❯ ByteDance Reorganizes Seed Foundation-Model Team, Creating Four First-Tier Departments Pointing to Ultra-Large Model

REORGSeed, ByteDance’s AI research unit, completed another round of organizational restructuring last week, according to LatePost, creating four first-tier departments in the foundation-model track, all reporting to Wu Yonghui. The move is widely read as paving the way for training an ultra-large-scale model.

SPLITThe restructuring cuts horizontally by function, merging scattered teams: the pre-training data department (head: Li Chenggang) folded in the data teams previously dispersed across text, coding, visual understanding, and speech, taking unified responsibility for the multimodal data of the new Omni model; Horizon RL (head: Tang Shengyu) consolidates the post-training, inference, and visual-understanding teams, focusing on reinforcement learning to raise the ceiling of foundational intelligence; the product post-training department (head: Qin Yujia) serves enterprise customers, handling integrated agent-model releases and office-scenario optimization.

REVIEW RELIEFEven before this round, ByteDance had been loosening the reins on research: in February 2023, OKRs moved from a two-month to a quarterly cycle; in early 2025, the Seed Edge research unit was fully exempted from quarterly reviews. A company known for high-frequency reviews is now dismantling that cadence of its own accord.

CULTURE TESTByteDance is good at solving problems that are already defined, and bad at betting on directions that are not — a view shared by many former Seed members. Seedance proved it can take a clear goal and execute it to the highest standard; the language model is the second question on the exam. Org form is easy to change; patience is not — frontier training offers no intermediate feedback, and this company’s operating system is used to cutting whatever fails to converge. Whether the four new departments can retain people will depend on whether this architecture can afford them room to fail.

▪ SIGNALLengthening the review cycle is easy; making “keep investing even when results don’t show” an instinct is hard — that is the real problem this reorganization has to solve.