Mike Taylor is the CEO & Co-Founder of Rally. He previously co-founded a 50-person growth marketing agency called Ladder, created marketing & AI courses on LinkedIn, Vexpower, and Udemy taken by over 450,000 people, and published a book with O’Reilly on prompt engineering.
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Most founders guess their pricing using intuition or competitor benchmarks, unknowingly leaving massive revenue on the table or scaring away customers. Rally uses AI to make professional-grade Van Westendorp pricing analysis accessible for just $50, helping startups price smarter, faster, and without the $5,000+ cost of traditional market research.
Optimizing AI models to reduce political bias can also reduce other forms of systemic bias, making responses more aligned with real-world distributions across domains like climate, education, and energy. This cross-domain correction suggests that even targeted optimizations, when properly applied, can generalize to improve overall model realism and reduce misleading consensus in AI outputs.
To predict the future, we must track what people actually do and the job they urgently need done.
When your proposed change to the homepage CTA sparks hesitation, you can lean on synthetic research using AI personas to validate the idea quickly and without risk, even without the traffic for traditional A/B testing.
Reconstructing personas solely from aggregate statistics can mash together incompatible traits—what we call the “Dutch Chris” problem—causing synthetic research to hallucinate unrealistic individuals and skew insights. You can combat this by using LLMs’ real-world knowledge of trait correlations as scaffolding and an iterative calibration process, raising the fidelity of virtual audiences toward the 70–80% accuracy needed for reliable, cost-effective studies.
AI has decimated traditional entry-level roles, leaving recent graduates stranded without a foothold in the job market. But by using advanced simulations to replicate real-world challenges, we can create new pathways for skill-building and hiring—restoring opportunity in a workforce increasingly shaped by automation.
AI market research often mirrors human biases, replicating stated intentions rather than actual behaviors. However, by carefully selecting and calibrating AI models, synthetic research can bridge the critical gap between what consumers say they'll do and their real-world actions.
Tim Ferriss turned a rejected book title into a data-driven naming experiment that birthed “The 4-Hour Workweek.” and sold millions of copies world wide. Today, AI persona testing lets anyone speed-run that same market-validation magic for pennies.
Left unchecked, large language models can massively distort reality. Our baseline simulation showed 90.6% of AI personas voting Democrat, a 40-point deviation from expected. But with DSPy optimization, we achieved near-perfect political balance, proving that prompt calibration isn’t optional, it’s essential.
