OpenAI ChatGPT Agents vs Manus AI

Today’s top AI Highlights:

1. ChatGPT Agent is Operator + Deep Research + Virtual Computer

2. Opensource multi-agent teams with transparent reasoning

3. Reduce your vector storage bills by up to 90%

4. xAI is paying nearly $0.5 million for building the anime of your dreams

5. Run a bunch of Claude Codes in parallel

& so much more!

Read time: 3 mins

AI Tutorial

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Latest Developments

ChatGPT Agent is Operator + Deep Research + Virtual Computer 🌐💡🖥️

Just when Manus AI and Genspark seemed to have the autonomous agent space figured out, OpenAI enters with a general-purpose AI agent with the same ChatGPT interface but more intelligence.

ChatGPT Agent simply turns your existing ChatGPT into a computer-operating AI that can handle anything from web interaction to analysis and automation.

This agent brings together the web browsing power of Operator, the research depth of Deep Research, and ChatGPT's conversational intelligence into one coherent agent that has its own computer to carry out your tasks completely autonomously. Connect ChatGPT to your apps like Gmail and GitHub so it can find information relevant to your prompts and use them in its responses - all while keeping you in the driver's seat.

Key Highlights:

1. Task Execution - ChatGPT Agent can handle complex workflows from start to finish, like deep research with reasoning, creating slide decks, planning and executing web tasks, creating spreadsheets, executing code, and more. You can chain multiple tasks in one prompt, and it seamlessly switches between the necessary tools to complete them.

2. Virtual Computer and Tools - The agent has its own virtual environment that combines a visual browser for human-designed interfaces, a text-based browser for reasoning-heavy queries, code execution, and direct API calls.

3. Benchmark Performance - ChatGPT Agent achieves a breakthrough 41.6 score on Humanity's Last Exam, reaching 44.4 when using parallel rollouts (similar to the recent SOTA Grok 4 Heavy on HLE), and impressive accuracy in really tough benchmarks like FrontierMath and SpreadSheet.

4. Control and Collaboration - You maintain full oversight with explicit permission requests before consequential actions, active supervision requirements for critical tasks like sending emails, the ability to interrupt and redirect tasks while preserving progress, and secure browser takeover mode where your inputs remain completely private during auth sessions.

5. Availability - Pro users get immediate access with 400 monthly messages, Plus and Team users receive access over the next few days with 40 monthly messages, and Enterprise and Education users get access in the coming weeks.

Here’s the reality though: Manus AI and Genspark are currently way ahead of OpenAI ChatGPT Agent in terms of output quality and features. However, OpenAI has an advantage - not technical but of trust and accessibility. ChatGPT will be rolling out to millions of existing Plus users who already rely on the platform daily.

Multi-Agent Teams With Next-Level Visibility 🔎 👀

Emad Mostaque’s last venture, Intellient Internet, is on a mission to create opensource AI infrastructure that collaborates with humans and not displaces them.

What better than a system that you can truly see, steer, and trust?

The team has released Common Ground, a framework to build multi-agent teams with transparent reasoning, where you know what's happening under the hood. You get full visibility into how AI agents think, plan, and execute complex tasks through real-time visualizations that show exactly what's happening and why.

Common Ground uses a Partner-Principal-Associate architecture that works like an elite consulting team. Every decision, tool call, and handoff between agents is visible through Flow, Kanban, and Timeline views.

Key Highlights:

1. Professional team simulation - Partners handle strategy and user interaction, Principals break down plans and manage execution, while Associates specialize in domains like code analysis or web research.

2. Workflow transparency - Provides 3 different visualization modes that show exactly how agents make decisions, use tools, and collaborate.

3. No-code agent customization - Define complex agent behaviors, prompts, and tool access through simple YAML files, making it easy to experiment with different team configurations.

4. Local-first with persistent memory - Runs entirely on your machine with free Google CLI, storing every run locally so past work becomes reusable intelligence for future tasks.

5. Unified Tooling - Easily integrate custom Python tools or external APIs via MCP. All capabilities are treated as standardized tools that any agent can use.

Quick Bites

Anthropic has launched a dedicated financial services package that gives Claude direct access to live market data from FactSet, Morningstar, PitchBook, and other major providers, for financial tasks like querying live data, analyzing earnings calls, building Excel models, and generating institutional-quality research reports.

Amazon just made vector storage ridiculously cheap with S3 Vectors, a purpose-built, durable vector storage solution that can reduce the total cost of uploading, storing, and querying vectors by up to 90%. It is the first cloud object store with native support for storing large vector datasets. It introduces vector buckets with native APIs that can handle tens of millions of vectors per index, automatically optimizing storage as your data scales.

Forget alignment research. xAI is hiring engineers at $440k to build AI waifus, complete with characters like goth girl Ani and "homicidal red panda" Bad Rudy. The company says this advances their mission to "understand the universe," and honestly, they might not be wrong about understanding human nature.

Tools of the Trade

1. Conductor: Mac app that runs multiple Claude Code instances simultaneously, each working in isolated git worktrees. You can assign different tasks to multiple Claude agents and monitor their progress in parallel workspaces.

2. Autotab: A general AI agent that both learns and works like a human. Show it how to perform your task, train it to be hallucination-proof by adding examples and providing feedback, and then run it on demand or on a schedule, in a secure, local browser.

3. VoltOps: A framework-agnostic LLM observability platform that provides visual monitoring and debugging for AI agents through interactive flowcharts instead of just text logs. It tracks agent decision-making processes, tool executions, and multi-step workflows in real-time.

4. 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. Cursor isn't leading anymore.

   Claude Code and Gemini Code are, in my opinion, ahead of everyone else.

   Windsurf is dead, and VSCode Copilot is too far behind. ~

   Santiago
   
   

2. Real reason they are scaling to million+ GPU clusters isn't to train super giant parallelised models, maybe need 100k max for a top model
   Real reason is to replace the digital workforce & have the compute to compete to do so

   ach GPU = 10+ workers replacement units 🙁 ~
   Emad Mostaque

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

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