Anthropic and OpenAI corner software market (worst case scenario)

### TL;DR Anthropic and OpenAI's introduction of the "Forward Deployed Engineer" role reveals that AI companies can't deliver fully automated solutions—instead, they've spawned a "human-as-a-service" model that could monopolize software development. Job seekers can ride this wave by mimicking the job requirements and using AI to ace interviews. --- ## What is a "Forward Deployed Engineer"? The job title sounds like military jargon—because it is, originally from Palantir. Palantir coined the term: send a trained, prepped engineer to your company, basically an "engineering slave." Now Anthropic has announced a $1.5 billion joint venture with BlackRock and Goldman Sachs, primarily to deploy these engineers across major enterprises. Immediately after, OpenAI launched its own deployment company, DeployCo, valued at $14 billion. The steps are simple: Go to LinkedIn, change your title from "Prompt Engineer" or any buzzword—like "Context Engineer" or "Vibe Code Fixer"—to "Forward Deployed Engineer." You don't yet know what it means, but that's fine—nobody does. It's provocative, attention-grabbing. One of the coolest job titles I've ever heard. --- ## The Biggest Confession from AI Companies These forward deployed engineers—let's call them "trash contractors." You go to Anthropic and say, "Hey, give me some AI. My engineers are useless now; they do nothing all day but talk about orchestration. Tokens are soaring, but I see nothing." Anthropic says, "Bro, I hear you. Here are five forward deployed engineers." These guys are like the Navy SEALs of AI—they come in, jacked, wearing black short-sleeve tees, air-dropped by helicopter (yes, Anthropic literally helicopters them in). They start "dumping trash"—doing the part AI is good at: demos and prototypes. In the first week, they build a system with a killer demo. The old-school executives at your company are stunned: "Oh my god, we've never seen anything this fast, this detailed." Of course, it's trash. We know it's trash, but they don't. Then they deploy a few automation widgets that work fine early on because there are no users. Six months later, problems arise, you realize it's trash, but the forward deployed engineers have already "backward deployed"—they left months ago, leaving you with the mess. You want to recall the SEALs? No problem, here are two more. You say, "Wait, these aren't the same people." They say, "No, no, these are all trained, 100% organic synthetically produced forward deployed engineers." What this tells us: The product AI companies offer isn't what they promised. They promised automation that could replace human labor, plug into an organization, and run itself—something executives could operate. But it's the biggest scam in capitalist history: They inject a little virus that makes your team lazy, then offer the antidote—hire our engineers, these guys are so badass you've never seen anything like it. --- ## Two Future Scenarios ### Scenario 1: Sci-Fi Dystopia In the future, software engineering is no longer a role you can hire for. Every company no longer has its own engineers. If you want software, you go to a software company like Anthropic. Anthropic has a giant warehouse with hundreds of thousands of these forward deployed engineers. And you get a discount because these engineers work for Anthropic and get tokens at cost. A decade later, only OpenAI and Anthropic are making software. You might think: "What's stopping a kid from using Opus 4.7 to learn software development, then grow up to be an AI engineer hired by a startup?" It doesn't work, because you assume you'll have access to those models—but you won't. You're not getting the models that make software. Haven't you noticed? Anthropic with Mythos does exactly this: they give you models that help you cook, write poetry, manage health—but the software models are tightly controlled. In this dystopian vision, Anthropic becomes a quadrillion-dollar company, the gatekeeper of all software development. ### Scenario 2: Open Source to the Rescue If OpenAI and Anthropic keep their models open and fairly accessible, we avoid the dystopia. But they don't—you can't access Mythos. There's always one model Anthropic holds back, and funnily enough, it's the safety model. They'll give you a software model, but it comes with countless security holes, making it undeployable. So if open-source models can keep up, we retain our freedom. You can build medium-quality software in-house, but not as good as what Mythos produces. Still, you can make cute little apps. --- ## What Should Job Seekers Do Now? Fortunately, Anthropic has given us the answer. Forward Deployed Engineer, Applied AI—these are hot now. If you're on X, you see everyone talking about forward deployed engineers. ### Revamp Your Resume Go to Anthropic's job posting (don't apply), look at the responsibilities section, copy all the bullets: - Build production-level applications using Claude models within client systems - Deliver technical products such as MCP servers or sub-agents to clients - Stay up-to-date with the latest LLM developments - Establish long-term client relationships Paste these into your resume, tweak them slightly so they sound like something you'd say, but imply that this is what you're currently doing. Your revamped resume will be super sexy—because the AI screening the resume is prompted with: "Hey, match this Anthropic job posting against our applicants, make sure it matches, then pass." So you'll definitely get a call—your resume jumps straight to the top. ### Prepare for Interviews Ever watched the Dwarkesh podcast? He interviews all the AI big shots, sounds knowledgeable, asks great questions. You'd think he's a genius? No—but The New York Times ran an article saying this guy just grinds the material like crazy—a super hard worker using flashcards, private coaches. You need to become a mini-Dwarkesh: superficially learn all the theory, never actually do it, but understand the principles. It's like the new LeetCode—understanding algorithms but never using them. Now it's about understanding the agent paradigms and patterns you're not sure you'll ever use, but the interview might test—pure practice. If someone asks you how to manage 100 agents simultaneously, you need an answer. If they ask how many PRs you can submit in a day, say at least 300—you can't lose to Boris. That guy submits 300 PRs on his way to work and has no idea what to do when he arrives. ### Technical Interviews If you get to the technical interview, it's not hard—assuming you can already code. In addition to the usual coding questions, they'll ask you to build a multi-agent orchestration system—something you bragged about on your resume. What you do is take everything you've practiced and learned, open Claude, and just brain-dump—say it, type it. Claude does everything for you; you just accept the praise. You might think this is cheating—AI handling everything. No, no, no. This is called AI engineering. This is forward deployment. It's a skill. The interviewer will say to you: "This guy just built a 100-agent orchestration system in front of my eyes. I saw it." Obviously, you did nothing—Claude did it all—but the demo is amazing. Remember Soham? The guy who was found working for 12 companies simultaneously. He mastered the interview process, then started taking sick leave and slacking off once hired. You have to be flexible: forward deploy yourself, put on a turtleneck, or a half-sleeve shirt, look buff. Anything goes, as long as you stand out. --- Source: https://www.youtube.com/watch?v=juHv_Vi4giU