Hayden Wolff

Trans af. Currently: Tech Marketing Engineer @nvidia. views are my own. (he/they)

[OpenAI @OpenAI]

Introducing GPT-Live, a new generation of voice models for natural human-AI interaction.

Rolling out in ChatGPT starting today.

You’ll want to turn the sound on for this one.

[Prime Intellect @PrimeIntellect]

Announcing our $130M Series A to build the Open Superintelligence Stack

Led by Radical Ventures, with NVIDIA, Intel Capital, Dell Capital, and existing investors

Train, deploy, and continuously improve your own models using our stack.

Own your intelligence.

[clem 🤗 @ClementDelangue]

👑 of 🇺🇸 Open-source!

[Nous Research @NousResearch]

We have been working closely with @nvidia to ensure Hermes Agent works smoothly on their new @NVIDIARTXSpark superchip and integrates with the new OpenShell runtime, which connects Hermes to @Microsoft's security primitives.

Watch our feature in the big announcement at Computex:

[Ali Spittel @ASpittel]

cron jobs are going through the most epic rebrand

[Harrison Chase @hwchase17]

https://t.co/aZnKZ1SVXB

[Hayden Wolff @HaydenWolff1]

I love these almost as much as i love using langsmith

[Harrison Chase @hwchase17]

LangSmith 🤝Fix your agents

You'll see our billboards around SF and NYC over the next few months.

The themes all point to the same problem: you don't know what your agents will do until you actually run them. What works in demos can break in the real world. Without tracing and evals, you're just guessing at why. Track what your agent actually does. Optimize and fix your agents. Then measure whether your fixes work.

That loop is how agents get better, and LangSmith is built to power that workflow.

If you spot one around, send it our way!

[Claude @claudeai]

Computer use is now in Claude Code.

Claude can open your apps, click through your UI, and test what it built, right from the CLI.

Now in research preview on Pro and Max plans.

[Sudo su @sudoingX]

the concept is right. local models replacing API bills is the future and i've been saying this for months. but the stack recommendation here will frustrate you before you even get started.

openclaw is 120K+ lines of typescript bloat that can't parse tool calls correctly on most local models. i've tested it extensively and have DMs from people whose "broken" models started working instantly after switching harnesses. the model was never the problem. the harness was.

ollama is convenient but it wraps llama.cpp with overhead and worse defaults. if you want real performance compile llama.cpp from source with CUDA. i get 35 tok/s on qwen 27B dense on a single 3090 with 262K context. flat speed, zero degradation. ollama won't really give you that.

the stack that actually works in march 2026 is llama.cpp compiled from source + hermes agent by nousresearch. per-model tool call parsers, fully open source, no corporation behind it mining your thinking, and the fastest growing agent community in local AI right now.

don't let a pretty landing page choose your tools. test them yourself. the receipts are on my timeline.

[Teknium 🪽 @Teknium]

Great article on Hermes' memory system(s)! Check it out

[NVIDIA @nvidia]

https://t.co/8zNQX2OSSF

[Hayden Wolff @HaydenWolff1]

Kinda back on twitter maybe and finally using Openclaw? Hello 👋🏻

[tweet davidson @andyreed]

how it feels to use claude code

[Amy Tam @amytam01]

https://t.co/b9f99xbcMx

[Viv @Vtrivedy10]

https://t.co/NhTTz2UbKt

[Harrison Chase @hwchase17]

https://t.co/neRV1d0sXq

[Hayden Wolff @HaydenWolff1]

https://t.co/GBUdFeAKkS

[Greg Brockman @gdb]

Software development is undergoing a renaissance in front of our eyes.

If you haven't used the tools recently, you likely are underestimating what you're missing. Since December, there's been a step function improvement in what tools like Codex can do. Some great engineers at OpenAI yesterday told me that their job has fundamentally changed since December. Prior to then, they could use Codex for unit tests; now it writes essentially all the code and does a great deal of their operations and debugging. Not everyone has yet made that leap, but it's usually because of factors besides the capability of the model.

Every company faces the same opportunity now, and navigating it well — just like with cloud computing or the Internet — requires careful thought. This post shares how OpenAI is currently approaching retooling our teams towards agentic software development. We're still learning and iterating, but here's how we're thinking about it right now:

As a first step, by March 31st, we're aiming that:

(1) For any technical task, the tool of first resort for humans is interacting with an agent rather than using an editor or terminal.
(2) The default way humans utilize agents is explicitly evaluated as safe, but also productive enough that most workflows do not need additional permissions.

In order to get there, here's what we recommended to the team a few weeks ago:

1. Take the time to try out the tools. The tools do sell themselves — many people have had amazing experiences with 5.2 in Codex, after having churned from codex web a few months ago. But many people are also so busy they haven't had a chance to try Codex yet or got stuck thinking "is there any way it could do X" rather than just trying.
- Designate an "agents captain" for your team — the primary person responsible for thinking about how agents can be brought into the teams' workflow.
- Share experiences or questions in a few designated internal channels
- Take a day for a company-wide Codex hackathon

2. Create skills and AGENTS[.md].
- Create and maintain an AGENTS[.md] for any project you work on; update the AGENTS[.md] whenever the agent does something wrong or struggles with a task.
- Write skills for anything that you get Codex to do, and commit it to the skills directory in a shared repository

3. Inventory and make accessible any internal tools.
- Maintain a list of tools that your team relies on, and make sure someone takes point on making it agent-accessible (such as via a CLI or MCP server).

4. Structure codebases to be agent-first. With the models changing so fast, this is still somewhat untrodden ground, and will require some exploration.
- Write tests which are quick to run, and create high-quality interfaces between components.

5. Say no to slop. Managing AI generated code at scale is an emerging problem, and will require new processes and conventions to keep code quality high
- Ensure that some human is accountable for any code that gets merged. As a code reviewer, maintain at least the same bar as you would for human-written code, and make sure the author understands what they're submitting.

6. Work on basic infra. There's a lot of room for everyone to build basic infrastructure, which can be guided by internal user feedback. The core tools are getting a lot better and more usable, but there's a lot of infrastructure that currently go around the tools, such as observability, tracking not just the committed code but the agent trajectories that led to them, and central management of the tools that agents are able to use.

Overall, adopting tools like Codex is not just a technical but also a deep cultural change, with a lot of downstream implications to figure out. We encourage every manager to drive this with their team, and to think through other action items — for example, per item 5 above, what else can prevent a lot of "functionally-correct but poorly-maintainable code" from creeping into codebases.

[Claude @claudeai]

Ads are coming to AI. But not to Claude. Keep thinking.

[OpenBMB @OpenBMB]

🥳 Introducing MiniCPM-o 4.5
The first full-duplex omni-modal LLM in open-source community 🎬🎙️

🔥 Key Highlights:
• Full-duplex Omni-modal Live Streaming: The model can see, listen, and speak simultaneously in a real-time conversation without mutual blocking
• Proactive Interaction: Moving beyond reactive QA to performing proactive interaction, such as initiating reminders
• Leading Performance: Scoring 77.6 on OpenCompass, it outperforms GPT-4o & Gemini 2.0 Pro in vision-language tasks with 9B params

The best part? You can experience all above on your PC!

#MiniCPM #OpenSource #MultimodalAI #LLM