Meta Is Firing Anyone Who Doesn't Use AI

This episode of Marketing School dives into Meta's aggressive AI adoption strategy, where 65% of engineers are now required to use AI for 75% of their code by mid-2026, with performance reviews tied directly to AI usage. The hosts debate whether AI-driven layoffs are truly about efficiency or masking overhiring from the pandemic era and low-interest-rate years. While coding is seen as a 'black and white' domain where AI's impact is verifiable, marketing remains more subjective—especially when measuring top-of-funnel engagement versus actual revenue. A real-world example shows a company seeing 7–8x more engagement from AI-generated social content, but no revenue lift, highlighting the danger of focusing only on vanity metrics. The hosts stress that AI’s real value lies in driving measurable business outcomes—like optimizing conversion rates across global markets by analyzing payment processor performance per country, leading to potential 4%+ revenue gains. They also discuss the rise of AI agents, API-first tools, and the shift from prioritization to 'Monte Carlo-style' experimentation, where companies test everything and let users decide what works. However, they caution that without sufficient traffic or distribution, even the most advanced AI experimentation fails. Finally, they emphasize that AI’s true power in marketing comes from combining it with data-driven decision-making, incrementality testing, and media mix modeling—tools now made accessible to smaller businesses thanks to AI.