Unlike at smaller companies like Cruise where scope is abundant, the speaker felt Meta's senior IC ranks were "crowded." This created an environment where finding impactful, level-appropriate projects required significant effort, making it harder for new senior hires to demonstrate their value quickly.
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The speaker suggests Meta's management struggled to onboard him as a senior IC because most senior talent is promoted internally. These internal leaders already possess deep institutional knowledge, creating a blind spot for how to ramp up experienced outsiders who start from zero context.
An IC7 engineer found the senior staff role was mostly meetings and docs. He preferred coding, debugging, and mentoring, which aligned better with an E5/E6 level. He actively requested a demotion to improve his job satisfaction, challenging the conventional "up-or-out" career mentality in tech.
Since modern AI is so new, no one has more than a few years of relevant experience. This levels the playing field. The best hiring strategy is to prioritize young, AI-native talent with a steep learning curve over senior engineers whose experience may be less relevant. Dynamism and adaptability trump tenure.
The path to senior engineering levels is tied to the scope of your work's influence. Rather than explicitly seeking promotions, focus on projects with natural potential to grow from solving a team's problem to solving an organization's. The promotions will follow the impact.
Mark Zuckerberg's AI strategy is not about hiring the most researchers, but about maximizing "talent density." He's building a small, elite team and giving them access to significantly more computational resources per person than any competitor. The goal is to empower a tight-knit group to solve complex problems more effectively.
Traditional big tech ladders often promote based on scope and cross-team influence, encouraging politics. A better system focuses on skill gradients like "truth-seeking." It rewards being right about foundational decisions, not just being loud or well-positioned, which fosters a healthier engineering culture.
When tech giants release low-ambition AI products, it damages their ability to recruit top talent who are drawn to mission-driven projects. This forces companies to significantly increase signing bonuses to compensate for the less inspiring work, turning a product launch misstep into a costly talent acquisition challenge.
The very best engineers optimize for their most precious asset: their time. They are less motivated by competing salary offers and more by the quality of the team, the problem they're solving, and the agency to build something meaningful without becoming a "cog" in a machine.
Layoffs at a leading AI company like Meta are not just a negative signal. They function as a healthy redistribution of talent. Engineers who don't meet Meta's extremely high bar are still elite performers who get quickly absorbed by other companies, accelerating innovation across the broader tech ecosystem.
A Meta engineer was denied a promotion despite a "Greatly Exceeds" rating due to a behavioral gap in cross-functional collaboration. This shows that lagging promotions hinge on consistently demonstrating the behaviors of the next level, not just delivering high impact at the current level.
