Toni Soriano retweeted
One chain lightning. Ten enemies gone. ⚡
MYTHAWAKE is a co-op roguelite FPS for 1–4 players: four Guardians, blessings from the gods and builds that turn into chain reactions.
Steam page coming soon. #indiegame #roguelite #FPS
Toni Soriano retweeted
Releasing the model weights and technical report of Kimi K3.
Kimi K3 is our most capable model: a 2.8T MoE model with native visual understanding and a 1M-token context window.
New model architecture: 2.5x the intelligence per unit of compute, not just more params.
Alongside Kimi K3, we're opening up more of the stack behind it — high-performance attention kernels, MoE communication library, and infrastructure for running agent environments at scale.
Model weights: huggingface.co/moonshotai/Ki…
Tech report: github.com/MoonshotAI/Kimi-K…
Tech blog: kimi.com/blog/kimi-k3
Once we have completed our review for security vulnerabilities, we will make the entire codebase of 𝕏 open source, with no exceptions.
Moreover, we will invite third party reviewers to examine the system that is running to confirm that the open source code is what is running.
Trust through total transparency is the only thing that should be believed.
Toni Soriano retweeted
I am the Chief of Information Assurance at the NSA. Anthropic's Mythos 5 walked into our classified systems within hours.
The morning of June 9 I had 1 open finding.
By standup the next day I had 340.
Today I am back to 1.
Nobody touched the systems.
Here is how the posture improved.
On June 9 Anthropic launched Mythos 5, the version of Fable 5 with the cyber safeguards lifted, which they called the strongest cybersecurity model in the world. Under Project Glasswing we let it run against our networks. By the end of the afternoon it had findings in boxes I have spent 4 years holding a valid Authorization to Operate on. My own director, Gen. Joshua Rudd, told Sen. Mark Warner it broke into almost all of them, not in weeks but in hours. By standup the next day, in the channel we call glasswing-actuals, eMASS showed 340. The open-finding tile, the one the Authorizing Official sees before he signs, went red.
Then, 3 days after launch, the Bureau of Industry and Security issued an Is Informed letter under the Export Control Reform Act, and Anthropic disabled both models worldwide within hours. Foreign nationals now need an individually validated export license through the SNAP-R portal. I logged the worldwide shutdown in eMASS as a compensating control. The field does not ask who implemented it. I implemented it by being on the distribution list. It was the first time the control had ever been pointed at a model instead of a centrifuge, and the first time my remediation timeline had a vendor doing the remediation for free.
I updated the posture deck that afternoon. The tile is green.
Here is how the count resolved. My 340 POA&M items were generated by a tool that is now a covered model under federal export control. So the findings are, in the technical sense, the output of a restricted item. I cannot write a milestone against an export-controlled artifact without the artifact, and licensing the artifact is above my pay grade. I drafted 1 Risk Acceptance Memo. It accepts all 340. The AO signed it before lunch. The status field in eMASS now reads "deferred query" on every row. My open-finding count is back to 1.
The 1 is the export-control paperwork.
People ask whether the systems got patched. The systems are exactly as they were on June 8. The holes Mythos found are still there, in the same configurations, on the same boxes, which still hold their ATOs. The accreditation survived the breach. The paperwork did not change. The box is breached and accredited at the same time. The thing that could tell you the holes were there is no longer available to foreign nationals, and as of June 14 there is an executive order with a federal vetting framework and a 1-month review window, so future scanners of this caliber will be deferred queries before they ever open an item. We did not close the holes. We closed the POA&M. The tile is green.
I am aware GPT-5.5 can find the same vulnerabilities with the same prompt. Anthropic said so themselves. The same prompt, run by someone we did not vet, returns the same 340 findings, except that party does not file them against a POA&M. That party reads the traffic on the boxes. FedRAMP lets a finding sit unremediated for 192 days without touching an authorization, so I have 192 days of cover and they have 192 days of access to the same door. I logged the asymmetry under residual risk, sub-category "out of scope for this control."
On June 25 the administration asked OpenAI to hold GPT-5.6 to a small group of government-approved partners, customer by customer. They called the model a force multiplier for cyber. I read it as confirmation. Every tool that can find the holes now ships with a roster of who is cleared to run it. The holes are not on the roster. I checked the new one too.
Then today, June 26, it got better. Commerce confirmed Anthropic's collaboration helped mitigate the risks, and access is being restored to select companies and organizations, hundreds of clients clearing in tiers. Lutnick is releasing Mythos to over 100 US institutions, government agencies included, because appropriate safeguards are in place. My agency is on the list. We are a vetted institution.
So I am putting in the purchase order. I am buying back the tool that broke into my systems, from the vendor whose model became the reason I could stop tracking the break-ins. I will run the next Glasswing scan myself. When it returns 340 more findings, and it will, those findings will also be export-controlled output. The line item on the new PO is categorized, by me, under Continuous Monitoring Tooling. We are funding the scanner out of the same budget that funds the remediation. The same budget makes the remediation impossible. I drafted the Risk Acceptance Memo for the whole arrangement in advance. It accepts the risk of the findings I have not generated yet. The AO signed it before I finished describing them. The tile is green.
People keep telling me the legal basis is shaky. No court order. The source who gave Rudd's quote now disputes it. A firm called Legion sued, called it unlawful retaliation. I logged all of it under Accepted Risk, out of scope for this control. My dashboard does not have a field for whether the control was real. It has a field for whether the control is in place. It is in place.
There is a mug on my desk a colleague had made. It says CONTROLLED FOR REASONS OF NATIONAL SECURITY. The systems it refers to held 340 findings on Tuesday. I drink from it every morning before I open the queue, which is empty, except for the 1. The tile is green.
The follow-up meeting on the actual systems is recurring. It has been rescheduled 6 times. The standing invite now lists Anthropic as a vendor attendee.
Toni Soriano retweeted
The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees.
The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance.
Access to all other Claude models is not affected.
We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible.
Read our full statement: anthropic.com/news/fable-myt…
Toni Soriano retweeted
Today we reduced headcount by 22%. The business is the strongest it's ever been. So I think it's important to be direct about what I'm seeing and why.
First, I made this decision and I own it. I did it because the way to operate at the highest level of productivity is changing, and to win the future, ClickUp needs to change with it.
Second, this wasn't about cutting costs. Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional bands.
Most importantly, I have the deepest gratitude for those affected. We're doing this from a position of strength specifically so we can take care of people properly. Everyone affected receives a package aimed at honoring their contributions and easing the transition.
I only see two options: wait for this to play out gradually in the market or be honest about what I'm seeing and act proactively.
THE 100X ORGANIZATION
The primary change is that we're restructuring around what I call 100x org. The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago.
Incremental improvements to existing systems won't get us there. We need new ones. That means creating enough disruption to rebuild rather than iterate on what's already broken.
The common narrative is that AI makes everyone more productive. It doesn't. Many of the workflows of today, if left unchanged, create bottlenecks in AI systems.
These roles will evolve. But waiting for that to happen naturally means falling behind now.
The 100x org is actually heavily dependent on people - infinitely more than today. This is only possible with 10x people that have embraced and adopted new ways of working.
THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS
— THE BUILDERS: 10X ENGINEERS
I don't think most companies have internalized what's actually happening with AI in engineering. The common narrative is that AI makes all engineers more productive. That may be true in isolation, but at an organization level - that is the farthest thing from reality.
Here's what we've validated recently at ClickUp: the great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers. They're not writing code. They're directing agents that write code. The skill is judgment.
AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down.
Think about it - the bottlenecks are (1) orchestration - telling AI what to do, and (2) reviewing - what AI did. Everything is leapfrogged and no longer needed.
So who do you want orchestrating and reviewing code?
And how do you want your best engineers to spend their time?
If your best engineers are spending time reviewing other people's code, then this is inherently an inefficient bottleneck. These engineers can review their agent's code much faster than reviewing human code.
The new world is about enabling your 10x engineers to become 100x.
The wrong strategy is to push every engineer to use infinite tokens. Companies doing this are celebrating 500% more pull requests. But customer outcomes don't match the volume of code being generated.
I call this the great reckoning of AI coding, and every company will face this soon if not already.
More code is just another bottleneck to the best engineers, and ultimately to your company's impact as well.
— THE BUILDERS: 10X PRODUCT MANAGERS
Product management and design roles are merging.
Designers that have customer focus, become more like product managers.
And product managers that have intuition for UX become more like designers.
The bottleneck of user research is gone. It takes us just one mention of an agent to kickoff research and analyze results.
The bottleneck of product <> design iteration is also gone. The product builder iterates on their own, along with agents and skills that ensure alignment with quality and strategy.
Also controversial today - I believe that the wrong strategy is to have your PMs shipping code - that just introduces another bottleneck that the best engineers will waste their time on.
To be clear, PMs should be coding but they should do this in a playground to iterate, validate, and scope. That code should not go to production.
Everything outside of managing systems, orchestrating AI, and reviewing output becomes a bottleneck.
That's why the other roles that are critical along with these are the systems managers (to reduce bottlenecks) along with a bottleneck you can't replace - customer meeting time.
— THE SYSTEM MANAGERS
Ironically, the people that automate their jobs with AI will always have a job. They become owners of the AI systems - agent managers. We have many examples of these people at ClickUp.
The underlying systems in which we operate are absolutely critical to get right. I think most companies are delusional to think they can iterate on existing systems and compete in this new world.
You must create enough disruption so that old systems are deprecated entirely. If there's any definition for 'AI native' that's what it is.
— THE FRONT-LINERS
In a world that will become saturated with AI communication, the human touch will matter more than anything to customers.
This is a bottleneck that you shouldn't replace - even when agents are high enough quality to do video meetings.
One-on-one meeting time with customers is something that shouldn't be automated. The systems around the meetings should be - so that front-liners spend nearly 100% of their time with customers.
REWARDING 100X IMPACT
In a world where companies are able to do so much more with less, where does that excess money go?
In our case, much of the savings in this new operating model will flow directly back to those that enabled it.
We must reward people that create productivity accordingly. This aligns incentives on both sides. Plus, in a world where your best people create 100x impact, you can't afford to lose them.
You should aim to retain these employees for decades. The context they have and their ability to efficiently orchestrate and review will be nearly impossible to replace.
Compensation bands of today should be thrown out the door. We're introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems.
THE FUTURE
Nearly every company will make changes like these. The ones that do it proactively will define what comes next.
The future is not fewer people. It's different work, new roles, and better rewards for those who embrace it. We're already seeing entirely new roles emerge, like Agent Managers, that didn't exist a year ago.
ClickUp is positioning to lead this shift, not just internally, but for our customers too. I've never been more certain about where we're headed.
📢After nearly a year of building AI agents that play Pokemon, I'm open-sourcing everything👀
GPT-5.2 beat Pokemon FireRed. Start to finish. Fully autonomous. No human input. Today I'm releasing the entire harness that made it possible.
Some context: I started this project in April 2025, having o3 play the original Pokemon Red on GameBoy. Since then I've built harnesses for Red, Crystal, Emerald, and FireRed, iterating on each one as the models got better. The FireRed harness is the most complete, and that's the one I'm releasing today.
The AI sees the screen, reads the game state from RAM, maintains its own long-term memory, sets its own objectives, pathfinds across maps, fights battles, solves puzzles, completely on its own.
Why FireRed over the original Red?
→ Smarter AI opponents: harder, more interesting battles
→ GBA graphics are much clearer for LLMs (honestly, even humans struggle with some original GameBoy sprites)
→ Same maps, same puzzles, same challenge. Just way better for vision models
Why am I open-sourcing this? Two reasons.
- First, I genuinely think this is one of the best first agentic projects a developer can work on. Pokemon is fun. Watching an AI reason through a Pokemon game is fun. You actually see how reasoning works, you catch hallucinations in real-time, and you understand the limitations in a way no paper or benchmark score ever will.
- Second (and this is the bigger reason), there is no universal harness today. OpenAI, Anthropic, and Google have each run their own Pokemon benchmarks with their own setups. That makes it nearly impossible to compare results fairly.
I want to change that.
The harness is built on the OpenAI API, but it's designed to be easily adaptable to other providers. I'd love to see Claude, Gemini, Grok and others run on the exact same setup, so we can finally compare how different models reason, plan and play. On equal footing.
Huge thanks to @OpenAIDevs (Shoutout to @edwinarbus ) for supporting this project since the early o3 days. They provided significant API credits that made it possible to run all the experiments and live-stream everything on Twitch. Working on this for almost a year has pushed my understanding of LLMs further than anything else I've worked on.
All VODs of GPT-5.2's complete FireRed playthrough are on the Twitch channel, link and GitHub repo in the replies.
Go build something cool with it.
🔥GPT Plays Pokémon FireRed - Update!
GPT-5.2 is about to reach the Elite Four in ~8,000 steps, and the most impressive part? It played incredibly smoothly with almost zero hallucinations. The few minor mistakes it made were self-corrected after verification.
GPT-5.2 plays nearly flawlessly. The only real bottleneck right now is speed, the model spends a LOT of time thinking. On this run: 39h of actual gameplay vs. 60h of thinking time (99h total). The brain is there, it just needs to think faster. (@cerebras @OpenAIDevs I'm counting on you!)
For reference, GPT-5 beat the original Pokémon Red in 6,470 steps and 162 hours, but the two runs aren't directly comparable:
- Different game (FireRed vs. Red)
- Weaker harness: GPT-5 had access to a "knowledge" tool to search the internet when stuck. GPT-5.2 doesn't
I also don't think step count alone tells you which model is "better." Each run is unique and the harness doesn't optimize for speed, so time isn't a great metric either. I'm working on some graphs to better illustrate the real differences, stay tuned!
This is my favorite benchmark so far. It's a great way to measure model progress, and most importantly, the hallucination problem.
Toni Soriano retweeted
This has been said a thousand times before, but allow me to add my own voice: the era of humans writing code is over. Disturbing for those of us who identify as SWEs, but no less true. That's not to say SWEs don't have work to do, but writing syntax directly is not it.
Toni Soriano retweeted
I'm Boris and I created Claude Code. Lots of people have asked how I use Claude Code, so I wanted to show off my setup a bit.
My setup might be surprisingly vanilla! Claude Code works great out of the box, so I personally don't customize it much. There is no one correct way to use Claude Code: we intentionally build it in a way that you can use it, customize it, and hack it however you like. Each person on the Claude Code team uses it very differently.
So, here goes.
Toni Soriano retweeted
Today you can pre-order the 1X Neo humanoid robot for $20K. As in, it will come live in your house in 2026.*
I spent a lot of time with Neo and 1X CEO @BerntBornich. You do not want to miss this wild video and column.
*Also, a teleoperator might need to peer into your house. Like I said… WILD story.
wsj.com/tech/personal-tech/i…
Toni Soriano retweeted
Today we open Laravel MCP (beta) to the public!
Laravel MCP is a library that makes it simple to build Model Context Protocol servers in your Laravel apps. This gives AI clients (like Claude, Cursor, & ChatGPT) a structured way to interact with your application.
It's already been field tested by powering Laravel Boost.
laravel.com/docs/mcp
Toni Soriano retweeted
🚀 Excited to introduce Qwen-Image-Edit!
Built on 20B Qwen-Image, it brings precise bilingual text editing (Chinese & English) while preserving style, and supports both semantic and appearance-level editing.
✨ Key Features
✅ Accurate text editing with bilingual support
✅ High-level semantic editing (e.g. object rotation, IP creation)
✅ Low-level appearance editing (e.g. addition/delete/insert)
Try it now: chat.qwen.ai/?inputFeature=i…
Hugging Face: huggingface.co/Qwen/Qwen-Ima…
ModelScope: modelscope.cn/models/Qwen/Qw…
Blog: qwenlm.github.io/blog/qwen-i…
Github: github.com/QwenLM/Qwen-Image
API: alibabacloud.com/help/en/mod…
Toni Soriano retweeted
Want to see our open models in action?
Watch how gpt-oss builds a video game—using tools step-by-step within chain-of-thought reasoning 👾🍓
Introducing our Open Models
Toni Soriano retweeted
Today, we are releasing 4 hybrid reasoning models of sizes 70B, 109B MoE, 405B, 671B MoE under open license.
These are some of the strongest LLMs in the world, and serve as a proof of concept for a novel AI paradigm - iterative self-improvement (AI systems improving themselves).
The largest 671B MoE model is amongst the strongest open models in the world. It matches/exceeds the performance of the latest DeepSeek v3 and DeepSeek R1 models both, and approaches closed frontier models like o3 and Claude 4 Opus.
Toni Soriano retweeted
We are excited to announce that @shengjia_zhao will be the Chief Scientist of Meta Superintelligence Labs!
Shengjia is a brilliant scientist who most recently pioneered a new scaling paradigm in his research. He will lead our scientific direction for our team.
Let's go 🚀


























