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- Build Once and Deploy with Any Agent Framework
Build Once and Deploy with Any Agent Framework
PLUS: Multiple parallel agents in your Terminal, ChatGPT Connectors for Pro users
Shubham Saboo & Gargi Gupta
June 25, 2025
Today’s top AI Highlights:
Build once and deploy across OpenAI, LangChain, and other AI agent frameworks
Vibe code your entire stack with parallel multi-agents in Terminal
Cognition AI just made VM snapshots 200x faster
Opensource AI maintainer agent for GitHub issues
Vibe build, debug, and deploy full-stack apps and software
& so much more!
Read time: 3 mins
AI Tutorial
Legal document analysis is a fascinating and complex domain where a team of legal experts traditionally work together to understand and interpret complex legal materials. Each team member brings their unique specialization - from contract analysts who dissect terms and conditions to strategists who develop comprehensive legal approaches.
But what if we could replicate this collaborative expertise using AI? By having multiple AI agents working together as a coordinated legal team, where just like their human counterparts, each agent specializes in a specific area of legal analysis.
In this tutorial, we'll bring this vision to life by creating a multi-agent AI legal team using OpenAI's GPT-4o, Agno, and Qdrant vector database. You'll build an AI application that mirrors a full-service legal team, where specialized AI agents collaborate just like their human counterparts - researching legal documents, analyzing contracts, and developing legal strategies - all working in concert to provide comprehensive legal insights.
We share hands-on tutorials like this every week, designed to help you stay ahead in the world of AI. If you're serious about leveling up your AI skills and staying ahead of the curve, subscribe now and be the first to access our latest tutorials.
Latest Developments
Your AI agent application just broke because you switched from OpenAI Agents SDK to LangChain, and now you're rewriting half your codebase.
Framework shopping for AI agents should be easier than this.
Mozilla AI has launched any-agent, a Python library that abstracts away the differences between major agent frameworks, letting you run the same agent code on OpenAI's SDK, LangChain, LlamaIndex, Agno, and others.
Instead of learning seven different APIs and dealing with incompatible tool formats, you get one consistent interface that handles framework-specific quirks automatically. Here's where it gets more interesting - it also enables true multi-agent systems where different agents can run on completely different frameworks and still communicate seamlessly through Google's A2A protocol.
Key Highlights:
One API, seven frameworks - Write your agent once and run it on any supported framework by changing a single parameter, eliminating the need to learn multiple APIs or maintain framework-specific codebases.
Multi-agent Architecture - Build sophisticated multi-agent systems where each agent can run on its optimal framework while communicating as peers through the A2A protocol, breaking down framework silos completely.
Tool Format - Use Python callables, MCP servers, and remote A2A agents interchangeably as tools, creating a truly unified ecosystem where framework choice doesn't limit your tool options.
Monitoring - Automatically generates OpenTelemetry traces with the same structure across all frameworks, providing reliable observability and making it easy to compare agent performance between different implementations.
The age of typing code is ending faster than most developers realize.
Your terminal is evolving into something that thinks, codes, and multitasks like your best developer teammate.
Warp 2.0 is the first Agentic Development Environment that’s amazing at coding and any development task you can think of. You tell it what to build, how to build it, and it gets to work, looping you in when needed. It lets you run multiple intelligent agents simultaneously while you focus on higher-level decisions.
Early adopters generated 75 million lines of code with a 95% acceptance rate, while one consulting firm reported a 240% productivity increase by letting developers coordinate multiple agents simultaneously across complex, real-world codebases.
Key Highlights:
Multi-agent orchestration - Run multiple coding agents in parallel with granular control over permissions, autonomy levels, and task management through a dedicated agent dashboard with real-time notifications.
Cross-repository coding - Work across multiple codebases simultaneously within single conversations, enabling complex client-server development workflows that traditional IDE agents can't handle.
Agent performance - Achieves #1 ranking on Terminal-Bench and 71% on SWE-bench Verified while maintaining the rich UX capabilities that CLI agents can't match.
Contextual intelligence - Agents leverage codebase embeddings, MCP servers, and Warp Drive's shared knowledge store to understand your team's conventions and coding patterns automatically.
Developer control framework - Configure agent permissions down to specific commands, decide approval workflows for code diffs, and maintain full transparency with network logs showing exactly what data leaves your machine.
Quick Bites
Opensource maintainers drowning in GitHub issues faster than you can triage them? This intelligent first-level agent support won Mistral AI's $2000 Choice Award at the recent Hugging Face hackathon.
OpenSorus is an AI maintainer agent for GitHub issues that reads incoming issues, indexes your codebase using semantic search, and responds with helpful fixes or suggestions before you even see the notification. Built with Gradio and powered by Mistral's Devstral models, it works as a GitHub app that you can summon with a simple @opensorus mention.
Sometimes the best tools come from pure frustration. When Amazon EC2 snapshots took 30+ minutes, the team behind Devin decided to build their own solution - and ended up creating blockdiff, achieving 200x faster VM snapshots at just a couple of seconds. The opensource tool creates incremental snapshots in milliseconds by operating purely on filesystem metadata rather than copying actual data blocks. It's now powering all of Devin's production workloads and available for anyone dealing with VM management headaches.
ChatGPT connectors for Google Drive, Dropbox, SharePoint, and Box are now available to Pro users in ChatGPT outside of Deep Research. Using these connectors for general queries besides Deep Research is a big unlock for pulling your personal context in real-time from everyday apps.
An AI image model that can spell! Google just released Imagen 4 image model, which addresses the notorious text rendering issues, one of the biggest pain points in current models. The new flagship model comes in two variants: standard Imagen 4 for general use at $0.04 per image, and Imagen 4 Ultra for precision prompt following at $0.06. Both are now live in paid preview through the Gemini API, with limited free testing available in Google AI Studio.
Tools of the Trade
Pythagora: Vibe code with 14 specialized AI agents to build full-stack web applications from simple prompts through planning, coding, debugging, and AWS deployment. It’s a VS Code extension, works with top models from OpenAI and Anthropic.
Zen Agents: Visually build custom AI coding agents tailored to specific frameworks, codebases, and development workflows, deployed across entire engineering teams with centralized configuration and tool integrations.
Wispr Flow: Voice dictation that works in every application. It’s 4x faster, typing at 220 words per minute. Comes with AI-powered auto-editing that cleans filler words and adjusts tone based on the app you're using.
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
AI is likely to be the most monetizable asset in human history ~
Logan KilpatrickAI doesn’t do it end-to-end.
It does it middle-to-middle.
The new bottlenecks are prompting and verifying. ~
That’s all for today! See you tomorrow with more such AI-filled content.
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