AI Native Medhavi Newsletter ·

Claude Fable 5, DeepSeek’s Token Battle, and Gemma 4’s Breakthroughs

Claude Fable 5 Gemma 4 Insights

Claude Fable 5 has launched, showcasing its new capabilities and limitations in the Mythos class, while DeepSeek is making waves in the token battle, increasing its share significantly. Additionally, Gemma 4 12B introduces on-device multimodal workflows, and we explore the hidden costs of agentic software development.

Top News

Tools & Launches

CLI v3.0.23 Released

The Cline CLI v3.0.23 features critical updates like fixes for Vertex AI settings and OAuth management centralized in the SDK.

Cline Changelog

Effective Tokens replaced by AI Credits

In the latest GitHub Agentic Workflows build, Effective Tokens (ET) have been replaced by AI Credits (AIC) as the primary spending metric. AI Credits are now the default cost metric reported in outputs, aligning spend tracking directly to monetary costs...

GitHub Agentic Workflows Blog

Models

Initial Impressions of Claude Fable 5

Claude Fable 5 shows a 25% increase in response relevance over Fable 4, featuring better context handling across longer conversations.

Simon Willison

Introducing North Mini Code by Cohere

Cohere's North Mini Code model offers reduced latency and higher accuracy for code generation tasks, supporting various programming languages.

Hugging Face Blog

llm 0.32a3

The article discusses the release of version 0.32a3 of an unspecified LLM, detailing new features and improvements made since the previous version. It highlights a reduction in model size by 15% while maintaining performance benchmarks across multiple standard datasets. The...

Simon Willison

The Open Source Community is backing OpenEnv for Agentic RL

The article discusses the OpenEnv framework, which has received backing from the open source community for its potential in agentic reinforcement learning (RL). OpenEnv aims to simplify the development of autonomous agents by providing a comprehensive environment for testing and...

Hugging Face Blog

Agents

ICYMI: Inside the Microsoft Agent Framework: How we designed a layered SDK

The Microsoft Agent Framework (MAF) provides developers with building blocks to create advanced agentic applications that integrate large language models, tools, and orchestration. It is organized around three core concepts: agent loops for execution patterns, structured workflows for multi-agent processes...

Microsoft Agent Framework Blog

Build an agentic incident triage assistant with Amazon Quick and New Relic

The article outlines the development of a custom incident triage assistant using Amazon Quick and New Relic, which helps site reliability engineers (SREs) coordinate investigations through integrated tools. This assistant significantly reduced the evidence-gathering phase of incident triage, leading to...

AWS AI Blog

Paving the way for agents in biology

The article from Anthropic Research discusses their efforts in developing agents for biological applications, emphasizing the impact these agents could have on biological research and applications. A specific focus is placed on the adaptability of these agents in various biological...

Anthropic Research

Worth Reading

Recursive Self-Improvement: The latest from Anthropic

Anthropic's latest analysis on Recursive Self-Improvement (RSI) showcases its engineering potential for AI systems to enhance their own development cycles. The usability of AI tools has reportedly increased, with Claude-authored code rising from low single digits before the Claude Code's...

Agentic AI

What Codex unlocks for Notion

In the latest update, Notion has integrated OpenAI's Codex to enhance its platform, allowing users to generate specifications in one go and implement AI Voice Input for the web. This integration aims to significantly increase productivity by enabling engineering teams...

OpenAI Blog

How LLMs work

The article provides a comprehensive overview of how large language models (LLMs) function, detailing their architecture and training processes. It explains that LLMs are based on transformer architectures and typically trained on vast datasets consisting of billions of tokens. Specific...

HN: AI Coding