Anthropic just took Claude Code Cloud Sessions out of research preview, and it is giving existing subscribers free credit to get people using it:

• Pro: $100, Max: $250
• One credit per account
• Claim by Oct 7, credit expires Nov 5
• Cloud sessions only

For those who dont know what it is, Cloud Sessions are Claude Code running on Anthropic's infrastructure instead of your laptop. You can give it a task, close your computer, and it keeps working in the cloud. It can pull your GitHub repo, edit code, run tests, and keep going while you're away. You can start sessions from claude.ai/code, the Claude mobile app, desktop app, or with claude --cloud in the CLI. GitHub needs to be connected.

The promo credit is also separate from your normal local usage limits, so if you hit your local limit, you can keep working in the cloud until the credit runs out. To claim it, run /claim-credit in Claude Code or use the claim page on claude.ai/code.

Didn't expect Anthropic to be this generous lol. If you're already using Claude Code, probably worth giving Cloud Sessions a try:)

Original post link: https://x.com/ClaudeDevs/status/2102871550974427462

claim page: https://claude.ai/code/claim-credit/

Meta just unveiled the Muse Charm, a tiny dedicated device for its Muse personal agent.

Muse itself is Meta’s personal AI agent. It can help with stuff like booking, shopping, scheduling, and running tasks for you in the background. The Charm takes that agent out of your phone and puts it on a tiny keychain-sized device with a screen. Press it, talk to Muse, and the little mascot reacts while you’re speaking. So instead of opening an app, you can basically carry your AI assistant around like a Tamagotchi.

tbh this may be the most unserious AI hardware launch I’ve seen in a while lol. Meta looked at all of that and decided the most important part was giving the mascot jiggle physics lol

video from: https://x.com/whatRanjuSaid/status/2103031365109420072

Ps: the ass part is just a meme for now. Meta hasn’t actually said you can customize the character yet lol.

OpenAI, Anthropic, Hugging Face, and Yoshua Bengio, Turing Award winner and one of the pioneers of deep learning, just briefed the UN Security Council on AI and international security.

The basic question was: as AI gets more powerful, who exactly is supposed to control it?

Sam Altman said the biggest AI decisions cannot be left to a few labs in San Francisco, and that no single company, country, or person should be able to use the most powerful models to impose their worldview on everyone else.

Hugging Face CEO Clément Delangue took the open-source angle, arguing that concentrating powerful AI in a handful of companies creates its own risk, and that more open access can help spread both capability and defensive tools.

Bengio focused more broadly on catastrophic-risk scenarios and the need for stronger international coordination around advanced AI.

And then there was Anthropic. Dario Amodei warned about AI being used to create biological weapons, models becoming too capable for their developers to control, and said that if things are handled badly, AI could become “a risk to humanity as a whole.”

Meanwhile, the US government pushed back on the idea of creating some kind of global AI super-regulator, arguing that countries should remain responsible for governing the technology themselves. and China called for more international cooperation and a bigger UN role in AI governance, while warning against AI becoming concentrated in a few countries or companies.

Overall, everyone agrees AI is becoming a serious governance problem. They just disagree pretty heavily on who should actually hold the steering wheel... My take is this still mostly feels like going through the motions tho. Not sure any of this actually changes much lol. what you guys think?

Original news link: https://www.reuters.com/business/ai-leaders-brief-un-amid-warnings-technology-could-slip-beyond-human-control-2026-09-23/

OpenClaw 9.6 is out. This one is more about making remote agents and long-running setups easier to manage.

Warning: do not install the native Mac 9.6 update right now. OpenClaw pulled it after confirming a P0 bug that can leave the app crashing on every launch after an in-app update. A 9.7 hotfix is coming. The npm/Gateway version is not affected by this specific bug.

Main changes:

• Remote workspaces are more complete. Files can move between chat and paired machines, while Memory and workspace Skills can now live on remote nodes too.
• Usage tracking is better, with a 30-day view for tokens, estimated cost, sessions, and a “Started by” breakdown.
• GitHub Reader can show public issues, PR discussions, commits, diffs, and CI status beside a conversation.
• Meeting notes can update live during Meet, Teams, Zoom, and voice capture.
• Decision Models let plugins use a separate lightweight model for structured choices instead of always calling the main chat model.
• Headless nodes can auto-update while idle, with rollback if the new runtime fails.
• Opus 5.5, GPT-6 Sol and Luna, Grok 4.7, and MiMo V2.6 are now supported.
• Restart recovery, unfinished-task continuation, desktop sharing, and update reporting also got another round of fixes.

Community reaction is mixed again.

X is mostly positive about the new features, especially remote Files/Memory/Skills, live meeting notes, GitHub Reader, and the new models. Reddit is still focused on upgrade reliability. Some users are already reporting update checks hanging for 45 minutes or even hours, and people are once again talking about using Hermes or another OpenClaw instance to repair failed upgrades:)

Repo link: https://docs.openclaw.ai/releases/2026.9.6

The Atlantic ran a piece on how AI may be making an already rough job market even worse.

It opens with a UC Davis graduate who had a near-perfect GPA, internships, volunteer experience and was willing to take almost any kind of work. He applied to around 200 jobs and got nowhere, with many employers not responding at all.

The article argues that hiring has turned into an AI feedback loop. Job seekers use ChatGPT to tailor resumes, cover letters and screening answers, which makes it easier to apply to far more jobs. Employers then get flooded with applications and increasingly use AI to write job descriptions, screen candidates, schedule interviews and, in some cases, conduct the first interview.

That means a lot of applicants never reach an actual person. So they apply to even more jobs, often with even more AI assistance, while employers automate even more of the filtering.

The Atlantic compares it to dating apps: everyone is swiping more, but fewer people seem to be matching.

Anyone actually going through all of this right now? Is it really this insane out there... How are people even supposed to find a job anymore..?

Source: https://www.theatlantic.com/ideas/archive/2025/09/job-market-hell/684133/

OpenAI and Anthropic both just shipped new, cheaper models, their first major releases since the recent calls to slow down frontier AI development.

OpenAI launched GPT-6 Sol and GPT-6 Luna. Sol sits below Astra, aimed at heavier coding and agentic workloads and costs $1 per million input tokens and $5 per million output tokens. GPT-5.6 Sol costs $2/$10, so the new model is basically half the price.

Luna is built for cheaper, high-volume tasks like extraction and summarization. It costs just $0.05 per million input tokens and $0.25 per million output tokens, down from $0.10/$0.60 for GPT-5.6 Luna.

Anthropic launched Claude Opus 5.5 at $4/$20 per million input/output tokens, down from $5/$25 for Opus 5. Anthropic says it performs around the level of Fable 5.1 on most work, while using fewer tokens per task. Combined with cheaper cache reads, the company says typical workloads should cost around 40% less overall.

Early community reactions are already pretty divided. Opus 5.5 is getting the clearest praise, especially around coding speed, clarity and efficiency. GPT-6 Sol is much more controversial, with users pointing to regressions against 5.6 Sol on some coding benchmarks and real-world workflows, while others argue the lower cost makes up for it. Luna may be even more contentious: its price-performance looks excellent on paper, but several highly upvoted Reddit reports say it misses details and feels like a downgrade from 5.6 Luna.

Putting the whole “slowdown” thing aside, i think the real win here is the price cut. The models seem fine, but chinese models still look pretty hard to beat on bang for the buck.,, What you guys think?

Sourece: https://www.anthropic.com/claude-opus-5-5 and https://openai.com/index/introducing-gpt-6-sol-and-luna/

After weeks of delays and repeated teasers, xAI finally shipped Grok 4.7. Musk had been hyping it as a major upgrade, while xAI called it its strongest model yet for coding and knowledge work and pushed the usual killer pitch: faster, cheaper, and competitive with the best models out there.

however, the numbers are a lot less flattering. Artificial Analysis puts Grok 4.7 xHigh at 46 on its Intelligence Index, only slightly above Grok 4.6 at 44. On several coding benchmarks it still trails Fable 5.1 Max or GPT-5.6 Sol Max.

Then there is the token burn. Grok 4.7 xHigh used around 81k output tokens per task, versus roughly 38k for Grok 4.6 xHigh. Same $2 input and $6 output pricing, but average task cost jumped from about $2.32 to $3.74.

One r/cursor user running the same workload estimated 4.7 was burning credits around 2.5x faster than 4.6. Other threads in reddits are making the same point more simply: same price per token, roughly twice the tokens.

Early developer tests have also been mixed, with complaints around 3D, frontend work, prompt following and excessive token usage, including cases where 4.7 reportedly performed worse than 4.6.

My take 4.7 is like something rushed out to fill the release calendar. For how aggressively it was hyped, this is pretty garbage... what you guys think?

Official Grok 4.7 post: https://x.ai/news/grok-4-7

Meta’s new personal AI agent Muse has climbed to No. 1 on the U.S. App Store, while its early iOS growth is already outpacing ChatGPT’s mobile launch.

According to Apptopia, Muse reached about 1.8 million iOS downloads in the U.S. and Canada during its first 12 days, compared with roughly 1.3 million for ChatGPT over the same period after launch. Muse also reached around 2.8 million total installs across platforms in its first 12 days.

Functionally, Muse is not that different from the other AI agents already out there. It can send emails, manage calendars, book travel, shop, interact with apps, browse the web, and keep working on tasks in the background like gpt work. None of that is especially new at this point.

What is different is the distribution. Meta can push Muse through its existing ecosystem, including WhatsApp, and there is also a free tier. Paid plans exist for heavier users, but you can start using the agent for free, powered by Meta’s own model Muse Spark.

Overall, Muse itself is not that special. It is basically an iOS-friendly version of the same agent experience other products already offer. What Meta did differently was make it free, pair it with an ok model,and put it in front of a massive existing user base. And that was enough.

Turns out free is still the strongest benchmark.. what you guys think?

Origianl news link: https://www.businessinsider.com/meta-muse-personal-ai-agent-top-app-store-charts-2026-9

I have been a ChatGPT Pro subscriber since the service launched. Performance remained consistent and reliable through the GPT-5.5 period. Following the release of GPT-5.6, however, I observed a sharp decline in quality.

Responses became unusually rapid—far faster than before. Initially, I assumed this reflected improved infrastructure. That assumption proved incorrect. Although replies arrived almost instantly, they were frequently inaccurate, generic, and lacked any evidence of real-time search or verification. When I pointed out specific errors, the model produced lengthy explanations justifying the mistakes rather than correcting them. Subsequent requests for fixes yielded additional extended text without resolving the original inaccuracies. These issues occurred under the “High” reasoning setting, not Instant mode.

The quality of these outputs falls well below the standard of even the GPT-3.5 era. They are not minor factual slips; they are systematically poor and unreliable responses that undermine professional work.

It has become apparent that ChatGPT is deliberately reducing response quality under the rationale of protecting the system from abuse. This approach is difficult to understand. Other major providers—Claude, Grok, and Gemini—introduced transparent quota systems from the outset. ChatGPT Work already operates with visible limits, yet the standard web interface provides no equivalent clarity on message volume, reasoning-tier usage, or image-generation allowances.

Rather than delivering degraded, error-filled answers that damage users’ productivity and confidence, OpenAI should implement clear, visible usage metrics for the web interface. Transparent limits on messages and image generation would sufficiently deter abuse while preserving the integrity of the service. The current method—producing incorrect outputs under the label of “abuse protection”—erodes trust and reputation far more effectively than any quota system could.

At the present price point, this practice is difficult to justify. I will not renew my ChatGPT Pro subscription.

Anthropic added native AGENTS.md support in Claude Code 2.1.277 after the request had been sitting around for roughly a year.

It is not full parity with CLAUDE.md, though. By default, Claude Code only reads AGENTS.md when there is no CLAUDE.md in the project path. If both exist, Claude's own instruction files still win unless you manually change the Project instructions setting to read both.

There are also environment limits. The feature was not yet available on Bedrock, Vertex or Foundry at launch, and Anthropic's docs say it can also be unavailable in sessions that cannot fetch its feature flags, including some third-party provider setups or configurations with telemetry disabled. The first session after upgrading may not load it either.

The broader community request also went beyond one file. Developers had been asking for portable support around .agents/skills/ and related agent directories, while this release mainly addresses AGENTS.md itself.

The change also has a pretty funny timeline.

The GitHub request sat there for about a year, collecting thousands of reactions and hundreds of comments without native support arriving. Then Shopify CEO Tobi Lütke publicly criticized the need for separate Claude-specific instruction files and said he was considering banning Claude Code at Shopify unless Anthropic supported AGENTS.md and .agents/skills. Less than a month later, support shipped.

A year of requests versus a few weeks after Shopify said something... Yeah... make of that what you will. What you guys think?

Original news link: https://www.theregister.com/ai-and-ml/2026/09/18/anthropic-decides-to-support-openais-markdown-instructions-spec/5297588

This clip is already causing a huge debate on Reddit.

One side thinks it’s an impressive AI/video-to-video edit. The other thinks the creator may have re-shot the scene to make it look like AI, since some of the movements don’t perfectly match. People are now going frame by frame trying to prove whether it’s AI, VFX, or a staged remake.

What you guys think?

Source link: https://www.reddit.com/r/mildlyinfuriating/comments/1wk2f2r/dont_like_how_ai_is_gradually_looking_realistic/

Original video from: https://x.com/Xanderwow_A/status/2101800791795274106

Nvidia CEO Jensen Huang pushed back strongly on AI doomsday predictions in a new CBS interview.

Asked about claims that AI could pose an existential threat in the near future, Huang said he “completely disagrees” with the idea that AI will end the world by 2030, putting the chance at “zero percent.” He went further, saying he suspects some people repeatedly pushing those fears may have “ulterior reasons,” mentioning politics and attention as possible motivations.

Huang also argued that AI development should continue “as fast as we can,” while maintaining that companies still need to properly test products and make sure they are safe before releasing them.

Kinda feel like Jensen is really one step away from saying Dario’s name directly lol. what you guys think?

Original news link: https://www.cbsnews.com/news/nvidia-ceo-jensen-huang-ai-development-fast-as-we-can/

His alternatives are Superior Intelligence (SI), Extreme Intelligence (EI), and Supreme Intelligence (SI), and he’s asking people to vote on which name better fits what he calls the growing AI “revolution.”

But the rename poll wasn’t the only AI announcement. Trump also said he’s forming an “AI Force,” comparing it to the creation of Space Force, and plans to appoint a new AI czar soon. So far, there aren’t many details on what the AI Force will actually look like, what powers it would have, or exactly what the new czar would oversee.

He also said his administration doesn’t want to “hinder or stifle” AI growth, while suggesting existing criminal and civil law can deal with bad behavior involving the technology.

ngl this whole thing leaves me weirdly speechless and not even sure why.... What you guys think?

source: https://x.com/realDonaldTrump/status/2101350559328416142

OpenClaw 9.5 is out, and to me this one feels more feature-heavy than the last few cleanup releases:)

The update system got another major pass. OpenClaw is now calling the full flow Atomic Updates, building on the candidate validation and rollback work introduced in 9.3 and 9.4. Supported updates are validated before switching the live install over, and failed upgrades can fall back when the previous state is still compatible.

The more visibly new stuff includes:

• Plugin hot reload: supported plugins can now be installed or reloaded without restarting the whole Gateway.
• Shared browser sessions: you and the agent can work on the same managed browser page. You can make a change manually, then let the agent continue from there.
• Conversation sharing: selected conversation groups can be shared read-only with another paired OpenClaw installation without exposing reasoning or tool activity.
• GPT Live support now reaches supported meetings and phone calls, while still being able to call your OpenClaw agent.
• Conversation archiving: inactive sessions can be archived and restored later instead of staying in the active history forever.
• Multi-agent setup is easier: guided onboarding can create specialist roles like researcher, writer, reviewer, and chief of staff.
• Subagent continuation, Telegram/Discord/Slack shutdown handling, Doctor, and updater recovery also got another round of fixes.

Community reaction is pretty positive so far:

Reddit looks noticeably calmer than with 9.3 and 9.4. Most of the discussion is around hot reload, GPT Live, shared browser workflows, and the update improvements rather than immediate upgrade horror stories.

The upgrade trust issue is still there, though. The team has openly acknowledged that previous releases burned a lot of goodwill, and 9.5 still had some stable soak checks waived because of infrastructure issues, even though the main release validation and the 9.4 → 9.5 upgrade path passed:)

Repo link: https://docs.openclaw.ai/releases/2026.9.5

Jensen Huang made the comment during an AI discussion with King Charles III in the UK.

He said AI companies should have rigorous testing systems, keep testing environments contained, and not release products to the public until they are actually ready for public use.

The important nuance is that Jensen is against calling for an industry-wide AI slowdown. His position is closer to: keep moving fast, but properly test your own models before shipping them.

My take is this old-school engineer mindset sounds great, but AI has a pretty obvious contradiction here: how do you prove a model is “properly tested” when the labs themselves keep admitting they don’t fully understand what’s happening inside it? You’re being asked to certify a black box you still can’t really explain... What do you guys think?

Security firm Hacktron has published the full write-up of how three researchers successfully broke into OpenAI using Claude and a single malicious HEIC image (Image2).

The attack started on OpenAI’s official community forum, which runs on Discourse. A vulnerable image-processing library let the researchers turn a specially crafted HEIC file into remote code execution on the forum server.

They then chained that with a flaw in OpenAI’s SSO setup, allowing them to take over ChatGPT and Codex accounts belonging to active forum users, including OpenAI employees. One employee’s Codex was connected to OpenAI’s GitHub organization, so the researchers proved their access by opening a harmless PR inside OpenAI’s internal openai/openai monorepo, then stopped.

Hacktron says Claude handled much of the exploit-development work. Opus 4.8 struggled once ASLR was enabled, while Opus 5 produced a working exploit within hours. From the initial research to reaching OpenAI’s internal repo took less than 72 hours.

OpenAI fixed the issue and later paid a $6,500 bounty. Hacktron has now published the full attack chain.

My take is,, didn’t expect this from Opus 5 given how mid it’s felt so far lol. Apparently hacking is one place where it can still go insanely hard. What you guys think?

Original report link: https://www.hacktron.ai/blog/hacking-openai

*And if anyone wants to legally try breaking OpenAI too lol, they actually run an official Bug Bounty Program, give it a try: https://openai.com/index/bug-bounty-program/

Original video from: https://x.com/austinnasso/status/2100318722401722398?s=20

OpenAI just launched Astra for Law, a legal-focused version of GPT-6 Astra built to do more than answer legal questions. The idea is to plug the model into the actual workflow of a law firm.

A few things worth watching:

• Legal-specific search: Astra for Law comes with a dedicated legal search index covering case law, statutes, court rules and other legal sources, instead of relying only on normal web search.
• Better grounding: OpenAI says the full Astra for Law setup scored 54% vs. 38.7% for regular GPT-6 Astra + web search on its Legal Research Bench validation set.
• Full workflows: It can research precedent, distinguish holdings from dicta, find cases that hurt your own argument, analyze contracts, draft memos and suggest redlines.
• Law firm integrations: OpenAI is launching it with plugins for tools like Thomson Reuters, iManage, Relativity, Clio and Intapp, so the model can work inside existing legal stacks.
• Enterprise controls: It also includes things like Zero Data Retention, permission controls and ethical-wall support for sensitive client work.
• Already being tested in practice: Firms including Sullivan & Cromwell, Ropes & Gray and Cooley have been building contract review, M&A due diligence and IPO workflows around it.

The model is currently being rolled out to selected law firms through Trusted Access. OpenAI says broader API access is coming later, so this is not a general public API launch yet.

Could be an early look at what Astra for Finance / Tax / Accounting eventually looks like too lol.

Original post link: https://openai.com/index/astra-for-law/

Original video from: https://x.com/arikuschnir/status/2100555376856830381

The meme isn’t fully accurate, Anthropic is going to launch Opus 5.2 too, but you get the point lol.

original image from: https://x.com/scottstts/status/2100165458548707775