Jones E Designs Studio

We build private AI systems for small business and nonprofits — foundational intelligence, integrated private apps. Intelligence layered into your operations.

[OpenRouter @OpenRouter]

Congrats on the launch @olam_labs and @sensho! Excited to support what you’re building and can’t wait to see what’s next.

[Jones E Designs Studio @jonesedesigns]

@NousResearch up & running

[Jones E Designs Studio @jonesedesigns]

@NousResearch What a great idea! I will spin one up now!

[Theo - t3.gg @theo]

Apparently I'm allowed to talk about GPT-5.6 now?

It's a damn good model. Not quite as "smart" as Fable, but it is incredibly capable. Fixed all the problems I had with GPT-5.5.

It is incredibly determined. Will run for a day without even using a /goal. It understands subagents incredibly well and is great at orchestrating. It's super pleasant in use cases like OpenClaw and Hermes Agent. It knows iOS dev incredibly well.

It has rough edges too, but FAR fewer than 5.5 did.

For many things, gpt-5.6-sol will become my obvious default.

I will share a lot more soon 🫡

[Jones E Designs Studio @jonesedesigns]

Launching publicly this Thursday!

Introducing GPT‑5.6 series from @OpenAI :
• Sol, the flagship model.
• Terra, a balanced model for everyday work.
• Luna, a fast and affordable model.

Terra has competitive performance to GPT‑5.5 while being 2x cheaper and Luna brings strong capability at the lowest cost.

In this new naming system introduced with GPT‑5.6, the number identifies a model’s generation, while Sol, Terra, and Luna identify durable capability tiers that can advance on their own cadence. Together, the family gives people and developers clearer choices across intelligence, speed, and cost.

GPT‑5.6 is priced per 1M tokens across three model sizes:

• Sol is $5 input / $30 output.
• Terra is $2.50 input / $15 output.
• Luna is $1 input / $6 output.

Read more at:

https://t.co/bdqqz4mGlF

[Vectorize @Vectorizeio]

Hindsight 0.8.4 is here!

Key updates:

- Multi-LLM Failover & Routing
- Finer Recall Control
- Scheduled Mental-Model Refresh
- Sharper LLM Control & Accounting
- Data-Integrity & Robustness Fixes

[Jones E Designs Studio @jonesedesigns]

A working shop is not built around one perfect tool.

It is built around knowing which tool to use for which job.

That is how I think about AI orchestration for small businesses: not one magic model, but a system that understands the work.

https://t.co/8o7K9pLbG2

[Jones E Designs Studio @jonesedesigns]

https://t.co/Lf8njrjJdk

[NVIDIA @nvidia]

Water usage has been a hot topic in the AI data center world, but the numbers may surprise you.

According to the Manhattan Institute, data centers use 0.2 percent of daily water usage in the U.S. and that number has dramatically decreased in the past few years due to a new method: liquid cooling.

By moving to 45°C liquid cooling, AI factories in favorable climates can use dry coolers instead of conventional cooling-tower-based systems, cutting facility cooling water use from roughly 2.6M gallons per MW per year to near zero.

Liquid cooling enables AI factories to be both water and energy efficient, while creating opportunities for heat reuse and dispersal to local communities, allowing these factories to become energy grid assets.

Learn more below ⬇️

https://t.co/7WanoPNKTR

[Elon Musk @elonmusk]

@jietang @teortaxesTex On benchmarks, yes, but as measured by true usefulness even Q1 would be very impressive.

Anthropic has rightly focused on maximizing useful intelligence, which does not show up in benchmarks, but definitely shows up in revenue.

[Alex Finn @AlexFinn]

I can't believe this is real

I have GLM 5.2 running 100% locally on my Mac Studio. 2 bit quant.

The results I'm getting are better than Opus 4.8

It's now powering my Hermes Agent and Codex. 100% free, local, private super intelligence on my desk

I also have it in a loop coding for me 24/7 now

I thought we were at least a year away from this type of event. It happened today.

The model takes up about 250gb of memory. So you can technically run it on a Mac Studio with 256gb, but you probably want the 512gb memory version (please tell me you listened to me 5 months ago when these were sitting on store shelves)

With Fable gone, I now have Opus 4.8 level intelligence on my desk for free. This is the future.

Local, private, secure, personal super intelligence.

If you're still writing off local AI as a fad or engagement bait, you are officially delusional

[Jones E Designs Studio @jonesedesigns]

@jietang It is working well for me so far! Great work!

[ElevenLabs Developers @ElevenLabsDevs]

Call your Hermes Agent

[Daniel Jeffries @Dan_Jeffries1]

Any arguments against open source and open weights are mendacious and malicious by their very nature.

Open source is the foundation of modern society worth 8.8 trillion to the economy and the foundation of every major cloud, your home router, your phone, your operating system and more.

These anti-open source anti-freedom arguments are especially nasty when they use weaselly hawk coded words like "dual use."

Linux is dual use. So is your operating system. So is your phone. So is your kitchen knife.

Dual use was used against encryption. Once this stupid and spurious restriction was lifted eCommerce took off like a rocket and was worth trillions to society.

Choke points, gates and centralized controls are inherently limiting and benefit the few at the expense of the many. They choke out growth and development in society.

We don't need monks in a cave deciding what books to copy.

We need the printing press.

Anti-open source arguments have no moral ground to stand on. They are inherently self-serving and have no other purpose than to create centrally dominated monopolies and regulatory capture in an underhanded, unscrupulous way.

[Peter Steinberger 🦞 @steipete]

Talked with @durov and Telegram folks offered uncomplicated help, welcome @izhukov as new OpenClaw maintainer!

First action point is to figure out why enabling the bot streaming API sometimes causes message dupes. This will make Telegram support so good!

[sunny madra @sundeep]

“If your $500K engineer isn’t burning at least $250K in tokens, something is wrong.”

[Andrej Karpathy @karpathy]

It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow.

Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes.

As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now.

It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.

[Ralph Fischer @RalphFischer_]

OpenClaw 🦞 just hit #2 OSS on GitHub stars⭐️

React: 243270⭐️
OpenClaw: 218261⭐️
Linux: 218260⭐️
Python: 217970⭐️

3 months in, passed giants like Linux #3 and Python #4. Only React left at #1, and that’s Meta not solo.

Huge congrats @steipete you reached literally the stars of open source and changed the curve on the way.

[Rhys @RhysSullivan]

Is that a claw