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[💚THICKUMS🙈] “When your a shortstack goblin with huge 🍒 its kinda hard not to stare😩” - #hugetits #shortstack #goblin #r34 #hentaivídeo #nsfwtwt #deepthroat #facefuck #nsfw #gooning #hentai 🎨: bungus_bongos
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![✨ I spent the last 48 hours making GPT-4 read the entire Solana validator codebase and write documentation, so doesn't have to. Introducing — an AI-powered chatbot trained on nothing but code that can answer deep technical questions. How it works 👇 But first... A huge shoutout to , Zahid Khawaja, and Sean. Their hard work made prototyping this thing a breeze. Without further ado... Devs like to write code, not documentation. Tribal knowledge is lost when devs move on to other projects, leaving future devs to sort through mountains of code and figure out not just how it works, but why it works that way. This is all about to change. GPT-4's ability to write code is stunning. It seems to understand something fundamental about writing software that previous models just didn't. This comprehension of the principles that drive the design behind a complex system carries over into its ability to document existing codebases in a truly impressive way. With the enlarged context window(s), it's now feasible to feed GPT-4 entire files of code and ask it to write documentation about how the code works. Taking this as a starting point, the process looks something like this: 1. Download repo. 2. Depth-first traversal of repo contents, ignoring things like package-lock and binary files. 3. For each file, feed to GPT-4 and ask it to write documentation in markdown. 4. Save the output in a separate location as [outputRoot]/[inputFilepath][inputFilename].md 5. For each folder, we ask GPT-4 to write a summary of the folder, taking the newly generated documentation for all files in the folder and the summaries from each of its subfolders as context. Write this to the filesystem as markdown. Now we have a filesystem that matches the structure of the input repo, but all files in the tree are markdown documentation of the corresponding code file. From here, we: 1. Load markdown documents into LangChain. 2. Embed all documents via OpenAI embeddings. 3. Store embeddings in Pinecone. When a user sends a query: 1. Embed query. 2. Find k-nearest markdown files. 3. Feed to GPT-4 with a prompt asking to answer the query based on k-nearest markdown documents provided. The craziest part of all this? GPT-4 actually wrote ~30% of the code. The results are pretty good for 2 days of work. There is certainly room for improvement. Some items that are top of mind: 1. TolyGPT will occasionally hallucinate answers. It is especially bad with links to external sources, like GitHub. The base model seems to know a bit about Solana already, and sometimes this creeps in. Fine-tuning the prompt can solve some of this. 2. Context selection is difficult in a codebase this large. For example, sometimes it will pull in details about the Solana SDK when asked about transaction processing. The SDK files can seem relevant depending on the phrasing of the question. It may be worth breaking the documentation into subsystems to limit this. 3. Not all files fit into the 32k token window. As of now, there are 23 (out of ~1,100) files that cannot be documented in their entirety. Some of these files are very important to how Solana works. Final thoughts: 1. GPT-4 is super powerful, and we're going to see a ton of tools that supercharge the entire software development lifecycle. This is not 12 months away. For the people that can afford it, these tools are here now. And they're only getting better. Act accordingly. 2. The price of inference has to come down for this to go mainstream. I spent about $300 prototyping this project, and the final crawl cost about the same. The high cost of GPT-4 will push developers to other, cheaper alternatives with similar performance. This is coming very soon. If you have a large software project and you're interested in something like this for your codebase, fill out this form and we'll be in touch this week. Or just DM me :)](https://image.24vids.com/tw-1637521141236658176/amplify_video_thumb/1637520929566908417/img/_ACBce6WhDBxVegD.jpg)
![The most epic 13 minute AI rant I've heard in 2026 PS: My parent's heard this when I was playing it in the car and thought Jason ✨👾SaaStr.Ai✨ Lemkin went OFF like Stephen A Smith does on first take PPS: Full transcript below [17:00] Harry Stebbings: I I just wanted to ask Jason, if the people that we want are fundamentally different, the developers that we used to hire, we don't because AI writes the code for us. The marketers we don't want, the sales people we don't want—who who do we want genuinely? Like what is the attractive profile? Because your Anthropic’s and your OpenAIs are hiring, so so what are the people that we want in the companies of the future? [17:18] Jason Lemkin: Look, I know it sounds trite, but but the answer is simple. It's just the expression each year changes. We want folks that are genuinely AI fluent. It's pretty simple. Now you know, maybe last year we called them prompt engineers, right? That used to be a job. I don't know if you remember that actually used to be the hottest job on planet earth. Now no one needs a prompt engineer because it's pretty easy to prompt all these tools. That job died. Okay. Um and now we need go-to-market engineers. Um I think that job's going to die. We need—everyone needs so many forward deployed engineers. Like you can't hire enough forward deployed engineers. But uh you know um but Palantir just announced in whatever their their big their big event—they've gotten their deployment times down over 90% with forward deployed engineers. So that may become—so the this wave of disruption for the titles and the specificity, it's also exhaustingly accelerating. But it's really simple. You meet anyone for any role—sales, marketing, engineering, product, QA—they're they're either they're either they can't keep all of the ways they use AI to accelerate their job from spewing out of their mouth, or they're staring at you. It's there's nowhere in the middle. Like, and the person that comes in and says—it's it's it sounds Captain Obvious—but like, you know, you just had the whatever from Lovable, the the marketing head that was super popular on the show, right? She's just spewing AI-native insights into Lovable, right? It's not that complicated. You hire her, Elena, or whatever it is. You just hire her. It doesn't matter whether she's still in college or a junior or a senior or a middler, a left or right. And honestly, if you interview people, I would say of all even of the best startups I've invested in, maybe 30% of the management team meets this standard at best. 30%. Maybe less. And of the interviews I do in general, it's single-digit percents. It's just and in in that sense, it's the same as ever. Like you either lower the bar in hiring or you hire someone that's actually great. And someone that's actually great is so far ahead of you in how to apply to to employ the efficiencies of AI in their role, your jaw falls on the table. The difference is we used to need warm bodies. That's what's changing. We used to need warm bodies to answer the call, to do QA, to do code review, to to get the blue pixel to go from the upper left to the lower right. You laugh, but you need you literally needed to brute force this with humans. With AI, every day that goes by, the AI—you do not need brute force human beings on your team. And that's another reason they're shrinking. Why are all these new companies so efficient? They're just not brute forcing things with humans. They're just not. They're choosing not to. And so these team—all the brute forcers out there—everyone talks about how bloated teams got in 2021. I don't agree with that. I think they got as big as they needed to be when growth was high and you needed humans to do everything. All you look at these teams that that doubled—well if growth continued at 60% like the rate in early 2021 for 5 years or can help me do the math and every single thing a software company did required a human. You were understaffed by your 2021 headcount. You'd be sitting here in 2026. You every office in SoMa would be triple packed and you there wouldn't be enough humans to staff your company. It's just the world changed. [20:33] Harry Stebbings: Jason, you live on the bleeding edge. I think me and Rory see that and I think the world sees that when they hear you every week in terms of how you run SaaS. For all of the CEOs and execs who listen to the show, what would you advise them in terms of determining whether someone is AI fluent when they meet them for jobs, for talent? [20:51] Jason Lemkin: Here's I realized I was just asked this. I just did a review with a super fast startup growing just crossing 100 million and I was asked this question. And one of my favorite executives, I thought his answer was pretty dated and because he gave me an answer that was about 6 months old. The answer 6 months old is: "I look for folks in my team, I look for you know at what tools they play with." Okay, that was a great answer in like summer of 2025. Okay, I tried Lovable last week. Okay, the answer in 2026 is: "What commercial AI tool have you brought into your organization this month?" That's the test. Anyone that is on the bleeding edge that you would want to hire—now there are so many great products in the market. Okay, there is no excuse in any role to have not brought one tool a month into your organization. Okay, there—now there's going to be better and better tools and better and better products as the year goes on. What's the one you did? And you will see folks with their deer in the headlights to this question. What what sales tool? What marketing tool? What product tool? What engineering tool? What did you bring in? Why did you pick it? How does it working? Because if you're at remotely at the cutting edge, you're all over this. You're looking for the next agentic tools that will radically improve how you do business. This is—you think everyone thinks SaaS is at the bleeding edge, right? You know, you know, all we do is we're just looking for the tools and trying them. Okay? Okay, we're one year ahead of everybody else because we did the simplest thing in the world. Like we tried the tools early and we trained them. We trained them for a month. Okay, I'll give you—want hear a horrible example from this week? Super hot AI company valued at 6 billion. Okay, I'm not going to name it. Um, this week yesterday told us we had to quadruple what we spent on their product. Okay, their agent told us, right? And why did this happen? Okay. Well, at this $6 billion company, no one had trained the agent on its pricing properly. No one had tested it. They said, "Well, well, we've been in beta." And we said, "Well, when did the beta launch? A year ago." Okay, these are people asleep at at the wheel. You want somebody who the instant this comes up, they exactly know what the issue is. And "Hey, when I was at Lovable Replit, we trained the agent. This is how we did it. I brought in this tool. I brought in this tool that that Rory invested in last week. It solved all these issues." That's what you want to hear. And if they haven't brought in a tool in the last 30 days, at least deeply evaluated it. I don't really care whether they bought it, but gone so far down the funnel they can tell you—pick whatever tool: Fixie, Regie, GC, AIGC—I don't care how you went through it, you looked at it, you can tell me the eight ways it would improve the productivity of your business and three you didn't. Just don't hire that person because they're going to run your company to the ground. This is the job today. The job today is not to screw around on ChatGPT and to be a prompt engineer. The job today is to bring the best AI and agentic products into your organization and leverage all the hard work that the engineers have done building those products. That's your job. You don't have to screw around. You don't have to be a prompt engineer anymore. You have to be an agent deployment expert. A—this is the new job we're making up today. An Agentic Deployment Expert. That's your job from C-level to junior. Agentic Deployment Expert. Don't hire anybody else. You're going to regret it. They're going to stare at the camera. He's good. Stare at the camera. He's honorable. We could probably just I could slip away, get a coffee, and come back. No. And I I sound exasperated, Rory. And I—but the reason I am is I can just see I can see my best companies doing it. And I can see some companies I've invested in not doing it. And I want to cry. I just want to cry when they have no ADs on their team. I just—like you're flushing your years of your life down the toilet by not approaching your how you're building this company this way. [24:33] Rory: Yes. And at the risk of being positive, it's worth pointing out two things he didn't say. Well, something implicit why he said—Jason didn't do the only hire, you know, he didn't commit the um employment law, I think it's a civil penalty of saying only employ people below X who get the new new thing because he implicitly said anyone can do it provided you're willing to learn. And I think that's the big aha that's one of the positive statements to make here right? Look and I think it applies—I'm always wary of being "Hey, coming across, hey this this is the things that you all have to do." I think it applies to everyone including investors right? I mean I will say I have found that unless you're willing to invest the time learning these tools you actually shouldn't be investing in them. One of my partners Andy had this expression: "You know, if you decide you want to stop learning new things you probably should retire within 6 to 12 months and never write another check again." Maybe that's down to 3 to 6 months at this stage, right? And I think, you know, it's— [25:27] Harry Stebbings: Yeah, I actually I actually had a meeting with mine and Jason's biggest investor the other day and I—pretend he's not here—I said I think he's the most equipped investor for this generation of investing because I don't think anyone quite sits at the bleeding edge like he does on the investor side. [25:42] Harry Stebbings: Why in terms of using the equip stuff? Yeah. Yeah. In terms of using the stuff, understanding understanding bottlenecks, constraints. For sure. [25:51] Jason Lemkin: But can I just add one point? We can just cuz it's so important if it helps people. Okay, we are—and thank you Harry. We're going through these phases. Okay, and when AI started to blow up for real for us, uh call it early 2024, right? Maybe late '23, I wasn't equipped. It was too technical. I wasn't going to go in and figure out—I wasn't smart enough to figure out how to deal with a massively hallucinating LLM API and turn that and turn that into something magical. Kudos to investors and others that that got it in early '23, '22. I mean I remember I—I guess it was maybe SaaStr Annual '23. I was with David Sacks and I did a Q&A and I said, "How you thinking about AI at Craft?" He's like, "Well we're all in. We want 80% of '23 of investments to be AI." I'm like, "Great but like show me the show me the great ones in market." He's like, "They're all prototypes. We're all they're all they're all proof of concepts but we're all in anyway." That's where you kind of had to be in '23 if you weren't investing at like the LLM level. Okay, I wasn't smart enough. Then we went through this weird-ass prompt engineer era where like you you could torture these products to do something good, right? But you had to torture them. You had to like craft these crazy things that made no sense. Now we are in the era where mere ordinarily smart generalists can make these tools do magical things. And literally I go to these meetings and people be like, "I don't know how to like this is so scary. I don't know how to do this." And we show them our backends. Do you know how to do a workflow generator? Do you know how to do a a decision tree? Like we've been building these since software in the '90s. Okay, if you—I can show you all of our agents. The how they work is novel. They do have to be trained. You can't be lazy and have these agents work. But honestly, the the UI, the UX, the way we interact with them, it's just software. And so my point is: Pick yourself off the ground. This is your time now. If you felt lost in AI era, if you felt like you're behind, you don't understand what all these people are saying on X and Twitter and their Claude and and their and talking about all the 4.6 point Nano point and it's over—like you just it's not your world. This is your time. This is your time for the generalist that knows how to use software tools really really well. And I—this is my last point but it's so important. If ever in your recent life—and this is why you could be all you need to be is young at heart to Rory's point—if in the last three to five years you have successfully deployed a piece of enterprise software of any sort you yourself, not some agency you hired, but if you have deployed it, you can deploy any agentic tool. Any. And you can become the hero in your company and you can become the hero in your functional area. But I watch folks—I'm literally helping a company now that they're adding hundreds of sales folks this year with a new pre-IPO COO—he's not hasn't brought in a single tool, totally scared of it. Okay, it's not that hard. Did you use SalesLoft? Did you use Outreach? Did you use HubSpot? Do you know these tools? If you can deploy these tools, you can deploy a world-changing AI agent. And so this is the time for people like the folks that that were shut out of the AI revolution right now. The generalist folks that are not that know how to deploy software that don't even know how to build software. Like vibe coding for me was folks who knew how to build software, but you didn't have to be an engineer. Now, you just need to know how to deploy software to win with AI agents. That's all you need to know. So many people have these skills and they're petrified of AI. "How did you do that? How did you deploy an AI BDR?" Well, we bought a piece of software, we figured out how it worked for a day, we set it up in an afternoon, and then and then we did spend 30 months training it, which you didn't do with this old software because in the old days, we just had to manually upload all the data, right? And there was no training. The the only non-intuitive part is training these things. And it's it's it's just work. So that's why when I see folks on the management team not doing this, there's no excuse. You do not need to be technical to win with AI agents in Q2 of '26. You do not need to be even 1% technical. Not at all. So it's your time. Or you're going to get laid off. Or you're going to get laid off because you're not going to matter.](https://image.24vids.com/tw-2036795243681423518/amplify_video_thumb/2036794127560613888/img/52_cdbzzL6_foTSI.jpg)
![HOW THE U.N. FOOLED THE WORLD ABOUT CHINA Westerners took over control of a United Nations body to claim the Chinese locked up a million or millions of people—but they had no evidence. The “MILLIONS” number was extrapolated from interviews with just 40 people, and they were not randomly selected, said Australian lawyer and researcher Jaq James from Geolaw Narratives. These clearly untrustworthy findings were then amplified by mainstream media reports quoting people from US groups paid to demonize China—with their membership and funding hidden from readers, our own research shows. The result is a massive scam on the world’s public. Four points: . 1. THEY HIDE THE NEED FOR DERADICALIZATION Point one: In mainstream reports about terrorist deradicalization efforts after the 9/11 attack, the 9/11 act of terrorism is mentioned. Same with the deradicalization efforts after the 7/7 terrorism act in London. But there were more than 130 brutal, acts of terror in China—that’s correct, more than 130 murderous acts in which large numbers of innocent people were killed by Uyghur separatists. But these are simply not mentioned in typical reports. Only the response is mentioned. By deliberately removing the huge number of acts of terror to which the Chinese are responding, western journalists make the Chinese look like they are taking arbitrary actions against the Uyghurs. Yet the truth is that they were doing what westerners also did, responding to terrorist acts. [Image shows clip of “French re-education camps” headline] You can see how unfair that is. . 2. ORIGIN OF ‘MILLION LOCKED UP’ CLAIMS Point two: The first claim that China had arbitrarily locked up a million people was exposed by independent journalists at The Grayzone, as coming from an extrapolation from just eight people. More damning still, that extrapolation came from CHRD, a notorious US-based demonization-of-China outfit funded by the US government. The second claim that million people had been locked up came from the UNOHCR, the UN's human rights office. They took interviews from just 40 people and extrapolated what they heard to claim one million people had been unfairly locked up, as Jaq James’ research shows. Ms James points out that the UN should have interviewed randomly selected individuals to get a fair picture. But by interviewing politically networked ones, they are guaranteed to get a biased image. Again, fundamentally unfair. . 3. JUSTICE AND FAIRNESS Point three: This UN department had a leader, Michelle Bachelet, known for her appetite for justice and fairness. This meant she struggled with her staff—westerners who really controlled the operation. She insisted that their report be released alongside a response from China. Here we can see two reports – one from the UN group’s staff, and the response from China. The staff report was just 48 pages long. China’s reply was 120 pages long. How many western mainstream media outlets quoted the Chinese report, or even acknowledged its existence? Zero. Not one. Not. A. Single. One. . 4. IN WHICH WE DESTROY THE FINANCIAL TIMES Point four: The mainstream media write-ups about this subject hid the truth from readers in a shockingly deceitful way. Let’s take a look at a Financial Times article, which is fairly typical. It reinforces the UN group’s dubious findings with evidence which comes from “human rights experts and activists” – in other words, people paid by the US government to demonize China. The writers do NOT provide their names, just calling them “experts”. As Kyle Feranna said in his 2024 book: “Western NGOs, ostensibly concerned with human rights, disproportion¬ately focused on alleged violations in China despite much worse abuses occurring elsewhere in the world.” In other words, they weaponize human rights as tool to use against the Chinese. . GUANTANAMO BAY Then we get a quote from “Rushan Abbas of the Campaign for Uyghurs”. The Financial Times hides from its readers the fact that Ms Abbas was at the notorious Guantanamo Bay – not as a Muslim victim, but on the US side there. And the paper hides the fact that the Campaign for Uyghurs is financed by the NED, the CIA’s regime change spin off. These are absolutely key facts which change the whole tenor of the piece – and the FT is cheerfully deceiving its paying readers by omitting them. Abbas is quoted as saying, of the UN group’s western office staff, “without them, it would not have been released”. This reinforces many reports which say that Commissioner Michelle Bachelet did not want to release such an unfair report, but her staff, mostly westerners, pushed the unfair report out on her last day. . ANONYMOUS SOURCES Then the FT feature article quotes yet another person described as “an activist” and declines to provide his or her name. Then we go to yet another unnamed “human rights” officer. And then yes, a further unnamed “human rights” officer. And then we get a quote from an unnamed “person with knowledge”. And here we have another anonymous quote – a senior European diplomat. No name. I mean, there are so many unnamed sources in this piece, it would have been rejected at any decent journalism school. . OTHER SIDE OF THE STORY Now the FT piece breezily passes over a reference to the other side of the story by quote “China and 68 other countries”. This is hilarious. So if you are a demonizer, paid by the US State Department, you can get as many column inches in the FT as you like, with your name and funding hidden. But if you are 69 actual named countries defending China, giving the other side of the story—well, they’ll just mention it in passing. . THE REAL STORY Now, right at the bottom of the article we actually have a named person – and he actually tells the real story. “Bachelet was never really in full control of her office,” said Marc Limon. Now any journalist worth their salt would realize that that is the key quote in the whole article – and they would ask – okay, if she was not in charge of that UN group, WHO WAS? But the FT writers choose not to ask that awkward question. They don’t want to know. And they definitely don’t want their readers to know. . CLOSING LINE The FT writers close the article with a line from a quote “Uyghur journalist” who actually is named. She is Nuriman Abdureshid. So the reader is left thinking – oh, so they actually did manage to discuss this with someone in Xinjiang, someone with a name and a job. But what the FT "journalists" omit to tell the paper's long-suffering readers is that Ms Nuriman Abdureshid is associated with a group called Victims of Communism Memorial Foundation, a Washington DC group which demonizes China to such an extreme extent that even other anti-China groups avoid them out of sheer embarrassment. Do I have proof that Victims of Communism is backed by the government? Well, the AI which has taken over Google tells us that Victims of Communism has received funding from the US State Department to deal with human rights issues. Here’s what happens when we look up their funding to check the details. [CLICKS LINK] “SORRY YOU HAVE BEEN BLOCKED’. Ah yes, the famous US “free speech”. . A QUESTION I’m going to close with a question. Why is the political and media class in the west working so hard to fool the world about the Chinese? Why work so hard to demonize a country that is working hard to lift itself out of starvation level poverty? What don’t they want the world to know? Could it be that China is actually doing something right? Think about that – and we may all, one day, be on the road to peace. .](https://image.24vids.com/tw-2070014240581431742/amplify_video_thumb/2070012930083758080/img/U1NzaDJxmLJBcpd4.jpg)