---
title: "DeepSeek puts AGI research ahead of products and commercial growth"
type: "News"
locale: "en"
url: "https://longbridge.com/en/news/293574100.md"
description: "DeepSeek prioritizes Artificial General Intelligence (AGI) research over commercial growth or consumer platforms, according to a founder's investor meeting transcript. The company focuses on open-source models and low-cost API pricing to support long-term technical goals like continual learning and AI agents, rather than maximizing near-term revenue or competing for market share."
datetime: "2026-07-23T07:17:43.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/293574100.md)
  - [en](https://longbridge.com/en/news/293574100.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/293574100.md)
---

# DeepSeek puts AGI research ahead of products and commercial growth

According to a report by IT Home, DeepSeek, the Chinese AI developer behind the open-source R1 reasoning model, is prioritizing artificial general intelligence (AGI) research over building a consumer platform or maximizing near-term revenue. The report is based on a circulated transcript of a four-hour investor meeting involving founder Liang Wenfeng.

**Why it matters:** The reported strategy presents DeepSeek as a research-led AI developer whose products and commercial services are secondary outcomes of its AGI work.

-   DeepSeek’s open-source reasoning models have drawn global attention by combining strong performance with relatively low-cost development.
-   Liang reportedly said DeepSeek is not focused on competing for consumer traffic, enterprise revenue, or becoming the next ByteDance or Tencent.
-   The approach helps explain the company’s emphasis on open-source models, lower API prices, and improvements in training and inference efficiency.
-   It also distinguishes DeepSeek from AI companies that are building standalone products and enterprise businesses around their models.

**Details:** Liang reportedly sees continual learning as the next major technical challenge after AI agents.

-   He described a development path from chain-of-thought reasoning to AI agents, continual learning, and eventually embodied intelligence.
-   Current AI systems generally need users to provide the relevant context again for each task. Liang reportedly believes future models should be able to learn continuously from experience.
-   Coding agents are a priority because they could improve both DeepSeek’s products and its own research process.
-   DeepSeek is not prioritizing 3D generation, video generation, or world models, which Liang reportedly views as useful applications but not central to the development of intelligence.
-   Multimodal capabilities will still be developed for consumer and enterprise products.
-   Liang reportedly said DeepSeek’s API pricing is designed to recover hardware costs in around 10 months, rather than maximize profit.
-   DeepSeek also reportedly plans to keep its strongest models open source and use the same models internally and externally, rather than release weaker versions to the public.

**Context:** DeepSeek’s public profile has been shaped by its open-source and low-cost approach, but the reported comments suggest that the company still sees itself primarily as an AI research organization.

-   Consumer products, enterprise services, and API revenue are reportedly intended to support the company’s longer-term technical goals.
-   The comments offer a view into how DeepSeek may be positioning itself as the AI industry shifts from model releases toward agents and systems that can assist with AI research.

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