The operational pace at xAI is not merely fast; it is fundamentally structured around eliminating temporal and material constraints, driving development at a velocity unmatched in the modern AI ecosystem.
Sulaiman Ghori, an engineer at xAI, offered rare and revealing insights into the unique culture and operational philosophy driving Elon Musk’s newest venture during a recent interview on the Relentless podcast, detailing how the company achieves exponential results by prioritizing foundational physics and radical autonomy over conventional corporate structures.
Ghori’s initial experience illustrates the extreme level of responsibility thrust upon new hires. The expectation is not that of a typical, structured onboarding process, but rather an immediate demand for self-direction and impact. He recounts his first day: “My first day, they just gave me a laptop and a badge. And I was like, okay, now what? I don't even have a team, I have not been told what to do.” This lack of bureaucratic overhead is intentional, designed to instantly filter for engineers capable of identifying and solving problems independently. The result is a highly leveraged environment where competence dictates authority. The most enjoyable aspect of working there, he notes, is that “No one tells me no. If I have a good idea, I can usually go and implement it that same day and show it to Elon or whoever and get an answer.” This culture accelerates decision-making to the speed of thought, bypassing the multi-layered approvals common in established tech giants.
This relentless focus on speed extends directly to the core technical challenges. Ghori emphasizes that xAI’s approach is rooted in first principles, constantly challenging established engineering assumptions. Many perceived limitations in software development, particularly regarding latency and speed, are dismissed as "not true." He posits that much of the existing stack in the broader tech industry contains "a lot of stupid stuff," and by optimizing and eliminating this overhead, engineers can typically achieve a "2x to 8x" performance improvement on almost anything. This dedication to fundamental efficiency is critical because xAI acknowledges that the true bottleneck in achieving Artificial General Intelligence (AGI) is not software complexity, but the physical constraints of computation—namely, energy and hardware availability.
This realization is where xAI's integration with the broader Musk ecosystem provides an almost insurmountable competitive advantage. Ghori details the strategic decision to leverage the computational power of Tesla’s vehicles for running macro hardware simulations. He frames the challenge starkly: “We want 1 million human emulators. We need 1 million computers. How do we do that?” The answer came in utilizing the hardware already deployed globally in Tesla cars. Ghori pointed out that the Tesla car computer is "actually much more capital efficient" than conventional cloud VMs or purchasing standard Nvidia chips. This access to a massive, distributed network of powerful, capital-efficient computers allows xAI to scale its training and simulation efforts in ways competitors relying solely on traditional cloud infrastructure cannot. This ability to integrate and leverage resources across seemingly disparate companies—from datacenter build-outs (Colossus) to autonomous vehicle processors—is the key physical moat protecting xAI's explosive progress.
The pace of iteration resulting from this infrastructure is staggering.
Ghori describes the model development cycle, which often sees new iterations deployed "daily. Sometimes multiple times a day." The financial implications of this speed are profound, calculated based on the immediate value added to the core metric. Ghori jokingly quantified his team’s recent contribution: “We did the math right now, we’re at I think about $2.5 million per commit to the main repo. And I did five today.”
This calculation, however hyperbolic, underscores the mindset: every hour saved translates directly into massive value creation, justifying the intense work rate and the constant pressure to deliver. The entire organization is aligned around rapidly accelerating the core metric, forcing engineers to look past conventional solutions and deliver immediate, high-leverage results. The constant pressure ensures that the team is always focused on the most critical path forward, operating under the principle that if a task can be done faster, there is no acceptable reason for delay.
