Action Absorbs Anxiety  ## Metadata - Author: [[Changelog Master Feed]] - Full Title: Action Absorbs Anxiety - Category: #podcasts - URL: https://share.snipd.com/episode/297045e6-4b52-4b58-9b37-5b218c1837a5 ## Document Notes ## Highlights - **Running Developer Programs At Intel** - Arun describes running Intel's developer, DevRel, OSPO and events teams and the scale of work they did. - He recounts building developer outreach, hackathons, and maintainership roles across major projects like PyTorch and Kubernetes. Transcript: Jerod Santo Here with our old friend Arun Gupta, a free man. You're a free man now, Arun. Arun Gupta Well, yeah, indeed it is. I like to call myself as a free agent now. This is the first time, gosh, in almost 30 years I've ever been a free agent. And it's weird because over the last five, six job changes, I've never had to prepare a resume. I never applied for a job. The last time I applied for a job was sun.com/jobs back in 98, actually. Wow. And after that, I've always been, hey, come work for me. Can I do this fun thing and we'll craft a job for you kind of thing. And as part of, as I say, corporate restructuring, the entire team that was to do with developers was let go. And here you go, you know, involuntary free agent. But as rightly said, you know, there is definitely a bit of freeness to this entire thing. But I'm enjoying it so far. Adam Stacoviak The company's Intel, right? That's the free agent company you're from. So there's some obvious things in the news about Intel for the last while. Are you going to spill some beans? Can you share some stuff? How close can we come to the sun on this conversation? Arun Gupta Well, so back in 21, I believe, is when Pat Gelsinger wrote a letter on LinkedIn, which is an open letter to the open ecosystem. And he said, open ecosystem is a fundamental philosophy at Intel. And at that time, I was at Apple. Nothing opened there. Things are changing. But at that time, it was very rough. And I said, my God, a CEO like that who believes in open source and open ecosystem. And if somebody could fix or change Intel, Pat Gelsinger. And so that's what got me excited. I saw the letter in October, November timeframe. So yeah, it's good. But then, you know, things change in January, February timeframe 22, when they reached out that, hey, we would like you to run this open ecosystem team. And then they offered a very lucrative title of a VP. So I said, okay, you know what? That sounds exciting. And I'm never afraid of challenges in that sense. So let's bring on the toughest challenge. Let's put the pedal to the metal, everything that you have learned in the industry and see what we can do to turn the ship around. And we did our best. My team was responsible for the developer outreach in the open source world. We were running events. We were doing hackathons. We were doing workshops. We were doing blogs. Very successful podcast. All sorts of fun stuff that developers would reach out to. We ran that. And over the last year or so, I was running the developer programs team that was about 40 plus people. So I had a whole bunch of DevRel people under me who was driving, who was really directly writing the code and working with the developers. Then that was DevAcademy team. Then there was an ACE team, Academy, Community and Events. And that team was responsible for running large events, having Intel's presence at events like KubeCon, Open Source Summit, etc., ReInvent and all. And we were very directly engaged with academia, running student ambassador programs and all sorts of fun stuff, also managing all the social media handles. And then I had a bunch of folks. At some point, I had OSPO, the open source program office, part of my team as well. And then I had a whole bunch of principal engineer-like people who were working with hyperscalers or with AI communities and all. ([Time 0:03:37](https://share.snipd.com/snip/baf0be9a-af71-47d4-8bcf-4f20a23c4e64)) - **Sudden Restructure And Acceptance** - Arun recounts the sudden corporate restructuring that eliminated his team and how leadership changes signaled trouble. - He describes receiving the decision through his boss and moving quickly to acceptance and next steps. Transcript: Arun Gupta Yeah, restructure. That's the term. Yeah. Corporate restructuring. Jerod Santo I'm sure there were whispers, right? Like this stuff is other people were losing their jobs. For sure. Arun Gupta Well, last year or so, I would say we definitely saw the writing on the wall, not to the extent that the entire team will be eliminated. So I did not expect that, frankly, coming to that extent. You know, over the years I was there, we were definitely trimming team constantly, constantly doing budget realignment. That's part of the job. So no regrets, no complaints about that that how do we justify the cost how do we justify hey you're gonna sponsor kubecon at the top tier level that's 100k sponsorship then 100k budget Then a 50k travel etc logistics etc so you're gonna spend quarter million dollar on a running an event and how do you justify the cost okay so let's trim it down maybe not do the top tier Sponsorship let's do the second tier sponsorship kind of a thing. And let's send less people, let's make sure we are not making people fly from North America to Europe, you know, let's leverage the local European developers that we have. So all that change was constantly happening. So that was constant tripping that was happening. And last year, when Pat was let go and then Greg, Pat Gelsinger was let go. And then when Greg left earlier this year, that's when it became very, very apparent that, oh, this is not going good. And it's just like the very classical administration change, right? And the new administration came in. Anything and everything to do with previous administration got to go. And that's literally how it came across. It was a very cold call. There was no discussion. The decision was handed down to my boss that, okay, you and your team are gone. So I was not even communicating directly. My boss, one of the most empathetic and kind people. So she and I were constantly chatting, but from the executive management, the decision was handed down to us that, yeah, we don't need this. Well, okay. Well, I guess you have made the decision. So here we are, we're going to make best of it and as i said when when grief hits you right the order is usually death divorce and layoff and then there are five stages of grief so across the Team there were people of you know different ranges people very young in their career fresh out of college year or two out of college. And some were more experienced, some were more mature, some were at Intel for 25, 30 years, some not so that long ago. And so different people had different capabilities, different ability rather to process that grief. But for me personally, I was very clear that I'm just going to cut through the first four stages. There is no denial. There is no anger. There is no depression. There is no bargain. Yep. Cut it, pull the card. ([Time 0:10:20](https://share.snipd.com/snip/a2ab2667-1042-4a17-b9ab-c8fcf658a9f9)) - **Use Action To Beat Anxiety** - Do move quickly from grief to action because worrying wastes time and opportunity. - Arun's mantra: "Action absorbs anxiety" and he focused on coding and learning instead of stewing. Transcript: Arun Gupta But for me personally, I was very clear that I'm just going to cut through the first four stages. There is no denial. There is no anger. There is no depression. There is no bargain. Yep. Cut it, pull the card. I am on the accept stage. What next? Right away. So it took me, I would say, maybe a day or so to kind of get over it. But then I quickly moved to the XF stage. Okay, this is it. Good riddance. I know I'm going to focus on the ([Time 0:13:09](https://share.snipd.com/snip/90422fd8-3315-4952-9a16-8bc1ec5f2c84)) - **Start With The Easiest Win** - Try tackling the easiest task first to build momentum and confidence. - Arun recommends sequentially completing small wins to create a virtuous cycle of progress. Transcript: Arun Gupta Because that easiest thing will give you a quick victory and say, aha, I've shown something here. Now I can do a better thing on top of that. Usually people pick, let me tackle the hardest thing first as the hardest obstacle is out, but you're not even ready for that hardest thing. You know, the more stumblings, more falls, et cetera, are going to happen. So I pick the easiest thing over there, tackle it. That gives me a sense of accomplishment. Then go to the second easiest, third easiest, so on and so forth. So you build on top of that. And that action kind of creates that virtuous cycle for you, that flywheel for you that feeds back into you, that you are actually accomplishing something better. ([Time 0:18:29](https://share.snipd.com/snip/7e560228-8495-4451-8f60-7eb85c0d65ec)) - **Actively Prepare Your Job Search** - Do audit and polish your LinkedIn and resume, and build an external voice with blogs or demos. - Network proactively, ask for referrals, and craft a focused elevator pitch centered on developer, open source, and AI work. Transcript: Arun Gupta Yeah, that's happening. I have, fortunately, a very good deep network. Applying a role through a company website or LinkedIn doesn't get anywhere, right? It just lands in a box. ATS whole system is broken. So you really have to start talking to people, you know, getting a referral. And sometimes just the referral doesn't cut it. You know, so you've got to go talk to the hiring manager, essentially, that, okay, hey, here's a candidate that I know. And then you've got to think about, okay, what do you want to do? This is what you have done for the last 25 years. What do I want my next 10, 15, 20? Whatever that timeframe looks like, I want to do there. So you've got to craft that pitch ready. Okay, here are three things that really matter to me. And here is what I'm good at. Here is what I've done. Be very crisp with that elevator pitch, so to say. So I've been talking to a lot of folks, all different kinds of roles. IC, founding engineer, founding CEO, all sorts of roles. CMO, SVP, sorts of different roles. But I am not in a rush to really pick up a role. I think it's really got to match with what I'm excited about. And what I'm excited about really is three things that matter to me. Something that I really excel at is building that developer community. How do you grow your developer community? It doesn't matter what product it is. And last week, I wrote an article on LinkedIn, which talks about how you grow your developer community, say from zero to 100k, then from 100k to 1 million, then 1 million to 5 million, Then 5 million to 50 million, then 50 to 100 million. And I wrote that article based upon my experience because I built some of those communities. And what are the leading factors? What are the lagging factors that kind of indicate what that looks like? What are the growth triggers that you need to adapt? So that's building that developer community is something I'm super excited about. So that's one. The second part of it is, and anybody that is doing technology these days, open source is a big part of it. So if there's an open source angle to it, then I will excel all the more. Now, if there's no open source angle, that's fine too. But if there is an open source angle to it, then I will excel all the more. So how do you tap that open source community to work for you in your basis, in your advantage? And how do you make sure the open source monetization model is in place? That's the second part of it. And then the third part, I definitely want to have AI as the central element of it. So developers, open source, AI, those are sort of the three key bullets that I'm looking for, what my next role is going to be. ([Time 0:25:10](https://share.snipd.com/snip/bf0e4242-0672-48a5-9027-40ffe84b000e)) - **Small Models Empower Open Source** - Arun sees a pendulum shift from huge LLMs toward smaller, task-specific SLMs that run on CPUs. - He predicts open source will proliferate as smaller models and developer participation grow. Transcript: Arun Gupta So if you think about the pendulum swung too hard towards LLMs to begin with. Oh, 400 billion parameter model, 500 billion, a trillion parameter model. And those are the ones that we really need. Those are all closed source models. You should worry only about the performance part of it, and we are good with that. But now we are seeing kind of pendulum kind of coming back. You know, those LLMs are great, you know, at all the things that needs to be done in the world. But in order to solve my problem, I don't need 99% of that functionality. I need like a small language model that does my thing well and really well. So if you think about that pivot is coming down back from LLMs to SLMs, small language models, 3, 5, 7, 15 billion parameter model that can very well run on my CPU. And that's exactly where the innovation is happening. And if you think about, pick a vendor, Microsoft, Google, Amazon is very, very service centric, but pick any other vendor, essentially. They have an open source model. And those open source models are a lot smaller, 5 to 7 billion parameter model. Heck, even OpenAI has a GPT-OSS 20 billion parameter model. Grok, XAI just did their Grok model. It's a large model, but it's open source. All of these large commercial entities are realizing that open source is the way by which you can bring the largest developer mindshare. As quirky as Grok is, but now open sourcing it, you understand the quirkiness and then you can start participating and make it better. So I think in that sense, with AI, frankly, more open source is going to happen because it's not going to be less. Yes, people are going to be able to write more, generate more code. ([Time 0:31:36](https://share.snipd.com/snip/8a2b9164-3324-409b-bc6e-c4c824c9b5d2)) - **Generated Code Raises Debt Risk** - More generated code will increase quantity but may massively raise technical debt and maintenance burden. - Arun worries many AI-generated repos will become dead, unmaintained sources of vulnerabilities over years. Transcript: Arun Gupta Yes, people are going to be able to write more, generate more code. The thing that I worry about, though, is I'm not a coder, but I'm using wide coding tool. And before wide coding, I could have done maybe 400, 500 lines of code in a day. But with wide coding, now I can do 4000 lines of code a day. What kind of technical debt that generates for future generation? So for example, I remember seeing a keynote from GitHub where they say, hey, we wanna reach out to a billion developers. Sure, we wanna reach out to a billion developers, but what does that mean? The classic example they said is, a grandma should be able to say on her phone, hey, take all my Instagram photos, organize them in certain order, store them somewhere, and she doesn't Even say store, organize them in a certain order, et cetera, et cetera. Now, the idea was that is an NLU interface that you will parse that. You will, end of the day, you need software to organize all of that. So if you organize that source code, it's sitting in a GitHub repository. So the classic example is great, where you get it work up and running for the first time. Who maintains that source code if things go wrong? And the models are not there. I mean, I'll give you an example. I was playing with the app. I've been working on an app, actually, and that app really allows you to compare different protocols. So REST, gRPC, WebSocket, SSE, GraphQL. So there's a graph database and I make the query to the database and I compare them and I create a postman collection for it for example. So I did all that. Now I created a GitHub Codespaces version of it where by click, you can have that environment deployed in your own environment. And then after a few days, I realized, oh, you know what? That Codespaces environment is not working. So I asked Cursor, delete that Codespaces button from the repo. And the dude didn't understand. It says, oh, you want me to delete the button, so I'm going to infer you want me to delete the.codespaces and.devcontainer definition from the repo. It struck it out completely. I said, what the heck? I said, I want you to delete the button only. Am I not explaining it? Are you not getting it? Are you inferring it? So I think in that sense, the amount of frustration, the amount of technical debt it will create, yes, it'll generate more source code, but the amount of debt it'll create is scary. ([Time 0:33:33](https://share.snipd.com/snip/d9d7bb1e-a20d-4f1e-ba7f-25dd3443d20a)) - **Plan Prompts Before Generating Code** - Do use chat tools for planning and ChatGPT for iterative prompt crafting before giving commands to wide-coding agents. - Arun first refines requirements in ChatGPT, then converts that to a precise prompt for Cursor to generate code safely. Transcript: Arun Gupta Pretty awesome. Yeah, I think my flow has been similar. For example, I don't do discussion in Cursor. All of my discussion is with chat GPT. So, hey, I'm formulating an idea because I don't know at what point of time cursor will trigger. Oh, let me start implementing the repo. No, don't implement the repo right now. I'll let you know when I need to implement the repo. Stop. Don't do anything. Yeah, exactly. Right. So what I do is I discuss with chat GPT that here's what I would like to do. What about this? What about this? What about this? So I craft my prompt from ChatGPT because ChatGPT can maintain the session. So as I'm doing back and forth, then I say, all right, now craft a prompt. Now you understand my requirement. I think I've communicated clearly. So give me the requirement. So I read it. I make sure that everything is documented correctly. Then I say, make this as a prompt for cursor. Then I give that prompt to cursor. And then it says, boom, now you go generate the first shot of the repo. And usually I commit the first set of the repo and then I start tweaking it for developer experience, whatever that needs to be done. ([Time 0:44:31](https://share.snipd.com/snip/7beae930-818f-496e-bdcd-35022508758b)) - **AI Tooling Market Is Fast But Fragile** - Startup SaaS growth in AI tooling is explosive but fragile due to heavy backend model dependence and cash burn. - Open-source wide-coding tools like Klein and RueCode are gaining traction as alternatives to hosted front-ends. Transcript: Arun Gupta I mean, and the more you play with them, I mean, if you think about Lovable has reached $120 million ARR in seven months. Seven months. That's astounding. This is, this is, this $100 million ARR companies used to take three to five years. And at $100 million, they say, aha, I'm ready to go IPO. The landscape, the dynamics are very different. Cursor is almost a billion dollar ARR. Almost a billion dollar ARR. And I was listening to 20VC podcast. They were talking in that podcast that by end of next year, it'll potentially be $4 billion. But then this morning, they were also talking about on A16Z, or I think different podcasts about the AI bubble. Because what is cursor? Tomorrow, if say Anthropic says, we're not going to let you use Claude, cursor is going to fall flat. They're really relying upon the back end of the Claude. And all of these companies, Enthropic, OpenAI, they're all burning money. They're not cash flow positive yet. Right. You know, yes, their valuation is $60 billion or $500 billion, whatever that number is. But they're all burning cash. So they're burning more GPUs today. They're not earning money and if cursor is just like a vs code nicer interface on top of cloud why would anthropic not build deeper features with cloud code so it's tvd that cursor continues To stay the market leader versus cloud code kind of picking it up. So I think all of this landscape is very dynamic. And then on the parallel side, you start seeing tools like Klein or Rucode. These are open source wide coding tools. These are becoming popular as well. You know, if you look at Klein, there are about two and a half million developers using it. If you look at Rucode, there are about 20,000 stars to the repo. And they brag about how you can use, they're not tied to a back-end model. You can choose whatever model. You can even choose OpenRouter. So I played with this. ([Time 0:47:03](https://share.snipd.com/snip/bfc79706-4095-4cb6-be86-3a21f770a330)) - **AI Autocomplete Needs Human Oversight** - Current code-gen models often "yes-person" and produce plausible but unchecked output, requiring human domain expertise. - Arun and hosts stress that AI autocompletes; developers must still deeply review and own quality decisions. Transcript: Adam Stacoviak It's just still too hard to to be a developer or to develop i i guess debtless software like that's yeah the debt-free scream the old dave ramsey debt-free scream stuff to get to with software Yeah it's it's being a developer or making software, however you want to frame what that role is these days as it changes, I think it's still just too hard. Or if that's a commercial facing application or anything beyond a toy, you face serious challenges at scale or even at not scale. Like your sale could be a hundred couple, could be a couple hundred people. It could be whatever your little thing is, whatever version of scale you're talking about. But it's still just too hard. There's still too much awareness of what a developer does from a terminal to production, even terminals, like I just said, like open sourcing versus publishing to get up that that's Not, you know, the same to everyone or production or CI or all these different things that happen in the build stage. Not common knowledge. And it's still just too hard. I think for most people, and Arun, you mentioned your wife and how technical she is, but back to what I think you were saying was that she doesn't have the patience because that's not what She's trying to accomplish. She'll play with it as a tool because you mentioned to go and play with it and see what she thinks. But I think a lot of people will lack patience to put together what we as developers have had to put together for so long. And I wonder when will it actually get easier? I think it's easier to generate code, but it's not easier to generate good debtless code. Arun Gupta I think that's really the key, really. How do you... I'll give a classic example, right? I was working on a simple GraphQL backend. So it loads the data from a text file and it creates a GraphQL visualization. And my son came back from office yesterday. He was asking me, dad, what library are you using? I said, I don't know. Cursor picked up a library. So the point is that you are getting to that point because Cursor gives you that ability. Oh, I'll pick up a good library. It'll look good. If you're caring only about the developer experience, you don't know if that is the right library. You don't know if Cursor is really checking that, does that library has enough star forks maintainability or is that C preference? So, you know, I mean, as a developer, you go through that mental process that I'm going to pick chart3.js because that is the top notch library. Again, it goes back to context engineering. If I'm not giving the context, cursor will think what is right for it and then it'll move on. And you have no knowledge of how this is being implemented. And if you have no knowledge, that is scary. Putting that code into production is scary. Adam Stacoviak Yeah. These LLMs are like brute force. They have to give you a result. They're designed to give you some version of happiness. I even tell us sometimes like, don't yes man me, okay? Don't yes person me. Give me critical thinking defend your decision or, you know, explain why mine sucks or whatever it might be. But don't yes person me into the next phase because your job is to give me a result. Jerod Santo You're absolutely right. I'm so sorry. I won't yes person you. Yeah. Arun Gupta And that's one of the most annoying things. Touche. If you give like a suggestion to say Kershaw, which which is using Cloud backend, you say, hey, this doesn't look right. You are absolutely right. Let me go fix this. I couldn't even think of this. Jerod Santo I know. Because they don't actually think. They just autocomplete. Arun Gupta And that's the point, right? We call it AI. It's very artificial and not intelligent. Yeah. Adam Stacoviak Well, we're good with marketing terms around these parts. I don't want to defend it deeply here, but I do want to say, I think that that's one thing I like differently about augment code. Honestly, like they have this, I don't even know what it's called, like some sort of context engine. It's got something in it where I haven't seen quite that same behavior where the yes person, yes man, whatever you want to say is in there. It's it seems to be it retains things I've told it even after a few prompts or, you know, kind of like back and forth later. Like I've been very surprised at how much it retains of the the core goal. And I don't know if it's the peps or if it's the agent flow or if it's the DDD or whatever it may be. But something in this flow that I've been doing doesn't give me that result. It's actually been quite uncanny. I've been surprised at how well it seems to retain the context. And it's without me prompting it for the context. Like it retains it in some way. I don't know if it's my what i've been doing the way i've been doing it or it's augment codes when i do they do the rag method of of you know retrieval and stuff like that but uh this context Engine i think it might have some different smarts with the way it looks at your code base and it retains certain contexts i'm not really sure but i haven't had quite that same that same Experience it's been a bit more joyful. Jerod Santo It's probably some traditional software engineering they're doing in order to provide the model with that context and everything that it needs. A lot of the differentiation right now between these tools is how much software you write around the model in order to really put its best foot forward in a continuing fashion. And we see that in different ways, be better or worse. And that's really kind of the different, because other than that, there's not much that differentiates these things today. It's really hard, I think, as a product designer to, especially with the chatbots, especially. It's like, how's Claude's chatbot UI or buttons or whatever, any different than chat GPTs, really. There's not much there. They're just like their own wrappers around a model, which is why so many people have made money just putting better wrappers around the same model and getting people to adopt them. But there's not much, there's no moat there. And that's why I'm just laser focused on the quality because it was so bad for a while that I was like, what are you people talking about? I'm talking about the code gen quality up until Claude 4, where as listeners of this podcast know, I've been genuinely impressed. It's the first time where I've been like, this code doesn't suck every time. I could use this as maybe this is better than what I would have written. Like, I'm actually impressed. That being said, there's so many things that make it not 100%. Where are we on the AIs can write all the software spectrum? I don't know. Maybe we're in the 94%. They can do 94% of what you need to have, but the last 6% is everything. That's really what I've been watching. Can they make that jump? Because until we don't have to look at the code anymore, we absolutely have to look at the code. ([Time 0:58:30](https://share.snipd.com/snip/9cb38ec3-9e74-4bea-95f8-ea6a22e59357)) - **Structure Your Job-Search Routine** - Do structure your job-search days: mornings for LinkedIn and networking, afternoons for deep tech work and writing. - Arun blogs twice weekly and uses that external output to stay visible and sane during the search. Transcript: Arun Gupta The second part of it is you also need to kind of build that profile externally. So for the last several weeks, I've been blogging twice a week. Usually one article is about thought leadership and the one article is about technical leadership. So, for example, last week I talked about that thought leadership article on how to grow from zero to 100 million developers. And after this podcast, I'm going to record a video about the lab, about the app that I was talking about. I'm going to record that video and announce that GitHub repo essentially. And then I have another thought leadership article lined up for later this week. You know, basically, if you are running a dev rel, what your metrics should be. And that's the discussion that I've been having with the Developer Relations Foundation, DRF folks in LF. So I think in that sense, I'm just sharing sort of my blueprint. And frankly, that keeps me sane that, again, solving that easiest problem, then the next, and then the next, it allows me to show me progress. And the worriness could differ based upon the stage of your life, right? I'm at that stage of the career where I'm not worried about that, oh, I do not have a shelter and things like that. Or my elder son is already working, so he's on his own already. Younger son is a senior in high school, so he's about to go to college. There is no financial constraints per so in that sense I don't have a rush that even if I don't get something solid in the next few weeks months as well I'm not in a rush no I'll do a consulting Gig and as an athlete I'm very comfortable with being uncomfortable physically mentally things like that. So that's something you've got to kind of keep in your head. But again, build your external brand so that that makes you a more attractive talent. Everybody has access to chat, GPT, cloud, et cetera. But so everybody's writing a very impressive cover letter, a very impressive resume. What helps you stand out is networking with people. So that's sort of where I've been spending having a structure to your day that for the first couple of hours, I'm going to scram through LinkedIn, comment on people's articles so that You build that, reestablish that relationship. ([Time 1:14:18](https://share.snipd.com/snip/4f967baf-956d-46a0-ad05-ccab281a5eff)) - **Mock Interviews With LLMs** - Practice tough interview scenarios with LLMs to identify weaknesses and perfect your pitch. - Use mock interviews to prepare concrete stories and calm under pressure for real interviews. Transcript: Arun Gupta Be self-compassionate. You know, oftentimes when you apply for a role, it's a multi-week cycle. Recruiters don't respond back. Sometimes you don't even get to a recruiter. You may be submitting a few applications every day, every week. Sometimes you don't get respond. Don't let that define you. Don't let that bring you down. Just keep chugging at it, you know, in a very relentless manner. Keep chugging at it. Each one of you that is looking for a job at this point of time has done something wonderful. Just focus on that part of it. Don't let the negative energy come around you at all. Just pull the cord on it right away. Because if you're not going to believe in yourself, that's going to show up in your conversation. If you believe in yourself, if you have the confidence that, no, I've done this, you know, yeah, I've done this at scale, you know, and this is how I've done this at scale, imagine what That interview conversation might look like, you know, mock it, you know, which at GPT can help you mock those interviews. So I think start getting yourself ready. So when the moment comes, then you are ready. ([Time 1:18:04](https://share.snipd.com/snip/8643f9aa-1380-4356-831c-51dacec50b49))