In a conference room that feels more like a clinical lab than a place of innovation, Masati Sajady speaks with quiet certainty. His demeanor is calm, but what he says is anything but conventional.
“We’ve just completed our 10,000th real-world application,” he explains. “We’ve seen measurable biological changes, reversals of degenerative conditions, gains in cognitive performance, increased physical resilience. No pharmaceuticals. No surgeries. Just frequency-based recalibration.” It sounds improbable. And that’s exactly the point.
Sajady is the founder of The XI Code, a bold venture that claims to unlock and apply a new layer of biology, one driven by coherence, resonance, and synchronization. And now, after over a decade of work, XI is in the spotlight with its submission to the XPRIZE. The goal is validation on a global stage, and what they got instead was resistance.
More Than Placebo or Just Another One?
Despite providing over 100 case studies and a staggering number of real-world sessions, XI’s submission was met with skepticism from the XPRIZE review panel.
The concern was familiar, if disappointing: “We’d need to see a clear delineation between XI’s biological effects and placebo or sham treatments,” says Sajady. To many scientists, this is a fair challenge. But to him, it reveals a fundamental blind spot in how modern science understands change and what it chooses to measure.
“Placebo isn’t an error in the data,” he argues. “It’s the data we should be most curious about. The fact that belief, expectation, and perception can trigger measurable biological outcomes should be a front-row topic in science, not a footnote.”
He points out that many accepted medical treatments do not fare much better under scrutiny. A 2024 meta-analysis published in Frontiers in Psychiatry found that placebo responses account for approximately 62–82% of the treatment response in randomized controlled trials (RCTs) of oral antidepressants. This indicates that a significant portion of the observed benefits from antidepressants in clinical trials may be due to placebo effects.
“And yet,” Sajady says, “those treatments are accepted because they fit the model. Our results don’t fit the model, so we’re told they can’t be real.”
A System That Doesn’t Want to See It
XI Meta Science works with what Sajady calls “time-coded frequencies,” precisely calibrated patterns that interact with the body’s natural rhythms. The idea is to restore coherence across multiple systems: neurological, hormonal, muscular, and even cognitive.
It might sound speculative, but Sajady points to metrics: telomere lengthening, inflammation reduction, muscle gain, and visible shifts in physical vitality. These are not imagined outcomes, they are tracked, logged, and consistent across thousands of sessions.
What’s most striking, however, is that these results were achieved in uncontrolled environments. Real people, living real lives with no sterile lab conditions, no artificial constraints. “We’re not interested in outcomes that only work in a vacuum,” Sajady says. “If a system only holds up under ideal conditions, then it’s not a robust system. We’ve tested XI in the wild, and it still works.”
The Problem Isn’t the Data, It’s the Frame
The resistance Sajady encounters isn’t unfamiliar. He compares it to historical patterns of dismissal and delay, think Semmelweis, Tesla, or the first pioneers of personal computing.
“The pattern is always the same,” he explains. “When new discoveries challenge entrenched systems, they’re first ignored, then ridiculed, then finally accepted after the old guard retires.”
In Sajady’s view, science has become less about exploration and more about self-preservation. “Experts tie their identities to their frameworks,” he says. “So when something new threatens those frameworks, it’s not just intellectual rather existential.”
His frustration isn’t with skepticism. It’s with how that skepticism is applied. “We’re held to standards that conventional treatments often fail to meet. But because those treatments speak the language the system understands, they’re allowed through.”
When Tools Limit Vision
Perhaps the most biting criticism Sajady offers is this: it’s not that XI is impossible to detect, it’s that current instruments are too crude to measure it. “Trying to evaluate our work using existing tools is like trying to detect Wi-Fi with a stethoscope,” he says. “You’re not going to get the signal, not because it isn’t there, but because you’re using the wrong equipment.”
He believes the placebo debate is a distraction. “It’s not about proving we’re more effective than placebo,” he says. “It’s about recognizing that placebo itself is a biological phenomenon worth understanding.”
When Bold Thinking Becomes a Liability
The irony of the XPRIZE committee’s reaction is not lost on Sajady. He references one of the competition’s foundational principles, attributed to founder Peter Diamandis: “The day before something is a breakthrough, it’s a crazy idea.”
“If that’s the spirit behind XPRIZE,” Sajady says, “then rejecting XI because it looks unfamiliar is rather hypocritical. You don’t get to brand yourself as a home for moonshots and then penalize people for bringing one.” He isn’t asking for blind belief. But he is asking for integrity in how new ideas are evaluated.
Redefining What Science Means
There’s no shortage of critics who say XI needs traditional trials, peer-reviewed journals, and mechanistic explanations. Sajady acknowledges the need for rigor, but argues that science must evolve alongside the phenomena it studies.
“We’re not anti-science,” he says. “We’re calling for science to grow. To become a framework that can accommodate what it doesn’t yet understand, instead of discarding it.” In his mind, XI doesn’t stand outside of science. It stands just one layer deeper than science currently dares to look.
10,000 Reasons to Look Again
Sajady leaves the interview with a final thought. “If your tools can’t tell the difference between a sham and a breakthrough,” he says, “maybe the tools are the problem.”
He doesn’t leave with a theory. He leaves with ten thousand data points. Ten thousand outcomes. Ten thousand lives touched, not inside a lab, but in the world we actually live in.
Whether science is ready to see it? That’s the real test.
