧰 Resources Mentioned

• The AI Engineer Path
• Learn Embeddings and Vector Databases
• Scrimba Podcast with Saron Yitbarek

⭐️ Leave a Review

If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in 🙏 Or tell Jan he's butchered your name here.

Meet Tom Chant 🇬🇧! Tom is a Scrimba instructor who is a part of our in-house team that brought you a brand new career path available on Scrimba.com - the AI engineer Path.

In this episode, we're diving into the world of AI foundation models: what are they, how do they work, and how can you use them to build front-end applications that you, until recently, couldn't even think of unless you were a big company with loads of resources.

AI is fundamentally changing the features and user experience of front-end applications. In this episode, you'll learn how to use different foundation models out there (so, not just OpenAI) for your own projects.

This is the second episode of our series on AI engineering, introducing Scrimba's AI Engineer Path. This path is your gateway to unlocking the full potential of AI for your projects.

🔗 Connect with Tom

• 👩‍💼 Linkedin
• 🐦 Twitter

⏰ Timestamps

• One year is a long time in AI (02:14)
• What are some of the recent applications of AI that have converted the skeptics? (04:06)
• Revenue-boosting usage of the new AI models (07:50)
• Is AI a revolutionary shift for developers? (13:03)
• What are foundation models (15:41)
• How do foundation models work? (18:12)
• Multi-modality of foundation models (20:04)
• What are the differences between different versions of GPT- 3.5, 4, 4 Turbo... (22:20)
• What's OpenAI Whisper? (25:49)
• HuggingFace and are alternatives to OpenAI (28:50)
• What to do if OpenAI goes down? (32:20)
• Why ChatGPT is slow... and running an AI model on your own hardware slower (35:35)
• What is fine-tuning? (38:01)
• What is RAG? (39:12)
• Using RAG can save you money (41:03)
• Scrimba's AI Engineer Path and Tom's course (43:46)
• Social Media Break with Jan the Producer (46:39)

🧰 Resources Mentioned

• The AI Engineer Path

⭐️ Leave a Review

If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in 🙏 Or tell Jan he's butchered your name here.