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Tech Careers Redefined by AI

Key Points

  • The tech job market has long assumed that knowledge is scarce and hard to acquire, but today knowledge is easily accessible, prompting a need to rethink how we structure careers and talent development.
  • Historically, the industry split roles into “technical” (requiring a CS degree and deep engineering knowledge) and “non‑technical” (focused on contextual product, sales, marketing, and stakeholder expertise).
  • For decades a computer‑science degree virtually guaranteed a software engineering job, while non‑technical roles relied on domain‑specific contextual knowledge rather than formal technical training.
  • Beginning around 2015‑2020—well before the rise of ChatGPT—this strict bifurcation started to erode, signaling an imminent shift in how tech talent is sourced, trained, and valued.

Full Transcript

# Tech Careers Redefined by AI **Source:** [https://www.youtube.com/watch?v=f4_u8wKMjAo](https://www.youtube.com/watch?v=f4_u8wKMjAo) **Duration:** 00:10:49 ## Summary - The tech job market has long assumed that knowledge is scarce and hard to acquire, but today knowledge is easily accessible, prompting a need to rethink how we structure careers and talent development. - Historically, the industry split roles into “technical” (requiring a CS degree and deep engineering knowledge) and “non‑technical” (focused on contextual product, sales, marketing, and stakeholder expertise). - For decades a computer‑science degree virtually guaranteed a software engineering job, while non‑technical roles relied on domain‑specific contextual knowledge rather than formal technical training. - Beginning around 2015‑2020—well before the rise of ChatGPT—this strict bifurcation started to erode, signaling an imminent shift in how tech talent is sourced, trained, and valued. ## Sections - [00:00:00](https://www.youtube.com/watch?v=f4_u8wKMjAo&t=0s) **Untitled Section** - ## Full Transcript
0:00you know the core of our job market 0:03problem right now in Tech is that we 0:06have predicated all of Tech for 40 or 50 0:09years on the idea that knowledge is 0:12something that is hard to gain and it's 0:14not anymore knowledge is easy to gain 0:18and I want to take a minute to step back 0:20to look at how we've architected our 0:22entire job career ladder job structure 0:25our whole Focus as an industry on how we 0:27develop talent look at how we've done it 0:29before 0:30and then look at what needs to shift so 0:32this is a strategic conversation about 0:34why tech jobs are hard right now and 0:37what we can do to prepare for a world 0:41where it's going to fundamentally 0:43shift so let's look first at what the 0:47previous date was before Chad GPT hit 0:49the 0:50scene for a long time as long as I've 0:53had my career just about for anyone else 0:55who's a graveyard in Tech we've had a 0:57fundamental bifurcation Tech there's two 1:00categories there's technical roles and 1:02there's non-technical roles those are 1:05predicated on knowledge gain and the 1:06difficulty of knowledge gain and 1:08Technical roles for years and years and 1:10years and years being a software 1:12development engineer virtually required 1:14a computer science degree certainly did 1:16when I was coming through college in the 1:18early 1:192000s and if you are getting a CS degree 1:26you are going to be guaranteed a 1:28software development engineering job 1:30that was the implicit promise that was 1:32the promise when I was in college it was 1:33the promise for decades afterward and 1:35decades before like even back in the 90s 1:38and the in the 80s if you got a CS 1:42degree you were headed to a technical 1:44role of some 1:45kind because it was all hand done like 1:49the knowledge had to be acquired by hand 1:51you had to read Hamming you had to read 1:54textbooks you had to actually write code 1:57by hand you had to learn how functions 2:01worked you had to learn how to code a 2:04program that was reliable you had to 2:06learn how to design Technical Systems 2:08all of that stuff right you get the idea 2:12non-technical roles were different the 2:15expectation was that the knowledge that 2:18mattered was contextual knowledge about 2:20the product about stakeholder management 2:23about the customer and so you can group 2:25product management customer success 2:27roles sales roles marketing roles they 2:31all fall into this non-tech bucket and 2:33essentially everybody was specializing 2:35in pieces of the non-tech value chain 2:38and what they were specializing on was 2:40contextual knowledge of that corner of 2:43the domain right like the marketers knew 2:45what kind of marketing worked for a 2:48particular product in a b Toc Market 2:50aimed at a particular 2:52demographic and the sales guys knew what 2:55particular sales approaches worked for 2:59B2 to be account 3:01selling and the product people knew how 3:05to connect engineering requirements 3:08which are quite specific with customer 3:10requirements which are quite 3:12vague and so all of that to say for a 3:16long time we had this split the split 3:19began to break down in the 2015 to 2020 3:24range and this is before Chad GPT so I 3:26want to actually call us back to this we 3:29started to have this idea of a technical 3:31product manager and a non-technical 3:33product manager and that was an early 3:35sign that this knowledge was starting to 3:37get blurry because PMS had been around 3:40Engineers so long that we had PMS in the 3:43job family who could code we had PMS in 3:45the job family who had acquired the 3:47technical knowledge needed to build 3:49extremely Technical Systems and we 3:51needed them to because the systems we 3:53were building at that point were built 3:56by hand there wasn't really an AI that 3:57was helping us build them but they were 3:59extremely Technical and extremely 4:01complex if you were driving 4:02personalization at Netflix it's a very 4:05technical role and you had to be a 4:07technical pm to do it successfully and 4:09so as our Technical Systems got more 4:11complex in the 2010s we had to have more 4:15technical product managers to make that 4:18work fast forward to when chat GPT was 4:21released and everything 4:22changed at that point the fundamental 4:26basis for that entire system of 4:28employment shifted 4:30we were now in a world we are now in a 4:33world where knowledge is a commodity 4:36knowledge used to be precious knowledge 4:38used to be something you went to college 4:39to gain and you paid like an absurd 4:41amount of money and it it has gotten 4:43more and more expensive and at this 4:45point one of the interesting things is 4:46even though College costs are going 4:48exponential the implied value of the 4:50knowledge you gain at a school has just 4:53fallen through the 4:54floor and no one really knows what to do 4:56with that dislocation this video is not 4:58about college cost unit economics we're 5:00g to put that to the side uh this is 5:03about talent in Tech and when knowledge 5:06gets commoditized what it means is the 5:08fundamental dichotomy between Tech and 5:11non-tech roles 5:13disappears like I will have people tell 5:15me Nate I'm not a technical person and I 5:19will say I don't care because you can 5:23have your best friend chat GPT make you 5:24a technical person in 30 seconds like 5:27there is almost no point now for example 5:30in saying we want a technical PM who can 5:33write SQL in Python because every PM can 5:35write SQL in Python now can they write 5:38it efficiently increasingly yes because 5:41the with proper prompting you can get 5:44efficient SQL and efficient python out 5:47of any llm it's not even a specific llm 5:51anymore chpt can do it Sonic can do it 5:53like it's just become commoditized and 5:56that's kind of my point you have a 5:57breakdown of Technical and non-technical 5:59skill skill sets and that means that the 6:02job creation ladder and the way we do 6:04Talent upleveling over time has changed 6:06because all of that was predicated on 6:08knowledge gain so if you think about the 6:10old way you would go to college you 6:11would get your degree maybe it was CS 6:13maybe it was something else and then you 6:15get an entry level role and the point of 6:16the entry-level role was to take all of 6:18this knowledge you had and basically 6:19show you how to apply it in the real 6:21world how do you write real life 6:22programs if you're an engineer how do 6:24you do real life program management or 6:26task management or CS if you are coming 6:28into an entry LEL role on the non-tech 6:30side and the idea was by gaining this 6:34knowledge of real world 6:37applications you would then be able to 6:39acquire enough experience and show you 6:41could solve problems in the real world 6:42enough to eventually earn a 6:44promotion and the problem now is that 6:49you don't really have any incentive to 6:53have those early rungs on the ladder in 6:56the organization chat GPT can do a lot 6:59of 7:00and so one of the things I've seen 7:01persistently is what happens to people 7:04who are early career what happens to 7:05people trying to break into Tech what 7:07happens to people who are just coming 7:09out of University how do they 7:12progress and I think that the key is 7:14understanding that we are no longer in 7:16an economy where knowledge is difficult 7:18to get and we're now in a world where 7:22showing that you can solve problems 7:24correctly is the new 7:27standard and we're still figuring out 7:29what that looks like as far as how 7:30resumés will change how applications 7:32will change it's early but fundamentally 7:35as an employer what people are looking 7:37for at the beginning of a career is show 7:39me that you can solve problems correctly 7:42in roughly this domain and show me that 7:44you've been able to deliver a little bit 7:45of impact there it's still a world where 7:49we recognize that you need more 7:50experience to deliver more impact but if 7:53you can come in and you can say I am 7:55already working in the B2B marketing 7:58space and this is what I already 7:59delivered on my own on the side here's a 8:02working piece of code that I put 8:04together with chat GPT and I got it up 8:06and running and look what I've solve for 8:07some marketers I'm making all of this up 8:10by the way but you get the idea it's not 8:13that everything has to be code 8:14generation and code portfolios I'm not 8:15trying to say that I'm trying to say 8:17that the focus from an employer is going 8:20to be on whether they can see that you 8:23can correctly solve problems because 8:26they know you can get the knowledge 8:27either way and so it's about your 8:28judgment 8:30it's not about the knowledge that you 8:32have and have brought to the 8:33table our application systems haven't 8:36caught up with that but I think that 8:39that also is a note of encouragement for 8:42us because I don't see a world where we 8:44don't need people with good judgment to 8:47solve problems I do see a world where 8:50people who assume that knowledge is 8:52still the coin of the realm right the 8:54currency we work in they're going to be 8:57in trouble because knowledge isn't hard 8:59anymore knowledge is easy it's about how 9:02you apply it that 9:03matters and so if you walk back into the 9:06job market like previously it was like 9:08okay so you have your Tech or non-tech 9:10degree you get an entry-level role you 9:13gain experience you get a mid-level role 9:15then if you show management aptitude you 9:17get a leadership role it's a very set 9:19pattern across a bunch of different job 9:22families now I suspect it's going to 9:25look different I think it's going to be 9:27show you can solve problems at the task 9:29level show you can solve problems 9:30correctly at the feature level so show 9:32you can solve problems correctly at the 9:34product level and finally show you can 9:36solve problems correctly at the business 9:38level that's going to be what people 9:40judge 9:41on and I think that one of the core 9:44questions if you're coming into Tech is 9:46how are you showing you can solve 9:48problems at what level are you operating 9:51at and how aggressive are you about 9:54scaling up and making sure that 9:55knowledge isn't a blocker because it 9:57doesn't have to be anymore you don't 9:59have to be blocked I saw a role just 10:02yesterday that was deliberately hiring 10:04for someone who would literally be a 10:07business in a box like this person would 10:09be product this person would be 10:10development this person would be 10:11marketing this person would be sales and 10:13they were operating within a larger 10:14platform they're not a Founder but they 10:18were taking this product end to end from 10:21idea to driving sales by 10:25themselves I think we're going to see 10:26more roles like that and so my my 10:29question for you is what kind of 10:32problems can you demonstrate that you've 10:35solved I'll leave it there let me know 10:38what do you think how's the how is the 10:39knowledge economy changing into 10:43the problem solving economy for lack of 10:46a better term cheers