Why Management No Longer Wins in the AI Era: Cognition, Vision, and Technology Take the Lead

AI Progress Speed Creates a New Landscape

Professor Tang Jie observes that AI breakthroughs now occur within days rather than years, turning technology cycles into a high‑density, high‑intensity stream. This rapid turnover makes the old model of waiting for a milestone paper obsolete; new methods, papers, and training paradigms flash across platforms, are reproduced by the community, and quickly become industry expectations.

“Many people think a company’s success used to rely on management, and that was true, but in the AI era everything changes—end‑to‑end, flat, and middle‑layer‑less.” Too many things are AI‑enabled; the anxiety is that technology must not fall behind, so engineers suddenly gain more influence than managers. “Management is still useful, but if you don’t understand the technology or AI workflow, you don’t know what to manage.”

Because AI now handles information processing, code assistance, solution generation, and workflow collaboration, many traditional coordination steps disappear. Managers who cannot see where problems arise may see their tools fail or become ineffective.

Technology’s Weight Rises

Tang notes that the density and intensity of AI‑driven technical progress surpass any previous era. A single technical cycle that once took years now unfolds in days, with new methods and training paradigms spreading worldwide almost instantly. Consequently, falling behind is no longer a gradual slide but an overnight shift, raising the strategic importance of technology to unprecedented levels.

He warns that a product that looks strong today can become a basic feature tomorrow after a model update, leaving little time for incremental improvement.

Vision Outpaces Technology

Beyond technology, Tang places "vision" (or "strategic outlook") ahead of technical execution. He argues that a large vision sets the ceiling for an individual’s potential, while a small vision limits achievement. In the AI era, imagination and strategic positioning become crucial: bold, high‑level planning is needed because the window for copying competitors has vanished.

“Vision size has always measured a person’s ceiling. A big vision doesn’t guarantee success, but a small vision guarantees failure.” In AI, you must seize the main contradiction and layout boldly; there is no longer a safe “wait‑and‑copy” strategy.

He contrasts past eras—20 years ago, success hinged on business models; 10 years ago, on product design—and asserts that the AI era is driven by rapidly evolving model capabilities, making both business model and product secondary to continual technical advancement.

Cognition Is the Real Ceiling

Tang ranks cognition above vision, technology, and management. He claims that only those who can quickly iterate knowledge, raise their understanding, and translate judgment into technical action will thrive.

“AI’s rapid progress shows that the core is technology, but the ultimate ceiling is cognition.” “AI may overturn many people’s perception: while many love ML and CS for elegant theory, AGI demands a more native, beyond‑CS level of mathematical reasoning.” “CS credentials no longer guarantee relevance; AI flattens the field, and only those with forward‑looking cognition survive.”

He notes that AI’s mathematical derivation, code generation, and research‑assistant capabilities are now challenging programmers and researchers themselves, eroding traditional safeguards such as degrees, titles, and experience.

One More Thing

Finally, Tang shares three additional insights he posted in May (links omitted for brevity), reinforcing the hierarchy: cognition > vision > technology > management.