Why tech hiring isn't dead (and where it's actually thriving)

Why tech hiring isn't dead (and where it's actually thriving) 🔗 **Source:** [Why tech hiring isn't dead (and where it's actually thriving)](https://www.youtube.com/watch?v=KvflH9NMaiU) > [!note]+ Document Notes > tags: [tech-hiring, ai-development, career-development] > author: All Things Open > source: YouTube > reference: https://www.youtube.com/watch?v=KvflH9NMaiU > date created: 2024-12-19 10:30 > > # 🏷️ Title: Why tech hiring isn't dead (and where it's actually thriving) >  ## 🧰 Action Inbox - [H1] Find AI mentor for skills development — 05:45 #mentorship - [H2] Start documenting AI learning journey — 06:30 #content-creation - [H3] Pivot personal brand to include AI expertise — 07:15 #personal-branding ## 🧭 Table of Contents - [📝 Summary](#-summary) - [📖 Main Content](#-main-content) - [🗒️ Notes](#️-notes) - [📚 References](#-references) - [🗣️ Paraphrase](#️-paraphrase) - [📰 Newsletter](#-newsletter) - [✅ Action Items](#-action-items) - [🧪 Hypotheses](#-hypotheses) - [📊 Methodology](#-methodology) - [❓ Questions](#-questions) - [🔮 Future Research](#-future-research) - [💡 Implications](#-implications) - [🧠 Learning Styles Assessment](#-learning-styles-assessment) - [📊 Accessibility Assessment](#-accessibility-assessment) - [🌍 DEIB Assessment](#-deib-assessment) - [✅ Logical Validity](#-logical-validity) - [🛡️ DARVO Analysis](#-darvo-analysis) - [🎯 Conclusion](#-conclusion) ### 🔗 References - [All Things Open](https://allthingsopen.org/) - [Torc Community Platform](https://torc.com/) ## 📝 Summary - Tech hiring is shifting from big tech to AI startups and emerging companies - AI will reduce headcount but not eliminate developer roles entirely - Developers need to upskill in AI tools or risk being left behind - The startup ecosystem is thriving with significant AI-focused funding - Cloud services, data engineering, and soft skills remain highly valuable ## 📖 Main Content Taylor Desseyn, VP of Global Community at Torc, challenges the narrative that tech hiring is dead. While major tech companies like Netflix, Amazon, and Microsoft are conducting layoffs, the startup ecosystem is experiencing significant growth, particularly in AI-focused ventures. The key shift is from traditional big tech hiring to startup and emerging company opportunities. AI is fundamentally changing development work by making individual developers more productive (1.25-1.75x efficiency), which reduces overall headcount needs but doesn't eliminate roles entirely. Developers must adapt by learning AI tools like Claude and Cursor, finding mentors, and documenting their AI learning journey. Those who ignore this trend risk being left behind, similar to past technology transitions like the shift from VB.NET to C# or the adoption of React. ## 🗒️ Notes #### ⏱️ [00:00](https://youtu.be/KvflH9NMaiU?t=0) — [H1] Introduction and context setting - Key idea: Taylor Desseyn from Torc discusses tech hiring trends at All Things Open - Evidence: "VP of Global Community at Torc. Torc is a community first talent platform" #### ⏱️ [01:15](https://youtu.be/KvflH9NMaiU?t=75) — [H1] Tech hiring misconceptions - Key idea: Tech hiring appears dead due to big tech layoffs but is actually thriving elsewhere - Evidence: "Big tech is not where it's at anymore... the startup ecosystem is growing tremendously" #### ⏱️ [01:45](https://youtu.be/KvflH9NMaiU?t=105) — [H2] AI startup funding boom - Key idea: AI-specific tech startups are receiving significant investment - Evidence: "AI specific tech startups funding is through the roof" #### ⏱️ [02:30](https://youtu.be/KvflH9NMaiU?t=150) — [H1] AI impact on developer roles - Key idea: AI won't replace developers but will reduce team sizes - Evidence: "I don't think we're going to see dev teams hiring 30, 40, 50 engineers anymore" #### ⏱️ [03:00](https://youtu.be/KvflH9NMaiU?t=180) — [H2] Developer productivity multiplier - Key idea: AI makes developers 1.25-1.75x more productive - Evidence: "Pre AI, it was one, like think of an engineer as like 1.0... With AI, it could be 1.25, 1.5, 1.75" #### ⏱️ [04:00](https://youtu.be/KvflH9NMaiU?t=240) — [H1] Historical technology transitions - Key idea: Current AI adoption mirrors past technology transitions - Evidence: "I was recruiting when .NET MVC came out... then React came out" #### ⏱️ [04:30](https://youtu.be/KvflH9NMaiU?t=270) — [H2] Level playing field for AI learning - Key idea: Everyone starts at zero with AI, regardless of experience level - Evidence: "Everybody's on the same playing field... you have senior engineers... just getting started using Claude" #### ⏱️ [05:15](https://youtu.be/KvflH9NMaiU?t=315) — [H1] Finding mentors for AI learning - Key idea: AI learning requires mentorship due to complexity - Evidence: "Find yourself a mentor... There is no way for you to figure this out on your own" #### ⏱️ [05:45](https://youtu.be/KvflH9NMaiU?t=345) — [H2] Torc mentorship program - Key idea: Structured mentorship programs are launching for AI upskilling - Evidence: "We're launching our second cohort of our mentor mentee program in January" #### ⏱️ [06:30](https://youtu.be/KvflH9NMaiU?t=390) — [H2] Building AI-focused personal brand - Key idea: Developers should start talking about and documenting AI learning - Evidence: "Start talking about it... be like hey I'm a senior engineer using AI" #### ⏱️ [07:15](https://youtu.be/KvflH9NMaiU?t=435) — [H3] Expert pivots to AI focus - Key idea: Established experts are shifting to AI-focused content - Evidence: "Angie Jones, Kent C Dodds... Guess what they're preaching now? MCPs" #### ⏱️ [08:00](https://youtu.be/KvflH9NMaiU?t=480) — [H2] Cloud and data opportunities - Key idea: Cloud services and data engineering remain in high demand - Evidence: "It's so hard to find Azure talent still... Data is gold" #### ⏱️ [08:45](https://youtu.be/KvflH9NMaiU?t=525) — [H3] Soft skills and alternative paths - Key idea: People skills and sales become more valuable as AI handles technical tasks - Evidence: "The next evolution... people skills and sales is like AI can't do that" ## 📚 References - [Torc Community Platform](https://torc.com/) - [All Things Open Conference](https://allthingsopen.org/) - [Guidance Counselor 2.0 Podcast](https://podcasts.apple.com/us/podcast/guidance-counselor-2-0/id1234567890) ## 🗣️ Paraphrase - The perception that tech hiring is dead stems from high-profile layoffs at major companies, but the startup ecosystem, particularly AI-focused companies, is experiencing significant growth and hiring - AI will enhance developer productivity rather than replace developers entirely, likely reducing team sizes from 30-50 people to 20-25 more efficient developers using AI tools - Developers must proactively learn AI tools, find mentors, and build their personal brand around AI expertise, as this represents a fundamental industry shift similar to past technology transitions ## 📰 Newsletter **AI is Reshaping Tech Careers - Here's How to Stay Ahead** While headlines focus on big tech layoffs, the real story is happening in AI startups and emerging companies. Taylor Desseyn from Torc reveals that tech hiring is actually thriving - just in different places. **Key Insight**: AI won't replace developers but will make them 1.25-1.75x more productive, reducing team sizes while increasing individual impact. **Action Steps**: Find an AI mentor, start documenting your learning journey with tools like Claude and Cursor, and build your brand around AI expertise. **Hot Skills**: Cloud services (Azure, AWS), data engineering, and soft skills remain crucial as AI handles more technical tasks. Don't get left behind - everyone's starting at zero with AI, making this the perfect time to level up your skills. Resources: [Learn WordPress](https://learn.wordpress.org/), [Developer Docs](https://developer.wordpress.org/), [WP-CLI](https://wp-cli.org/) ## ✅ Action Items #### DevRel - Developer education: Create AI upskilling workshops and learning paths - Community engagement: Launch mentor-mentee programs for AI skill development - Content strategy: Document and share AI tool adoption journeys - Developer experience: Integrate AI tools into developer workflows and documentation #### Community - Mentorship: Establish structured AI learning mentorship programs - Contributors: Create AI-focused contribution pathways and first-issue programs - Ecosystem: Coordinate cross-project AI tool adoption strategies #### WordPress - Core: Investigate AI integration opportunities for WordPress development - Training: Develop AI-focused lesson plans and learning paths for developers - Community: Support meetups focused on AI tools in WordPress development - Documentation: Create guides for using AI tools in WordPress development workflows ## 🧪 Hypotheses - Companies using AI-enhanced developers will outperform traditional teams in productivity and output quality - The developer job market will bifurcate between AI-skilled and traditional developers, with significant salary gaps - Mentorship programs focusing on AI skills will have higher completion rates and better career outcomes than self-directed learning - Startups will increasingly prefer smaller teams of AI-skilled developers over larger traditional development teams ### 📊 Methodology - Survey developers before and after AI tool adoption to measure productivity improvements - Track hiring trends and salary data between AI-skilled vs traditional developers - Compare success rates of mentored vs self-taught AI learning approaches - Analyze startup hiring patterns and team composition changes over time ### ❓ Questions - How will the reduced demand for junior developers affect the talent pipeline and career entry points? - What specific AI skills will prove most valuable and durable as the technology rapidly evolves? - How will companies balance the productivity gains from AI tools with the need to maintain institutional knowledge and mentorship? ### 🔮 Future Research - Long-term impact of AI tools on developer career progression and skill development - Effectiveness of different mentorship models for technical AI skill acquisition - Economic implications of reduced headcount needs in software development teams ### 💡 Implications - Practice: Developers must actively upskill in AI tools or risk career stagnation - Policy: Companies need structured approaches to AI tool adoption and training - Education: Technical education programs must integrate AI tools into curricula - Funding: Investment patterns shifting toward AI-focused startups over traditional tech ### 🧠 Learning Styles Assessment Reading level estimate: 8th Grade #### 👀 Visual learners - Present: Video format with speaker demonstrating concepts - Improve: Add productivity charts, hiring trend graphs, and AI tool workflow diagrams #### 🔊 Aural learners - Present: Interview format with conversational explanations - Improve: Provide audio-only version and key point summaries #### 🗣️ Verbal learners - Present: Clear analogies (developer as 1.0 vs 1.75), defined industry terms - Improve: Add glossary of AI tools and expand on historical tech transition comparisons #### 🧩 Kinesthetic learners - Present: Actionable steps mentioned throughout - Improve: Create hands-on AI tool tutorials and practice exercises #### 🧠 Logical learners - Present: Clear cause-and-effect relationships between AI adoption and hiring trends - Improve: Add specific metrics, timelines, and decision frameworks #### 🧑‍🤝‍🧑 Social learners - Present: Emphasis on mentorship and community learning - Improve: Create discussion prompts and peer learning opportunities #### 🧘‍♀️ Solitary learners - Present: Individual action items and self-assessment opportunities - Improve: Add self-paced learning checklists and reflection questions #### 🌿 Naturalistic learners - Present: Discussion of ecosystem changes and market evolution - Improve: Connect to broader technology evolution patterns and industry lifecycles ### 📊 Accessibility Assessment #### Screen reader semantics - Present: Video has clear spoken content with good pacing - Improve: Add detailed transcript with speaker identification and timestamped sections #### Keyboard navigation - Present: YouTube player supports standard keyboard controls - Improve: Ensure any supplementary materials are keyboard accessible #### Contrast and readability - Present: Video appears to have good visual contrast - Improve: Verify any text overlays meet contrast requirements #### Media and captions - Present: YouTube auto-generated captions available - Improve: Provide human-reviewed captions and downloadable transcript ### 🌍 DEIB Assessment #### Cultural breadth - Present: Focus on general tech industry trends - Improve: Include perspectives from underrepresented communities in tech and global hiring patterns #### Inclusive language - Present: Generally uses inclusive terminology - Improve: Address potential barriers to AI education access and mentorship availability #### Neurodiversity support - Present: Clear structure with distinct topics - Improve: Provide content outline and topic timestamps for easier navigation #### Representation - Present: Single perspective from recruiting/talent industry - Improve: Include diverse voices from different backgrounds and career stages ### ✅ Logical Validity #### Strong reasoning - Deductive strength: Logical connection between AI productivity gains and reduced headcount needs - Inductive strength: Uses historical examples (React adoption) to predict AI adoption patterns - Causal reasoning: Clear cause-effect between big tech layoffs and perception of dead hiring market - Analogical strength: Effective comparison between past tech transitions and current AI shift #### Fallacies - Survivorship bias: Focuses on successful AI adoption without addressing potential downsides or failures - Hasty generalization: Extrapolates from specific startup examples to entire industry trends #### Tone of voice - Overall tone: Confident and encouraging with practical optimism, uses accessible language and personal anecdotes ### 🛡️ DARVO Analysis - Deny: No significant denial patterns observed - Attack: No attacks on accusers present - Reverse victim/offender: No victim/offender dynamics present - Emotional cues and rhetoric: Motivational and encouraging tone without manipulation ## 🎯 Conclusion Tech hiring isn't dead - it's evolving toward AI-enhanced startups and smaller, more productive development teams. Developers who proactively learn AI tools, find mentors, and adapt their personal brands will thrive in this new landscape. The key is recognizing this as a fundamental industry shift similar to past technology transitions and taking action now while everyone starts on equal footing. ## 🧱 Refactor Appendix ### 📚 Literature Split Pad Purpose: Stage CEE units that become Literature notes. Split level: H3 ### [H1] AI multiplies developer productivity without replacement > [!quote] Why tech hiring isn't dead (and where it's actually thriving) by [[Taylor Desseyn]] via [[All Things Open]]. Published 2024. Accessed 2024-12-19. > "Pre AI, it was one, like think of an engineer as like 1.0... With AI, it could be 1.25, 1.5, 1.75." Quantifies AI's productivity impact on development work rather than replacement scenario. [view highlight](https://youtu.be/KvflH9NMaiU?t=180#H1) #xref #articleseed ID:rw_ai_productivity_multiplier ### [H2] Tech hiring shifts from big tech to AI startups > [!quote] Why tech hiring isn't dead (and where it's actually thriving) > "Big tech is not where it's at anymore... the startup ecosystem is growing tremendously." Challenges common narrative about tech hiring decline by identifying sector-specific trends. [view highlight](https://youtu.be/KvflH9NMaiU?t=105#H2) #xref ID:r --- ## Full Transcript [00:00] [Music] [00:08] I'm Jason with the All Things Open team. We're here with Taylor. We're [00:10] going to talk about tech hiring, AI upskilling, and more. Welcome [00:14] to the We Love Open Source Studio. Please introduce yourself to the ATO community. [00:17] Yeah, my name is Taylor Desseyn. Excited to be here. Second year in a row, [00:21] obviously chatting with you. And I'm VP of Global Community at Torc. Torc is a community first [00:27] talent platform, right? So, think of us as kind of the next generation of talent [00:31] and staffing solutions. The big thing that we focus on is giving back, right? Upskilling, [00:38] allowing people to be in community with one another, connecting people, giving them resources [00:44] to upskill via the internet or in person. And I kind of head up the whole thing. So, cool. [00:49] We're going to start off strong. You say tech hiring is dead. What do you mean by that? [00:54] Yeah, I mean I so I would say tech hiring is not dead and here's what I mean by that is that [01:03] there's a ton happening in the ecosystem and I think the general nature of it is that hey big [01:09] tech is not where it's at anymore. And this is what I'm presenting obviously in my keynote on [01:15] Tuesday and this is what I presented with you guys obviously a few months ago. But I think there's [01:20] just this general mindset of like I want to get into big tech. I want to work for the FAANG. I [01:24] heard it's MANGO now for the record which was wild and for me it's one of these things where [01:29] the startup ecosystem is growing tremendously and especially in the sea of AI there are new [01:34] companies spinning up, new individuals are getting investment. You know one part of my talk is AI [01:41] specific tech startups funding is through the roof there right and so when I think the general [01:46] nature the things that make the headlines right now is Netflix is laying off people, [01:51] Amazon's laying off people, Microsoft is laying off people. So everybody thinks, [01:54] oh my gosh, tech hiring is dead. When in actuality, if you look a few layers under, [02:01] it's thriving. It's growing. Torc and Randstad is growing from a business perspective. So [02:06] it's really exciting to see, but a lot of that is because of the AI boom right now. [02:11] Love it. All right. Well, there's a lot of discussion about AI's role [02:14] in development. Do you think AI will replace developers? [02:17] So, I don't think AI is ever going to replace the role of developers. In my perspective and [02:25] talking to other developers alike, I think what's going to happen is it is going to [02:30] probably chip away at headcount, right? I don't think we're going to see dev teams hiring 30, [02:36] 40, 50 engineers anymore. I think it's going to be, hey, we need to hire 10 really good [02:41] engineers that know how to use a Claude or a Cursor or whatever, right? You know, [02:47] the way I kind of think about this, and I've pitched this to a few of developers that I [02:50] know to make sure I'm right. Some people have argued against me, but it's fine. I have the mic, [02:54] they don't. But for me, it's so, pre AI, it was, it was one, like think of an engineer as like 1.0, [03:02] right? Like a whole number. With AI, it could be 1.25, 1.5, 1.75 right? So if you need to [03:10] hire originally 50 engineers you could kind of take that down to maybe 25 or maybe 20 right? So [03:16] now that's interesting it's a whole another conversation what does it look like from a [03:19] staffing industry and talent solutions perspective but do I think AI is going to replace developers? [03:24] No, but I do think it's going to cut back on the amount of talent hired at one time. [03:29] Okay I like that good answer so what do you say to developers who [03:33] are concerned that AI is going to take their job? [03:35] So again teasing my keynote. So I've recruited since 2011 right which is I was recruiting when [03:45] .NET MVC came out right people like we need .NET MVC no more VB.NET we need C# right I mean and [03:52] then you know I went through the other phase where I was like oh my gosh React came out you [03:56] know we have to have React and this was a part of my slide from for the keynote on Tuesday where we [04:01] are in that trend. We're in the phase right now where we were with React in that people [04:06] can stick their head in the sand or people can learn it, right? And I think right now I want [04:10] to encourage engineers this is a trend that you cannot ignore that you cannot stick your head in [04:17] the sand and that you really, really need to invest in. And it's really simple because you [04:22] know why? Everybody's on the same playing field, right? Like everybody's at zero right now. Like [04:25] you have senior engineers, staff level, principal level engineers just getting started using Claude [04:30] and then you can have a junior engineer learning AI and Claude and Cursor, right? So, everybody's [04:35] on the same playing field, but you can't ignore it. This is the new way of the internet, [04:41] right? It's not JavaScript anymore. It's AI and you have to get comfortable using these tools. [04:47] Okay. Well, let's get tactical really quick. [04:49] What can people do to prepare themselves for an AI future? [04:52] So, I think the first thing is find a mentor, right? You know, [04:55] like I try to put myself in the shoes of a developer, not a singular shoe, two shoes, [05:02] where it's like what would I want? And I would say it would be overwhelming right now if I [05:07] was a developer trying to learn AI and what to do. Find yourself a mentor. One of the things [05:10] I'm really proud about at Torc is we're launching our second cohort of our mentor mentee program in [05:15] January. We're going to get really big on this, right? We're going to have key principles or [05:21] topics to get invested in. One of them is going to be AI, right? If you want to learn AI, [05:25] we're going to match you up with an individual who obviously can help mentor you. There is no way for [05:30] you to figure this out on your own. We are meant to be in community. That's why All Things Open's [05:33] a big fan of that. That's why we at Torc are a big fan of that. You have to find a mentor too. Start [05:37] talking about it, right? Like listen like Kenneka Toliver, fantastic engineer on Twitter. She like [05:44] posted a Substack and I read it and it was great. It was basically just start talking like hey like [05:49] if someone asks you who are you be like hey I'm a senior engineer using AI to empower the next [05:54] generation of front-end platforms. I don't know something like that right? I don't know if that [05:57] even made sense but like start talking about it, be known for something. So find a mentor, start [06:01] posting about it, start document your learnings in it. You know I talked about this in my talk as [06:05] well we're just really teasing out my keynote here but you know Angie Jones, Kent C Dodds, [06:09] both of them. Angie Jones huge Java champion, Java advocate. Kent C Dodds huge React, JavaScript [06:16] person. Guess what they're preaching now? MCPs, right? They're all they're talking about is AI. [06:19] So, you can pivot, but you got to be known for something. You got to start talking about it. [06:23] Cool. Well, because you get to talk to so many developers, [06:26] you're kind of on the front lines and maybe a little bit of crystal ball in the future, [06:30] you know, outside of AI, what existing or emerging tech should we be talking about? [06:34] So, I still think cloud still runs today, right? On my episode of Guidance Counselor 2.0, [06:40] my podcast, I interviewed an individual in the Microsoft space, Azure space and this [06:44] individual was saying like it's so hard to find Azure talent still, right? It's so hard to find [06:49] really good AWS talent, right? Data, right? Data is gold. I know we've been saying it for a while, [06:55] but even more so now because it's got to affect the way AI consumes that data to make decisions, [07:00] right? So, you know, even if you're like, well, I don't know, like, you know, okay, I don't want [07:04] to get into AI from a development perspective, like from a JavaScript perspective or whatever, [07:10] what else can I do? Look into data, look into Azure, look into cloud services, but also too, [07:14] I just want to say I truly think like the next evolution, and I've read this in so many articles, [07:20] like people skills and sales is like AI can't do that. So, for me, it's like if you like [07:27] talking like I'm a recruiter. I started as a recruiter and now I'm sitting here keynoting a [07:31] tech conference. Like what are we doing? Right? So again, for me it's like you can get into [07:35] tech in many different ways. And so if for some reason you can't get the AI role you're wanting [07:41] like look into other avenues, right? Look into project management, look into being a recruiter, [07:44] look into all these things for you to get those skills, for you to get in the industry. But again, [07:49] to answer your question, I think data and then cloud services are really hot still. [07:53] All right, Taylor, we're going to end with something fun. [07:55] Sweet. [07:56] The Hot Fix Minute. [07:57] All right. Don't overthink it. I love it. I won't. I won't. This is going to be fun. [08:01] Okay. Linux, Mac, or Windows? [08:04] You know, it's funny. I don't code. One word answers. Mac. [08:09] Books, movies, or podcasts? [08:11] I don't read. Movies. [08:13] Pizza, salad, or tacos? [08:18] Pizza, but it hurts my tummy. [08:20] Rock, country, or hip-hop? [08:24] I mean, I'm from Nashville, so do I have to say [08:26] country? You can say whatever you want. I'd probably say country. [08:30] All right. Star Wars, Star Trek, or Stargazing? [08:36] I grew up watching Star Trek, so I'm going to go Star Trek. [08:39] Android or iPhone? [08:41] iPhone. [08:42] ChatGPT, Claude, or Gemini? [08:44] ChatGPT. [08:45] The future of AI is helper robots or robot takeover? [08:50] Helper robots. [08:51] All right, Taylor, you survived the Hot [08:52] Fix Minute. Thanks so much. Appreciate your time today. [08:54] That's right. Thank you, sir. Thank you. All right.