Meet the Token Saver: An Open Source MCP Extension Using Local Hybrid RAG to Reduce Token Costs Claude PDF 90-99%

Meet the Token Saver: An Open Source MCP Extension Using Local Hybrid RAG to Reduce Token Costs Claude PDF 90-99%

AI developers, researchers, and experts often hit a frustrating wall when analyzing large documents with LLMs: the hidden, integrated costs of context windows. Attaching a 200-page PDF to a thread is not a one-time charge. Because the conversation history is resubmitted to the model every time, that large document is repaid with every follow-up query. … Read more

Prompt Engineering vs Loop Engineering vs Graph Engineering: What Are the Differences in Each Layer

Prompt Engineering vs Loop Engineering vs Graph Engineering: What Are the Differences in Each Layer

Three terms now compete along the same lines in AI engineering job descriptions. Fast engineering is the default. Loop engineering entered the AI ​​vocabulary in late 2025 and dominated engineering conversation until June 2026. Graph engineering followed about six weeks later. They are used interchangeably. Should they be? The three are not competing methods. There … Read more

Liquid AI Releases LFM2.5-Encoder-230M and LFM2.5-Encoder-350M: CPU-Fast Bidirectional Encoders for 8K Content

Liquid AI Releases LFM2.5-Encoder-230M and LFM2.5-Encoder-350M: CPU-Fast Bidirectional Encoders for 8K Content

Liquid AI has released two open source bidirectional encoders, the LFM2.5-Encoder-230M and the LFM2.5-Encoder-350M. Both are latent language models built on a hybrid LFM2 core. Both hold a core of 8,192 tokens. Encoders live under separators, purpose routers, security filters, and PII finders. Those tasks run continuously, often without the GPU, and are increasingly long-term … Read more

Building Agentic Seamless Code Workflows with Kimi’s Moonshot AI CLI, JSONL Streaming, Testing, and Session Memory

Building Agentic Seamless Code Workflows with Kimi’s Moonshot AI CLI, JSONL Streaming, Testing, and Session Memory

In this lesson, we prepare and work For me CLI as a fully interactive AI code agent. We include the CLI via uv with a separate Python 3.13 environment, configure Moonshot API authentication with a TOML-based provider and model definition, and create a reusable Python wrapper for executing non-interactive CLI commands. We then use Kimi … Read more

Microsoft AI Releases MAI-Cyber-1-Flash: 5B-Active-Parameter Cyber ​​Model Pushes MDASH to 95.95% in CyberGym

Microsoft AI Releases MAI-Cyber-1-Flash: 5B-Active-Parameter Cyber ​​Model Pushes MDASH to 95.95% in CyberGym

Microsoft AI has released the MAI-Cyber-1-Flash, its first model specifically designed for cyber defense. The model does not run as a standalone storage. It runs inside MDASHMicrosoft scan harness for many models. MAI-Cyber-1-Flash is a converter capable of self-attention and minimal Mixture-of-Experts layers. It carries 137B is the number of parameters with 5B in effectand … Read more

Kimi AI and kvcache-ai Open Source ‘AgentENV’: A Distributed System Enabling Agentic Reinforcement Training (RL) in Kimi K3

Kimi AI and kvcache-ai Open Source ‘AgentENV’: A Distributed System Enabling Agentic Reinforcement Training (RL) in Kimi K3

Kimi’s Moonshot AI team and kvcache-ai are open source AgentENV (AENV)a distributed platform for operating agent environments at scale. AgentENV enables agentic reinforcement (RL) training for For me K32.8-trillion-Mixture-of-Experts Moonshot model. The code goes under MIT License. Why Environment Infra Holds Agentic RL Agentic RL is not just a sample script. It requires the model … Read more

Perplexity Releases pplx, a Single-Binary CLI That Deploys Its Search API to Terminal Coding Agents

Perplexity Releases pplx, a Single-Binary CLI That Deploys Its Search API to Terminal Coding Agents

Confusion is released pplxthe official command-line client for its Search API. The tool returns the base search results and the extracted page text, all as JSON. According to its documentation, it targets humans and coding agents alike. It is not a chat client. There is no chat mode, no model selection and no integrated feedback. … Read more

KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Code Model Trained on 100,000+ Verified Locations

KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Code Model Trained on 100,000+ Verified Locations

The KwaiKAT team at Kuaishou has introduced KAT-Coder-V2.5. It’s a code model that’s trained to run inside real, executable repositories rather than a single-turn code release. The given model is available through StreamLake. An open source variant, KAT-Coder-V2.5-Dev, was released separately from Hugging Face under Apache-2.0. AutoBuilder: environments that use target tests The study puts … Read more