I'm curious about how everyone here is approaching the transition into a Forward Deployed Engineer role. If you had 90 days to become interview ready for an FDE position, how would you spend your time? Would you focus more on: Building AI agents Learning system design Improving customer communication Creating end to end projects Practicing technical interviews Something else entirely If you've already landed an FDE role or are actively interviewing, what do you think made the biggest difference in your preparation? I'd love to hear your roadmap, mistakes to avoid, and the resources that actually helped. I think this discussion could become a valuable guide for everyone in the community.

ElevenLabs is hiring for a Forward Deployed Creative (FDC) role 👀 This is not your typical job. It’s for people who: Have strong creative + marketing instincts Can work directly with clients / brands Are comfortable using AI creative tools Think like a builder + strategist In simple terms: You don’t just create content… you solve real business problems using creativity + AI Why this matters Roles like FDC (Forward Deployed Creative) are the future. Companies don’t just want designers or marketers anymore. They want people who can: Understand clients Execute fast Use AI to scale ideas Deliver results (Reference screenshot attached above) Want to become an FDC or similar role? We’re breaking down: AI tools you need to learn Creative + strategy skills Real-world execution frameworks 👉 Start Learning Keep it simple. Stay ahead. This is where the market is going

You've probably heard of the Forward Deployed Engineer the role Andreessen Horowitz (a16z) called "the hottest job in tech," growing 800% in a single year at companies like OpenAI and Anthropic. Almost nobody is talking about the creative version yet. That's the opening. A Forward Deployed Creative (FDC) is a creative embedded directly with top brands and agencies to help them actually adopt generative-AI tools producing high-craft work, pioneering new production workflows, and turning "cool AI demo" into work teams can really ship. Think of it as three roles in one: 🎨 Creative — you make real, high-craft work with AI tools 🤝 Customer — you work hands-on with clients to drive adoption 🔧 Product — you feed what you learn back to shape the tools And it's not theoretical. Companies like Luma, FLORA, High touch, and Adobe are already hiring for it some in the $150K–$200K range often as brand-new "0-to-1" roles where the first hires write the playbook. Here's why this is a real opportunity: the role is exploding right now, there's no established pipeline of trained FDCs, and the field is wide open. Being early to a role like this is one of the best career positions there is. The catch? Most people have never even heard of it so they can't position for it. That's exactly what Part 1 fixes. 👉 Head to the Classroom and start [Forward Deployed Creative: Foundations (Part 1)] In it you'll learn exactly what the role is, why it exists, where FDCs work and what they do all day, the mindset that makes someone great at it, an honest intro to the AI creative craft plus a transition roadmap tailored to your background (designer, motion, video, marketer, developer, and more) and a capstone to build your first proof piece. If you've felt like AI is reshaping creative work and you want in early this is your starting line. Drop a 🚀 in the comments if you're starting Part 1 today.

Most people think AI is inconsistent. It isn't. The quality of the output depends largely on the quality of your prompt. If you've ever thought, "ChatGPT isn't giving me what I asked for," chances are your prompt needs improvement. Here's a simple framework that professionals use to get significantly better results from any AI model. The 5-Part Prompt Formula 1. Role Tell the AI who it should be. Example: "You are a senior marketing strategist with 10 years of experience." This helps the AI respond from the right perspective. 2. Task Clearly define what you want. Instead of: Write about AI. Try: Write a LinkedIn post explaining how AI agents help small businesses save time. Specific tasks produce specific results. 3. Context Give the AI background information. Example: The audience consists of small business owners with no technical knowledge. Context helps AI tailor its response to the right audience. 4. Constraints Set clear rules. Examples: Keep it under 250 words. Use simple English. Avoid technical jargon. Include one real-world example. End with a question. Constraints improve consistency and reduce unnecessary revisions. 5. Output Format Tell AI exactly how you want the response structured. Example: A strong hook 3 short paragraphs Bullet points where appropriate A conclusion 5 hashtags When you define the format, the output becomes much easier to use. Complete Prompt Example You are a senior marketing strategist. Write a LinkedIn post explaining how AI agents help small businesses automate repetitive work. The audience consists of business owners with no technical background. Use simple language. Keep it under 250 words. Include one practical example. End with a question that encourages discussion. Format the response with a compelling hook, three short paragraphs, and five relevant hashtags. Why This Framework Works Most people give AI a sentence. Experts give AI instructions. The more clearly you communicate:

Most companies don't fail at Forward Deployment because their engineers aren't good enough. They fail because they mistake customer success for product progress. That's a dangerous assumption. Forward Deployed Engineers (FDEs) have become one of the most talked-about roles in enterprise software. Palantir built an entire operating model around them. Companies like OpenAI, Anthropic, Databricks, and others are investing heavily in similar deployment teams. But after reading through engineering playbooks, deployment case studies, and discussions from experienced FDEs, one pattern kept appearing. The companies that win aren't the ones with the smartest Forward Deployed Engineers. They're the ones that learn the fastest from them. That's a very different objective. Most people describe an FDE as "an engineer who works closely with customers." That's technically correct. But it completely misses the real purpose of the role. A great Forward Deployed Engineer isn't there to solve customer problems. They're there to discover which customer problems deserve to become product capabilities. That distinction changes everything. Think about Palantir. Their engineers don't simply configure software and move on. They embed deeply inside customer environments, understand operational workflows, solve incredibly specific problems, and then look for patterns across completely different organizations. A government agency struggles with entity resolution. Months later, a pharmaceutical company runs into what looks like an unrelated issue. Then a financial institution experiences something surprisingly similar. Three different customers. Three different industries. One underlying engineering problem. That's the moment where a company stops thinking like a consultancy and starts thinking like a platform company. Instead of shipping three custom solutions, the problem becomes a reusable capability inside the core product. Every deployment makes the next deployment cheaper. Every customer makes the product smarter.