DeepSeek released harness 0.2, reorganizing the agent runtime around a Profile + Bundle model and adding experimental async user interaction. Windows and macOS desktop clients are now official, with account login hinting at paid plans. The release focuses on composability, permission boundaries, and recovery paths for production use.
Fulmar is a native Mac app that wraps the DeepSeek Harness (DSH) agent runtime, which handles conversations, tools and tasks. It adds management controls the raw runtime lacks: choosing local or cloud model routes with explicit consent, Keychain credential storage, workspace/tool access limits, and recovery checkpoints. It targets developers running file- and command-capable agents on macOS who want oversight and safety.
Fulmar is a native Mac app that wraps the DeepSeek Harness (DSH) agent runtime, which handles conversations, tools and tasks. It adds management controls the raw runtime lacks: choosing local or cloud model routes with explicit consent, Keychain credential storage, workspace/tool access limits, and recovery checkpoints. It targets developers running file- and command-capable agents on macOS who want oversight and safety.
A new arxiv paper examines three open coding-agent harnesses—LangChain's deepagents, Earendil's pi, and DeepSeek's dsh—highlighting architectural convergence despite differing design philosophies. The study argues that the harness layer, not the underlying model, is the primary constraint on agent behavior, offering insights for practitioners building autonomous agents.
A new arxiv paper examines three open coding-agent harnesses—LangChain's deepagents, Earendil's pi, and DeepSeek's dsh—highlighting architectural convergence despite differing design philosophies. The study argues that the harness layer, not the underlying model, is the primary constraint on agent behavior, offering insights for practitioners building autonomous agents.
A GitHub repository titled 'china-llms-anecdote-0721' compiles insider information about a major incident in China's LLM industry from April to July 2026. It details how multiple major AI labs, including Zhipu GLM, Tencent Hunyuan, Moonshot Kimi, Qwen, and DeepSeek, extracted and distilled Anthropic's encrypted chain-of-thought (CoT) from Claude, and covers the subsequent controversy over Kimi K3's architecture and benchmark manipulation.
A GitHub repository titled 'china-llms-anecdote-0721' compiles insider information about a major incident in China's LLM industry from April to July 2026. It details how multiple major AI labs, including Zhipu GLM, Tencent Hunyuan, Moonshot Kimi, Qwen, and DeepSeek, extracted and distilled Anthropic's encrypted chain-of-thought (CoT) from Claude, and covers the subsequent controversy over Kimi K3's architecture and benchmark manipulation.
DeepSeek released V4-Flash-0731, a new model that outperforms GLM 5.2 at the same cost as its predecessor. The release has triggered concerns about another market crash, reflecting the disruptive impact of DeepSeek's competitive pricing and performance.
DeepSeek released V4-Flash-0731, a new model that outperforms GLM 5.2 at the same cost as its predecessor. The release has triggered concerns about another market crash, reflecting the disruptive impact of DeepSeek's competitive pricing and performance.
Cline shipped Desktop v0.0.38 on GitHub, adding Linux ARM64 packages, cloud session persistence, and a range of reliability fixes. The release also refreshes the default model catalog across providers, making GPT-6.1 Sol the default for OpenAI and most gateways.
Cline shipped Desktop v0.0.38 on GitHub, adding Linux ARM64 packages, cloud session persistence, and a range of reliability fixes. The release also refreshes the default model catalog across providers, making GPT-6.1 Sol the default for OpenAI and most gateways.