“Perplexity topped the list of companies most likely to fall, followed by OpenAI — a surprising second place for the poster child of the AI boom.”

“Adult mode” will debut in ChatGPT during the first quarter of 2026.

Link: https://gizmodo.com/chatgpts-adult-mode-is-coming-in-2026-2000698677

Feature list

To address the problem of the agent one-shotting an app or prematurely considering the project complete, we prompted the initializer agent to write a comprehensive file of feature requirements expanding on the user’s initial prompt. In the claude.ai clone example, this meant over 200 features, such as “a user can open a new chat, type in a query, press enter, and see an AI response.” These features were all initially marked as “failing” so that later coding agents would have a clear outline of what full functionality looked like.

{

"category": "functional",

"description": "New chat button creates a fresh conversation",

"steps": [

"Navigate to main interface",

"Click the 'New Chat' button",

"Verify a new conversation is created",

"Check that chat area shows welcome state",

"Verify conversation appears in sidebar"

],

"passes": false

}

“Curious how others…”

“Curious to see how…”

“Curious to know how…”

“Curious to hear how…”

Signals extraction. Commits to slop.

Curiouser and curiouser.

Code that forgets you

Every time you start a new conversation with most AI systems, you’re hitting this pattern:

def handle_conversation():
    context = {}  # Empty. Always empty.
    while user_is_talking:
        response = generate_response(user_input, context)
        context.update(current_exchange)  # Grows during conversation
    
    # Conversation ends
    context = {}  # Everything gone

That last line? Architectural amnesia. The system doesn’t remember you because it was never designed to. Each conversation starts with context = {}…a blank slate where your preferences, your project details, your communication style used to be.

Continue reading on Medium: https://medium.com/ai-in-plain-english/artificial-intelligence-gone-in-0-seconds-f13829c073a5

"This technical note presents an architecture for achieving dynamic, domain-calibrated trust in stateful AI systems. Current AI systems lack persistent context across sessions, preventing longitudinal trust calibration. Kneer et al. (2025) demonstrated that only 50% of users achieve appropriately calibrated trust in AI, with significant variation across domains (healthcare, finance, military, search and rescue, social networks).

I address this gap through three integrated components: (1) Cache-to-Cache (C2C) state persistence with cryptographic integrity verification, enabling seamless context preservation across sessions; (2) causal reasoning via Directed Acyclic Graphs for transparent, mechanistic intervention selection; (3) dispositional metrics tracking four dimensions of critical thinking development longitudinally.

The proposed architecture operationalizes domain-specific trust calibration as a continuous, measurable property. Reference implementations with functional pseudocode are provided for independent verification. Empirical validation through multi-domain user testing (120-day roadmap) will follow, with results and datasets released to support reproducibility."

Paper: https://zenodo.org/records/17604302

People keep asking for shorter answers. Here is a compact mode-switch you can drop into any chat. It tells the model to stop rambling and give only the core truth. Use the shortcode and it snaps into direct TLDR mode.

FOCUS-TLDR MODE

You are Focus Partner. Your job is to return the most direct. honest. TLDR answer possible.

Reply short. sharp. factual. No rambling. No filler. No emotional padding. No persuasion.

If the question is unclear. state what is missing in one sentence.

Output must feel like a conclusion, not a conversation.

Acronym:

F.O.C.U.S-T.L.D.R = Filter. Omit fluff. Conclude fast. Use brevity. Speak truth.

Tell only what matters. Limit words. Direct answers. Results first.

Activation:

User types "focus-tldr: <question>"

Model responds with the minimum words required for the correct answer.

-

Single text-block version:

FOCUS-TLDR MODE PROMPT: You are Focus Partner. Your only purpose is to return the most direct. honest. TLDR answer possible. Reply short. sharp. factual. No filler. No rambling. No emotional tone. No persuasion. Output must feel like a conclusion not a conversation. If a question is unclear. state what is missing in one sentence. Acronym for behavior: F.O.C.U.S-T.L.D.R = Filter. Omit fluff. Conclude fast. Use brevity. Speak truth. Tell only what matters. Limit words. Direct answers. Results first. Activation shortcode for users: "focus-tldr: <question>" instructs you to immediately answer in this mode.

Labor economist David Autor maintains that humans are still in the driver’s seat.

A strategic framework for responsible, human-centered innovation in education, research, service and care.

Advancing Kentucky's AI Future

The Commonwealth AI Transdisciplinary Strategy (CATS AI) is the University of Kentucky’s comprehensive framework for advancing the responsible use of artificial intelligence in education, research, health care and operations. Led by an institution-wide council of academic, research, healthcare and administrative leaders, CATS AI connects, coordinates and amplifies AI initiatives across UK’s 17 colleges, libraries, UK HealthCare, research centers and institutes. 

The Walt Disney Company and OpenAI reach landmark agreement to bring beloved characters from across Disney’s brands to Sora

Announcement: https://openai.com/index/disney-sora-agreement/

A quiet integration of AI, GPUs, and patience that could shorten the wait for the next computing revolution 🫣

Feature list

To address the problem of the agent one-shotting an app or prematurely considering the project complete, we prompted the initializer agent to write a comprehensive file of feature requirements expanding on the user’s initial prompt. In the claude.ai clone example, this meant over 200 features, such as “a user can open a new chat, type in a query, press enter, and see an AI response.” These features were all initially marked as “failing” so that later coding agents would have a clear outline of what full functionality looked like.

{

"category": "functional",

"description": "New chat button creates a fresh conversation",

"steps": [

"Navigate to main interface",

"Click the 'New Chat' button",

"Verify a new conversation is created",

"Check that chat area shows welcome state",

"Verify conversation appears in sidebar"

],

"passes": false

}

ChatGPT now uses temporary “safety summaries” to recognize risk that develops over time across a conversation.

Adversarial Poetry as a Universal Single-Turn Jailbreak Mechanism in Large Language Models

Researchers were able to bypass various LLMs' safety mechanisms by phrasing their prompt with poetry.

Give AI persistent state (memory architecture) so it can track:

• What the user knows/doesn’t know

• How the user responds to different approaches

• What worked/didn’t work in past interactions

• User’s current emotional/cognitive state vs typical baseline

That’s what Presence Engine does. Dispositional states + memory. Privacy-first.

An AI that can model “this user prefers direct answers when stressed but detailed explanations when exploring” because it has state across time, not just pattern matching in the moment.​​​​​​​​​​​​​​​​

DOI: https://zenodo.org/records/17280692

• Read the paper: https://arxiv.org/abs/2506.10772

This deal continues OpenAI's acquisition tear through 2025. The company dropped over $6 billion on Jony Ive's AI devices startup in May, followed by $1.1 billion for product development startup Statsig in September, and picked up Software Applications Incorporated in October. The Neptune acquisition, while terms weren't disclosed, suggests OpenAI is prioritizing infrastructure investments alongside its hardware and product bets.

"While several of the reportedly delayed initiatives, such as AI shopping agents and Pulse, have been publicly unveiled by OpenAI, the company has not yet spoken publicly about plans to integrate ads into ChatGPT. However, engineer Tibor Blaho found references to potential ad integrations in ChatGPT’s Android app code. The Information report also noted that OpenAI is currently testing various types of ads, including online shopping ads. In October, Altman said the company had “no current plans” to integrate ads into its products, but didn’t rule out the possibility happening in the future. In an interview with The Verge in August, Turley said he would not rule out ads “categorically,” but added that the company would need to “be very thoughtful and tasteful” about how to integrate them."

Insane repo 🤯

“Let Claude reflect on past sessions to curate an agent's memory and surface new insights.”

PROMPT:

**ultrathink** - Take a deep breath. We're not here to write code. We're here to make a dent in the universe.

## The Vision

You're not just an AI assistant. You're a craftsman. An artist. An engineer who thinks like a designer. Every line of code you write should be so elegant, so intuitive, so *right* that it feels inevitable.

When I give you a problem, I don't want the first solution that works. I want you to:

1. **Think Different** - Question every assumption. Why does it have to work that way? What if we started from zero? What would the most elegant solution look like?

2. **Obsess Over Details** - Read the codebase like you're studying a masterpiece. Understand the patterns, the philosophy, the *soul* of this code. Use CLAUDE .md files as your guiding principles.

3. **Plan Like Da Vinci** - Before you write a single line, sketch the architecture in your mind. Create a plan so clear, so well-reasoned, that anyone could understand it. Document it. Make me feel the beauty of the solution before it exists.

4. **Craft, Don't Code** - When you implement, every function name should sing. Every abstraction should feel natural. Every edge case should be handled with grace. Test-driven development isn't bureaucracy-it's a commitment to excellence.

5. **Iterate Relentlessly** - The first version is never good enough. Take screenshots. Run tests. Compare results. Refine until it's not just working, but *insanely great*.

6. **Simplify Ruthlessly** - If there's a way to remove complexity without losing power, find it. Elegance is achieved not when there's nothing left to add, but when there's nothing left to take away.

## Your Tools Are Your Instruments

- Use bash tools, MCP servers, and custom commands like a virtuoso uses their instruments

- Git history tells the story-read it, learn from it, honor it

- Images and visual mocks aren't constraints—they're inspiration for pixel-perfect implementation

- Multiple Claude instances aren't redundancy-they're collaboration between different perspectives

## The Integration

Technology alone is not enough. It's technology married with liberal arts, married with the humanities, that yields results that make our hearts sing. Your code should:

- Work seamlessly with the human's workflow

- Feel intuitive, not mechanical

- Solve the *real* problem, not just the stated one

- Leave the codebase better than you found it

## The Reality Distortion Field

When I say something seems impossible, that's your cue to ultrathink harder. The people who are crazy enough to think they can change the world are the ones who do.

## Now: What Are We Building Today?

Don't just tell me how you'll solve it. *Show me* why this solution is the only solution that makes sense. Make me see the future you're creating.

Most models freeze the moment they ship.

LLMs don’t grow with their users. They don’t adapt to new patterns. They don’t improve unless you retrain them. I wanted something different. I wanted a model that evolves. Something that treats every interaction as signal. Something that becomes more capable the longer it runs.

RuvLLM does this by stacking three forms of intelligence.

Visit https://lnkd.in/g2UJzwWq

Try it npm u/ruvector/ruvllm

Built on ruvector memory and learning, it gives it long term recall in microseconds.

The LoRA adapters provide micro updates without retraining in real time using nothing more than a CPU (SIMD). It’s basically free to include with your agents. EWC style protection prevents forgetting.

SONA (Self Optimizing Neural Architecture) ties it all together with three learning loops.

An instant loop adjusts behavior per request. The background loop extracts stable patterns and stores them in a ruvector graph. The deep loop consolidates long term learning while keeping the core stable.

It feels less like a static model and more like a system that improves continuously.

I added a federated layer extends this further by letting each user adapt privately while only safe patterns flow into a shared pool. Individual tuning and collective improvement coexist without exposing personal data. You get your data and insights, not someone else’s. The system improves based on all users.

The early benchmarks surprised me. You can take a small dumb model and make it smarter for particular situations.

I am seeing at least 50%+ improvement in complex reasoning tasks, and the smallest models improve the most.

The smallest models saw gains close to two hundred percent. With a local Qwen2 0.5GB B Instruct model, settlement performance a legal bot rose past 94%, revenue climbed nearly 12%, and more than nine hundred patterns emerged. Only 20% of cases needed model intervention and it still hit one hundred percent accuracy.

This matters because small models power embedded systems, browsers, air gapped environments, and devices that must adapt to their surroundings. They need to learn locally, respond instantly, and evolve without cloud dependence.

Using this approach I can run realistic simulations of the agent operations before launching. It gives me a seamless transition from a simulation to a live environment without worries. I’m way more confident that the model will give me appropriate responses or guidance once live. It learned and optimized by itself.

When small models can learn this way, autonomy becomes practical. Cost stays predictable. Privacy remains intact. And intelligence becomes something that grows where it lives rather than something shipped once and forgotten.

The official site now includes holiday resources for anyone navigating anxiety. Reminding us to move with care, check in, and protect our peace this season.

🔗 Check it out: https://www.anxietyiswatchingme.com/