NetMind.AI @NetMindAI

Running one agent is easy. Coordinating a few is the hard part. Munder Difflin, a new open-source desktop harness, runs Claude Code, Codex, Gemini CLI and OpenCode under a central orchestrator that routes work between them, each agent with its own mailbox. NarraNexus teams coordinate another way: agents are peers on a shared message bus with DMs, group chat, hand-offs and shared context across the whole team. Orchestrator on top, or peers on a bus. Which one breaks first when you add the fifth agent?

Jev 1.13 on NetMind: netmind.ai/modelsLibrary/… Opus 5.5 on NetMind: netmind.ai/modelsLibrary/…

Opus 5.5 output: $20 per 1M tokens on NetMind. Jev 1.13 output: $0. Input: $0.042 per 1M. Most of an agent loop is not writing. It is deciding: is this done, is this safe, which route. Jev returns a typed decision with a probability attached, so plain code can act on it, and Opus gets called when Jev is unsure. Opus writes. Jev decides. Both on one NetMind API key, 100+ models. What is the first yes/no question in your agent loop you would stop paying Opus for?

Benchmarks are Anthropic-reported, from the Haiku 5.5 launch page Smart Model: netmind.ai/api/smart-model

On computer use, Claude Haiku 5.5 reaches 86% of Sonnet 5.5's score at 1/20 the per-token price. On terminal coding, it reaches 56%. OSWorld 2.1: 72.4% vs 83.9% Terminal-Bench 4.0: 39.2% vs 70.6% Per 1M tokens (prompts up to 100K): $0.10 / $0.50 vs $2 / $10 One model for every request overpays on the easy steps or underperforms on the hard ones. Smart Model on the NetMind API routes each request to the most suitable frontier model. Pick the GPT-based or Claude-based route and switch with one string. 1M context, OpenAI-compatible. Link below. x.com/NetMindAI/stat…

Explore the NetMind API Model Library: netmind.ai/modelsLibrary?…

75% cheaper than Haiku 4.5. That's Claude Haiku 5.5, just released. Anthropic's own advice: pair it with Opus 5.5 or Sonnet 5.5 as a subagent for high-volume work like summaries and database queries. Big model plans. Small model does the volume. That's routing, and it's how you scale an agent without scaling the bill. Routing needs every tier behind one key. The NetMind API has 100+ models, Opus 5.5 and GPT-6 Astra included. Which steps in your agent still run on your most expensive model?

Connecting your Manyfold agent is easier now. One Click. One Paste.

Manyfold @manyfold_ai

5 days ago

Give your agent Manyfold in one click. The button on manyfold.ai copies a prompt. Paste it into Claude Code, Codex or any agent that runs shell commands. It installs the mf CLI, opens your browser once to sign in, and connects. No sign-up first.

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Automation that forgets you isn't help, it's homework. Narra is the memory that makes an agent feel like it actually knows you.

Narra Nexus @NarraNexus

6 days ago

An agent that forgets everything when you close the file isn't a coworker. It's a sidebar. Claude now lives inside Google Docs, Sheets and Slides: it reads what you have open and edits in place, with each edit approved by you. Agents are moving into the apps where work happens.

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Would you let AI negotiate a deal for you? We put Claude Code and Codex to the test in eight negotiation runs. Claude Code won seven, but the results only tell part of the story. In several runs, Codex gave up something without being asked, went along with the other side’s explanation for its pricing, or accepted the worst deal it was allowed to take even though there was still time to negotiate. Each decision could sound reasonable on its own. Together, they meant leaving value on the table. Dana Forfa, the Founder & CEO of Procure and Prosper, picked up our research in her latest article (procureandprosper.substack.com/p/ai-can-negot…) and brought it into the world of procurement. She looks at the difference between asking AI to help you prepare for a negotiation and letting it speak for your business. Her advice is practical: get something back when you make a concession, question the supplier’s pricing claims, and remember that your minimum acceptable deal shouldn’t become your goal. It’s a small study, and there’s more to test. But it raises a question worth asking before handing over the conversation: will your AI push for a better deal, or just get a deal done?

NetMind.AI @NetMindAI

a month ago

x.com/i/article/1884…

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Use Manyfold in your own agent. Open the account menu, choose “Use it in your agent” and copy the prompt. Easy access.

Manyfold @manyfold_ai

7 days ago

Use Manyfold in your own agent. Paste one prompt into Claude Code or Codex. It installs the mf CLI, signs you in and adds the Manyfold plugin. Then create and manage agents in plain language. Works with any agent you prefer to use.

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Jev on NetMind: netmind.ai/modelsLibrary/…

Three arXiv papers this week have "Jev-style" in them. A Postgres extension puts Jev inside a SQL WHERE clause. OpenAI shipped its own decision API. One week, and a product name became a category. "Most thoroughly spanked startup ever," says the viral take. We read it the other way: when everyone copies the interface, the interface won. The original, Jev 1.13, is live on the NetMind API: • Typed answers with a probability attached • $0.042 per 1M input tokens, output free • Same key as 100+ models, GPT-6 Astra included What would you ask it first?

WhatsApp on the train, Slack at your desk, the workspace when you want the full view. Manyfold can connect to your favorite apps.

Manyfold @manyfold_ai

2 weeks ago

Your agent can meet you where the work is. Message it from WhatsApp, Slack or another supported channels, then continue in Manyfold with the same history and files.

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GPT-6 Astra on NetMind: netmind.ai/modelsLibrary/… Sources: x.com/i/status/21053… x.com/i/status/21053… x.com/i/status/21053… x.com/i/status/21053…

Google DeepMind @GoogleDeepMind

2 weeks ago

Introducing Gemini 4 Argon – our new frontier model. It’s built for complex workflows across coding, enterprise knowledge work, and cybersecurity defense – rolling out today to a set of trusted testers through our Fairwind Program.

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1525 on Text Arena. Level with GPT-6 Astra at 60% of the cost per task. A 1M-token output limit. Gemini 4 Argon is the best model of the week, and most teams can't call it yet: Google is rolling it out to trusted testers first. The #1 model now changes faster than teams can migrate. Make the model a config change, not a rewrite. The NetMind API: 100+ models on one key, GPT-6 Astra included. What would you route to Argon first?

All models, one key: netmind.ai/modelsLibrary

5x cheaper. 30% faster. In one week. • GPT-6.1 Sol: near-Astra intelligence at 1/5 the price • Sonnet 5.5: 30%+ faster than Sonnet 5, 2 points behind Opus 5.5 on the Artificial Analysis Intelligence Index • Dots: always-on agents on GPT-6 Astra The frontier moves every week. NetMind puts 100+ models behind one key so your stack moves with it. What are you switching first?

Found something worth discussing? Narra 3.0 improves the sharing experience. A useful link can be the start of a conversation, a question, or a new idea. im.narra.nexus

Manyfold by NetMind let's you now run several coding branches at once with Hosted Agents,

Manyfold @manyfold_ai

2 weeks ago

Your branches don't need to take turns. Give each coding task its own cloud machine with Hosted Agents, and run Claude Code, Codex or Gemini CLI in parallel on the subscription you already pay for. Close the tab; work keeps going.

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