Contrary to the belief that deep-tech startups should be purely technical, ElevenLabs prioritized distribution early. Their first 10 hires included 3 people focused on go-to-market and growth, enabling both self-serve and sales-led motions from the start alongside foundational research.

To move beyond general knowledge, AI firms are creating a new role: the "AI Trainer." These are not contractors but full-time employees, typically PhDs with deep domain expertise and a computer science interest, tasked with systematically improving model competence in specific fields like physics or mathematics.

The forward-deployed engineer (FDE) model, using engineers in a sales role, is now a standard enterprise playbook. Its prevalence creates a contrarian opportunity: build AI that automates the FDE's integration work, cutting a weeks-long process to minutes and creating a massive sales advantage.

Instead of searching for new "AI" job titles, non-coders should focus on applying AI capabilities to traditional roles like marketing or sales. Companies are prioritizing existing positions but now require AI fluency, such as building custom GPTs or using AI assistants, as a core competency.

Top-performing engineering teams are evolving from hands-on coding to a managerial role. Their primary job is to define tasks, kick off multiple AI agents in parallel, review plans, and approve the final output, rather than implementing the details themselves.

Companies are replacing traditional, siloed sales assembly lines with a centralized "GTM Engineer." This technical role uses AI and automation tools to build revenue systems, absorbing the manual research and prospecting work previously done by individual reps. This allows for rapid learning and scaling of creative ideas across the entire team.

Traditional "value-based selling" is obsolete. In an AI-driven market, customers demand tangible, immediate results, not buzzwords. A sales rep's only true value is their deep product expertise—the ability to deploy the tool, troubleshoot, and demonstrate ROI firsthand. Reps who lack this are being bypassed in favor of those who can actually deliver.

The traditional tech team structure of separate product, engineering, and design roles is becoming obsolete. AI startups favor small teams of 'polymaths'—T-shaped builders who can contribute across disciplines. This shift values broad, hands-on capability over deep specialization for most early-stage roles.

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.