Sending a resume is now an outdated and ineffective way to get noticed by AI startups. The proven strategy is to demonstrate high agency by building a relevant prototype or feature improvement and emailing it directly to the founders. This approach has led to key hires at companies like Suno and Micro One.
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Instead of just sending a resume, prove your value upfront by delivering something tangible and useful. This could be a report on a website bug, an analysis of API documentation, or a suggested performance improvement. This 'helping' act immediately shifts the dynamic from applicant to proactive contributor.
New AI tools often have flawed user experiences. Instead of just getting frustrated, create a detailed product breakdown with recommendations for improvement. Sending this to the company serves as a powerful "warm intro," showcasing your product skills and providing value before you're hired.
With 88% of companies using AI to screen resumes, traditional applications are often unseen by humans. A new hack involves sending a small Venmo payment with a resume link directly to a hiring manager, creating an unignorable notification that bypasses automated gatekeepers.
A powerful, non-traditional way to break into a competitive field like AI is to identify a company's core research hub and offer your services for free on off-hours. This demonstrates passion and provides direct access to opportunities before they become formal roles, allowing you to bypass traditional application processes.
To get hired in a competitive market, stop spamming resumes. Instead, consistently create and publish content on platforms like LinkedIn that showcases your expertise, knowledge, and passion for your craft. This demonstrates value and attracts opportunities, making you a magnet for recruiters rather than just another applicant.
Lovable prioritizes hiring individuals with extreme passion, high agency, and autonomy—people for whom the work is a core part of their identity. This focus on intrinsic motivation, verified through paid work trials, allows them to build a team that can thrive in chaos and drive initiatives from start to finish without supervision.
Lovable employs a full-time "vibe coder," a non-engineer who is an expert at using AI tools to build functional product prototypes, templates, and internal applications. This new role collapses the idea-to-feedback loop, allowing teams to prototype and ship at unprecedented speeds without relying on engineering resources for initial builds.
Perplexity's talent strategy bypasses the hyper-competitive market for AI researchers who build foundational models. Instead, it focuses on recruiting "AI application engineers" who excel at implementing existing models. This approach allows startups to build valuable products without engaging in the exorbitant salary wars for pre-training specialists.
In rapidly evolving fields like AI, pre-existing experience can be a liability. The highest performers often possess high agency, energy, and learning speed, allowing them to adapt without needing to unlearn outdated habits.
Instead of recruiting for a job spec, Cursor identifies exceptional individuals and "swarms" them with team attention. If there's mutual interest, a role is created to fit their talents. This talent-first approach, common in pro sports, prioritizes acquiring top-tier people over filling predefined needs.
