James Caudill

Software Engineer that enjoys technology

[Claude @claudeai]

Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use.

Its capabilities exceed those of any model we’ve ever made generally available.

[Boris Cherny @bcherny]

Just landed nested subagent support in Claude Code

Starting to experiment more with agents kicking off agents as a way to better manage context. Capped at depth=5 to start, going out in today’s release.

Lmk what you think!

[James Caudill @jpcaudill]

@MasterTimBlais @SpaceX Hahahah

[James Caudill @jpcaudill]

@MasterTimBlais So awesome. Great post man!

[Mats Engstrom @matseng]

My UNIX V7 port to MMU-less 68000 is coming along nicely. I can now boot into single user mode, then exit out into multiuser to enable more terminals. And then I've ported a 68K C compiler so I can self-compile code inside the UNIX. #HELLORD

[Tib3rius @0xTib3rius]

Happy Birthday Whit Diffie. 🔥

[James Caudill @jpcaudill]

@alphafox Those were the bomb back in the day.

[Boris Cherny @bcherny]

We doubled Claude Cowork usage limits for the next month. This applies to your 5-hr rate limits. If you’ve been saving up a big messy project, now’s the time.

[Claude @claudeai]

We've doubled usage limits in Claude Cowork for the next month.

Delegate bigger, more complex tasks to Claude.

[James Caudill @jpcaudill]

@theo It will be a while before they pay.

[Sawyer Merritt @SawyerMerritt]

SpaceX has just announced that they have entered into a $920 million per month agreement with Google to provide compute capacity, according to a new filing.

"On June 5, 2026, we entered into a Cloud Service Agreement with Google with respect to access to compute capacity. The customer has agreed to pay us $920 million per month from October 2026 through June 2029, with capacity ramping up through September at a reduced fee. The compute capacity provided includes approximately 110,000 NVIDIA GPUs, CPUs, memory, and other related components.

After December 31, 2026, the agreement may be terminated by either party upon 90 days' notice. The customer will retain ownership of, and intellectual property rights in, its content, Al models, and related data."

[James Caudill @jpcaudill]

After installing 2026.14.6.7 on the M3 it is noticeably better.

[Mustafa Suleyman @mustafasuleyman]

It’s time to move from renting intelligence to truly controlling your AI. Microsoft Frontier Tuning lets you take our models and make them uniquely your own, turning them from capable generalists to completely custom partners.

It starts with reinforcement learning environments (RLEs) that allow our models to learn directly from your workflows. Think of them as training gyms for AI. Here the agent learns your very specific processes, your standards, your way of working. It goes from off-the-shelf to hyper-adapted to exactly what you and your teams need. Those adaptations drive efficiency and performance, and your unique models can keep continually learning in your RLEs. This changes the nature of AI – and it changes the impact.

For example, within Microsoft we use our RLEs combined with our MAI models to climb towards the best agentic use cases for Excel. Our MAI tuned model is on par with GPT-5.4 on public and private benchmarks, while being up to 10X more efficient.

Only you control your agents made with Frontier Tuning. You keep the benefits of your hard-earned know-how, data and institutional knowledge. With us, the RLEs and the models you build in them become your moat.

This is distinct. It’s a new era. An era of AI that you control, on your terms. I think it’ll be a good one. More on the blog: https://t.co/v65eop5aHS

[Sundar Pichai @sundarpichai]

Our new Gemma 4 12B model hits a sweet spot between size + performance: it can run locally on a laptop, while enabling powerful multi-step reasoning and agentic workflows. Can’t wait to see what the community does with this one!

[elie @eliebakouch]

microsoft MAI tech report is a gold mine, one of the most transparent for a model at this scale.

this model uses zero synthetic data or distillation from previous models. this means reasoning, agentic behavior, tool use are all learned fully during post-training with no cold start. bold choice that makes it harder and requires more iterations to reach sota, but you get FULL control over your model series and it proves they are serious about being a frontier lab.

the tech report is insanely detailed and precise about numbers. to give an example, they give the exact MFU across all the iterations of the model, with the exact changes etc. they also share the full scaling ladder recipe, to my knowledge this is the first time i've seen this in a tech report at this scale

let's look at all of this in this likely very long thread 🧵

[Peter Steinberger 🦞 @steipete]

Such a privilege to work with Microsoft to bring claws to enterprises!

[Microsoft AI @MicrosoftAI]

Seven new models launching at Build: let’s go!
Reasoning. Code. Image. Transcribe. Voice.

Built from scratch on a clean data lineage, designed for efficiency, working seamlessly as a family of models

Thread 🧵
#MSBuild

[Burke Holland @burkeholland]

Introducing MAI-Code-1-Flash

Microsoft's latest small coding model.

51.2% on SWE-Bench Pro.

Rolling out now to @GitHub Copilot Free, Pro, Pro+ And Max users.

https://t.co/vQTuCTQTnF

[Satya Nadella @satyanadella]

Great to be back at Microsoft Build today. For us, it is not about any one piece of technology or even the platform.

It is about how we can build a frontier intelligence ecosystem together.

Sharing some of our big announcements today ...