Claude 4 is the Best Agentic Coding Model

Today’s top AI Highlights:

1. Build and run AI agent workflows as MCP servers

2. Claude 4 with hybrid reasoning, parallel tool use, and improved memory

3. New features in Anthropic API to build powerful AI agents

4. Vercel debuts its first AI model for full-stack web development

5. Vibe build complete n8n workflows with simple prompts

& so much more!

Read time: 3 mins

AI Tutorial

Building tools that truly understand your documents is hard. Most RAG implementations just retrieve similar text chunks without actually reasoning about them, leading to shallow responses. The real solution lies in creating a system that can process documents, search the web when needed, and deliver thoughtful analysis. Moreover, running the pipeline locally would reduce latency and ensure privacy and control over sensitive data.

In this tutorial, we'll build a powerful Local RAG Reasoning Agent that runs entirely on your own machine, with web search fallback when document knowledge is insufficient. You'll be able to choose between multiple state-of-the-art opensource models like Qwen 3, Gemma 3, and DeepSeek R1 to power your system.

This hybrid setup combines document processing, vector search, and web search capabilities to deliver thoughtful, context-aware responses without cloud dependencies.

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Latest Developments

AI Agent Workflows as MCP Servers 🤖📞🤖

Last Mile has just dropped a major update to their mcp-agent framework that flips how we think about AI agents and MCP. Instead of agents just being clients that consume MCP servers, you can now package your agents as MCP servers themselves. This means any MCP-compatible client can invoke, coordinate, and orchestrate your custom agent workflows just like they would with any other tool.

The framework offers two execution modes: a lightweight asyncio implementation for quick development and testing, plus a Temporal-powered option for production workloads that need durability, letting workflows pause, resume, and retry in production environments.

Key Highlights:

1. Agent-to-Agent Communication - Your agents can now be exposed as MCP servers for direct agent-to-agent interaction through the same protocol. This opens up multi-agent ecosystems where a research agent can call a writing agent, which can then invoke a fact-checking agent, all through standardized MCP tool calls.

2. Execution Options - Choose between asyncio for fast, in-memory execution with minimal setup (perfect for development and simpler workflows) or Temporal for production deployments that need pause/resume capabilities, automatic retry logic, and workflow observability. Both modes expose the same MCP interface.

3. Platform-Agnostic - Build your agent workflows once and use them from any MCP client - Claude Desktop, Cursor, VS Code, or your custom applications. The framework provides standardized workflow management tools that work consistently across all MCP clients.

4. Composable Workflow Patterns - All the proven patterns from Anthropic's "Building Effective Agents" are available as composable MCP servers. Whether you need parallel execution, router logic, evaluator-optimizer loops, or orchestrator-worker patterns, you can chain these together and expose the entire workflow as a single MCP tool that other agents or clients can invoke.

Claude 4 Outperforms OpenAI’s Latest SWE Model Codex-1 🏆🧑‍💻

Anthropic released Claude 4 Opus (a new Opus model after almost a year) and Claude 4 Sonnet, setting new standards for coding, advanced reasoning, and AI agents. Claude Opus 4 is the world’s best coding model, and excels in complex, long-running tasks and agent workflows.

Both models are hybrid reasoning models, giving near-instant responses or using extended thinking. They can use tools in parallel, like web search during extended thinking, allowing Claude to alternate between reasoning and tool use to improve responses. Further, the models have been improved in instruction following and memory capabilities, extracting and saving key facts to maintain continuity and build tacit knowledge over time.

Key highlights:

1. Claude 4 Opus - Now the leading coding and reasoning model, outperforming all other models on SWE-bench and Terminal-bench. It excels in complex, long-running tasks that require thousands of steps, with the ability to work continuously for several hours.

2. Claude 4 Sonnet - A significant upgrade to Claude Sonnet 3.7, it delivers superior coding and reasoning with improved instruction-following capabilities. While not matching Opus 4 in most domains (besides coding), it delivers an optimal mix of capability and practicality.

3. Performance Comparison - Both Sonnet and Opus 4 outperform OpenAI’s latest SWE model, Codex-1, on SWE-bench Verified. On other benchmarks, both models match OpenAI’s o3 performance when they use parallel test-time compute.

4. Availability and Pricing - This is probably the best part of the release — the API pricing remains unchanged. Both models have been priced the same as Claude 3 Opus and Claude 3.7 Sonnet. Both models are available for all paid plans on claude.ai. Sonnet 4 is also available on the free plan.

5. Prompting Claude 4 - Since the models now adhere to instructions even more closely, the team has published a prompting guide to help transition your prompts to these new models.

New API Capabilities for Building Powerful Agents ⚡️🤖💡

Anthropic has rolled out four major features to their API that, with the new Claude 4 models, will enable you to build more powerful agentic applications. These include Code execution, MCP connector, Files API, and the ability to cache prompts for up to one hour.

Here are the details:

1. Code Execution - Claude can now run Python code directly in a sandboxed environment within API calls, executing data analysis, generating visualizations, and iterating on results without you having to copy-paste code. You can upload a dataset and get complete analytical insights with charts and statistical analysis in a single API interaction.

2. MCP Connector - The new MCP connector feature enables you to connect to remote MCP servers directly from the API without a separate MCP client. The API handles all connection management, tool discovery, and error handling automatically. Simply add a remote MCP server URL to your API request, and you can immediately access powerful third-party tools

3. File Management - The Files API lets you upload documents once and reference them across multiple conversations without needing to re-upload files for every request. It integrates with the code execution tool so Claude can process your uploaded files and generate outputs like charts directly.

4. Extended Context Caching - Prompt caching now offers a 1-hour time-to-live option (12x longer than the standard 5 minutes), which can reduce costs by up to 90% and latency by up to 85% for applications with long prompts. This makes it economically viable to build agents that maintain extensive context over long workflows.

Quick Bites

Mistral AI has launched Document AI, a full-stack solution for fast and accurate document processing, powered by their best OCR model. It handles everything from scanned PDFs to complex tables and handwritten text, extracting structured data with over 99% accuracy across multiple languages. You can build end-to-end document pipelines - from OCR digitization to natural language querying, with fully automated structuring in between. Priced at $0.001 per page, and speeds of up to 2,000 pages per minute on a single GPU.

Claude Code is now available with new beta extensions for VS Code and JetBrains IDEs. You can get inline code suggestions, track diffs, and use shortcuts to share context or diagnostics, right inside your editor.
You can also integrate Claude Code with your GitHub workflows for automated code review, PR management, and issue triage. With a simple @claude mention in any PR or issue, Claude can analyze your code, create pull requests, implement features, and fix bugs - all while following your project’s standards.

Vercel has launched v0-1.0-md, its first AI model for front-end and full-stack web development. This multimodal model has a 128K context length, supports function calling, and streams fast responses via an OpenAI-compatible API. It's tuned on modern stacks like Next.js, and includes features like auto-fix for common coding issues, inline quick edits, and framework-aware completions.
Currently in beta, it’s available through Vercel’s API, AI Playground, or SDK for Premium and Team users.

xAI API now supports Live Search. Grok can now search through real-time data from 𝕏, the internet, trending news, and more, and consider those in generating responses. Instead of orchestrating web search and LLM tool calls yourself, you can get chat responses with live data directly from the API. FREE in beta for a limited time.

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Tools of the Trade

1. n8nChat: Generate and edit n8n workflows from scratch based on natural language commands. It integrates directly into the n8n editor. Like Cursor but for n8n, it can create, edit, debug, and optimize your workflows.

2. Rork: Vibe code complete, cross-platform mobile apps using AI and React Native, powered by Claude 4. Build one-shot apps that use GPT-4o API, no API keys or docs needed. Before publishing to App Store or Google Play, you can share native app previews with the world before publishing to the App Store.

3. Plast: AI agent that connects to your apps like Notion, Linear, GitHub, and Stripe to read data and take actions directly inside them. It uses MCP to connect to tools, handle authentication, reduce token usage, and speed up task execution across tools.

4. Entelligence: Vibe-coded PRs are not production-ready, often creating more subtle bugs throughout the codebase. Entelligence goes beyond simple AI-powered code review. It understands your entire codebase, not just the lines changed. It flags regressions across files before merge, catches 7x more bugs before production, auto-generates summaries with architecture diagrams, and helps you ship 3x faster with fewer bugs.

5. Awesome LLM Apps: Build awesome LLM apps with RAG, AI agents, MCP, and more to interact with data sources like GitHub, Gmail, PDFs, and YouTube videos, and automate complex work.

Hot Takes

1. I don't know why the narrative is "AI isn't going to take your job."

   Of course it is.

   I'm predicting we'll see at least 4 million layoffs driven by AI over the next 24 months. ~
   GREG ISENBERG

   
   

2. Common Sense!

   If AI could really fix most bugs or write complex applications, we wouldn't all be hiring SWEs at our current pace.

   Yes, we are still hiring!! ~
   Bindu Reddy

That’s all for today! See you tomorrow with more such AI-filled content.

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