Mark

Founder @ lamigo - Building the context layer for AI revenue agents.

[Nous Research @NousResearch]

The strongest models are gated and access is granted only to a select few.

Hermes Agent now exposes MoA presets as virtual models, giving you capabilities beyond the publicly available frontier: 8% higher than Opus 4.8 and 11% higher than GPT 5.5 on our upcoming benchmark.

[Mark @ThisisMarkT]

Big leap if it’s true. Could be just hype. I’ve been working on a similar solution for our startup so can’t wait to try this @tricalt

[Vasilije @tricalt]

Introducing Cognee v1.0: a major breakthrough in agentic intelligence.

It is 145% better than Opus 4.8 and GPT 5.5 at long context memory retrieval.

Cognee allows a 100 BILLION token context window 100,000x more than Claude. It's:

- 6.9x cheaper than GPT 5.5 and Opus 4.8
- Cold starts in 350ms & searches in 260ms

Why this matters:

Today agents forget important context, redo tasks, waste tokens, and slow down as workflows get more complex.

Cognee solves this.

It’s not a place to build agents. It connects to the agents you’ve already built, across any platform, and makes them significantly cheaper, faster, and more accurate.

Here's how it works:

[leo 🐾 @synthwavedd]

🚨 Exclusive GPT-5.6 scoop:

- Today 5.6 launched for OpenAI enterprise partners for testing ahead of the wider launch
- ETA for wider launch is the 2nd week of July
- There will be NO pricing changes
- A new "max" reasoning effort will be introduced for the 5.6 series
- The model is less token efficient than 5.5

[Ornith @ornith_]

Aloha! 🌺 Meet Ornith-1.0, a family of open-source LLMs specialized for agentic coding.

Ornith-1.0 spans the full parameter sizes including 9B Dense, 31B Dense, 35B MoE, and 397B MoE. It achieves state-of-the-art performance among open-source models of comparable size on coding benchmarks including:
✅Terminal-Bench 2.1(77.5)
✅SWE-Bench(82.4 on verified, 62.2 on pro, 78.9 on Multilingual)
✅NL2Repo(48.2)
✅SWE Atlas(41.2 on QnA, 42.6 RF, 39.1 TW)
✅ClawEval(77.1)

Post-trained on top of gemma4 and qwen3.5, Ornith-1.0 employs a novel self-improving training strategy in which reinforcement learning is used to generate not only solution rollouts, but also the task-specific scaffolds that drive those rollouts. By jointly optimizing the scaffold and the resulting solution, the model generate higher-quality solutions in agentic coding.😎

All models are released under the MIT license, enabling full commercial and research use.

📖Tech Blog: https://t.co/qT9N2HYWFn
🤗Huggingface: https://t.co/PRrwqjeBtM

[Mark @ThisisMarkT]

@kai_brokering @OpenAI You think mostly hype? Demos well!

[Mark @ThisisMarkT]

@TheAmolAvasare It's manifesting not shitposting? 😅

[Mark @ThisisMarkT]

Let's gooo??? I'm ready 🚀

[Chetaslua @chetaslua]

🚨 Claude Fable 5 is back and rollout is going on slowly

> few users reported it to me and i got screen recording proof for it
> i will run my macos test on it and post asap
> lets goooooooooooo.....

[Mark @ThisisMarkT]

@Mr_Salio Easy way to rack up views? 😂😂

[Mark @ThisisMarkT]

@bindureddy I had the same dream too @bindureddy.. 😅

[Mark @ThisisMarkT]

When you're taught yourself how to build a real software with @AnthropicAI's Claude Code and you still ask amateur questions, Claude can actually scold you.. but I kinda like it haha
Sorry @claudeai 🫢
#claude #vibeengineering #building #real #application

[Mark @ThisisMarkT]

Just give use Fable 5 already 🙏

[Mark @ThisisMarkT]

@claudeai is behaving badly and getting the usual message 'model overloaded' - I predict it's gonna be down again (it was around the same time yesterday). I think it's time to call it a day 😴
I'll find out in the morning #sydney @claude @down @again
@ClaudeDevs @claude_code

[Justin Poehnelt @JPoehnelt]

Two months ago I was fired by Google for creating the Google Workspace CLI. It went viral, hit #1 on Hacker News, gained thousands of GitHub stars and many thousands of actual users in just a couple days.

It was an incredible, confusing journey, from directors and leaders asking what they could learn from the tool to getting grilled by legal about why the Google logo and brand colors are on the Google Workspace GitHub code repositories.

I think the cause was that Workspace and certain leaders (and projects) were afraid of being disrupted. But the fear wasn't specific to my CLI, it was a broader fear in what agents meant for Workspace. Either way, the irony of my termination was the announcement at Google Cloud Next two days before I was fired that an official Workspace CLI was coming.

I want this out there because it is easier for me to explain my story and it is an experience I want to fully own. It's also part of my healing.

Nearly 7 years at Google was an incredible opportunity for me and I was fortunate to have wonderful teammates and a manager that fully supported me through these last few months. Thank you.

[Mark @ThisisMarkT]

@kzitouni1 Like for like? 😝

[Mark @ThisisMarkT]

@Shivam25mishra An open source model from China? 😝

[Mark @ThisisMarkT]

I mean 🤯

[Andrew Curran @AndrewCurran_]

A new, more capable version of Mythos has emerged from training. I don't know whether it will be called Mythos 5.1 or Mythos 6, or if Anthropic will keep it internal to accelerate further development - but it has arrived.

Stopping models like Fable 5 or Mythos 5 from being served to the public does nothing to slow down development. In fact, it probably speeds it up slightly by freeing up resources. There are also no rules preventing the labs from continuing to advance capabilities while any current model is under embargo - or from keeping progress quiet until they choose to release it. None of them can afford to pause or slow down. We need only look at how capable GLM-5.2 is as proof of this. To protect their business models, the frontier labs must continually train increasingly capable systems to stay ahead of open source, and each other. The current continues to rage beneath the ice, and we continue to race toward our destination.

[Mark @ThisisMarkT]

🔥 Japan just dropped an AI that hits Claude Fable 5 & Mythos level performance.

Not by building a bigger model.

By orchestrating them.

Sakana Fugu (from @SakanaAILabs) is a multi-agent orchestrator that works through a single API.

✅ Routes different parts of a task to the best models in its pool

✅ Coordinates them (including recursive calls)

✅ Verifies the work

✅ Hands back a final answer that matches or beats top frontier models

Fugu Ultra matches Claude Fable 5 / Mythos on tough benchmarks while adding something the giants can’t:

✅ Full resilience to export controls (swap in any restricted model)

✅ Built in Tokyo by a team that includes Llion Jones (co-author of the original Transformer paper)

This is collective intelligence beating single-vendor dependence.

The future of frontier AI isn’t “bigger models.”

It’s smarter orchestration.

Try it now: https://t.co/HNMvfxqqY2 🐡

Does this change how you see the AI race? 👇

#SakanaFugu #AI #MultiAgent #JapanAI #AISovereignty #FrontierAI #Claude #Transformer

[Mark @ThisisMarkT]

@levie @hardmaru Impressive!