Search: “openai”

Sharing my current setup to run Qwen3.6 locally in a good agentic setup (Pi + llama.cpp). Should give you a good overview of how good local agents are today: # Start llama.cpp server: llama-server -hf

'The post all LLMs hate and want you to NOT SEE' ^^ Serious title, you can also discuss this with the LLM, it would be biased against it, as it's known at this point that memory is the true long term

A startup called Sabi just came out of stealth with a beanie that reads your thoughts. 70,000 to 100,000 miniature EEG sensors woven into the fabric. You put it on like a winter hat and type by imagin

Can people please stop taking shots at @sama, and boycott his company instead? Violence is not the answer. This is really bad. The scary part in the US is that it doesn’t matter whether you are the CE

Gary Marcus advocates for applying Satyagraha—a principle of nonviolent resistance emphasizing moral conviction—as a response to contemporary challenges, likely in the context of AI development and go

if you’re interested in local/edge AI related repos and their trends, these are your guys Launching Inference Radar: our new weekly newsletter that tracks the top 130+ inference repositories, monitori

As of April 2026, Latent Space published a curated ranking of the top locally-runnable AI models, providing a research-based overview of the best open-weight or self-hostable models available at that

Catch Or Dagan, AI21's Chief Product & Strategy Officer, at #AIDev26 on April 29: 'An End to Manual Tinkering: Optimizing Accuracy, Cost & Latency in Real-World Agents'. We'll be at Booth 121. See you

🚨 In 2 weeks, a final decision on amendments to the EU AI Act and the GDPR will be made. What is at stake is nothing other than the future of Europe. Many don't know, but the stream of events leading

Love seeing this open-sourced. Had a great chat with @nicoalbanese10 some weeks ago where he hinted to something like this. Great reference architecture for cloud coding agents. Open Agents gives you

Who's coming to AI Engineer Miami? @swyx and @liamcbride will be there! Grab the last few available tickets and meet us there! We are 10 days away! Join us in Miami and see incredible speakers like: @

At this point, I assume that every internal memo at an AI lab is just written for public release. The labs are certainly capable of keeping secrets that don’t leak, so they must realize that all-hands

Open secret that the big AI labs see themselves as emergent state-like entities in the vein of the distributed polities in “Diamond Age” or “Terra Ignota”, which is pretty funny bc staff at said labs

“Above the api line” Good phrase GBrain is my attempt to be in control of my own personal AI that could become my intentionally designed cognitive armor Open source open prompts means you aren’t under

Harrison Chase, co-founder of LangChain, shared or engaged with commentary emphasizing the importance of owning your own memory harness in AI applications rather than relying on third-party API-based

This post by Harrison Chase (or from his X feed) likely discusses the challenges and considerations around implementing proper memory management in AI agents or LLM-based applications. It reflects on

Ethan Mollick shares an assessment of an AI model (likely a newer or smaller model) that, while not matching the performance of the leading frontier models (likely referring to top offerings from Open

Harrison Chase, co-founder of LangChain, shared a post expressing agreement with content discussing the importance of 'not locking in' to specific decisions or commitments, likely in the context of AI

memory is just context -> the harness decides what gets remembered, how, and when memory ownership = agent ownership deepagents lets you own your memory: agent-scoped, user-scoped, or org-level, all i

Harrison Chase discusses the concept of 'memory lock-in' in AI agent frameworks, arguing that the switching cost doesn't occur at the point of adoption but rather accumulates over time as agents build

Memory features in AI platforms represent a strategic mechanism for increasing user retention and platform lock-in, as personalized context and learned preferences become increasingly difficult to mig

Model providers don’t lock you in with the API. They lock you in with your own data. Memory is the moat. If you don’t own your agent’s harness, you don’t own your agent’s memory. And switching means s

Most people building AI agents don't realize this until it's too late. Your agent's memory isn't a feature. It's your moat. 1. Closed harness = they own your memory 2. Switch models → lose all context

Harrison Chase, co-founder of LangChain, likely discusses the concept that AI agents and systems lacking persistent memory cannot truly learn, adapt, or maintain continuity across interactions — makin

Harrison Chase, co-founder of LangChain, discusses a trend in the AI industry where agent harnesses are becoming increasingly closed and proprietary, with memory systems locked behind vendor-specific

Harrison Chase (creator of LangChain) shared a concise architectural principle regarding AI agent design: memory and harness components should remain on the application side of the API boundary rather

Harrison Chase shared a post on X (formerly Twitter) describing a resource as a very helpful overview that also presents a clear framework for understanding Anthropic's recent positioning toward OpenC

At this point how can anybody take seriously @sama’s claim that “Working towards prosperity for everyone, empowering all people, and advancing science and technology are moral obligations for me”, whe

Harrison Chase, co-founder of LangChain, wrote a post in a similar style to a piece by Sarah Wooders, focusing on the concept of 'your harness, your memory' in the context of AI agents and memory syst

For once I actually agree with the constructive argument here. There are more approaches that allow you to own your own destiny. Memory is just context after all and you can provide that at many place

Great breakdown of how model providers are platformizing their AI/agents. A lot of people will take the convenience of going all in on a provider, but they will be locked in and giving up data control

Great piece. The lock-in point is the one nobody talks about enough. If your agent’s memory lives behind someone else’s API, you don’t have a product. You have a dependency. Learned this early buildin

Relying on model providers' stateful APIs or harnesses creates lock-in: switching models means losing your agent's memory -- a cost that only grows as agents get better at learning a big part of agent

@sterlingcrispin @sama Violence was unjustified, and i don’t support it. But many many people may die at Altman’s hands and it is important to speak out when he lies about his moral stance. The headli

The most important post I've read all week by @hwchase17 . Memory, particularly memory consistency is the biggest performance inhibitor to AI agents today. As we interact with different harnesses and

This is a talk from the AI Engineer conference presented by Swyx (or a colleague), focusing on 'Code mode' and letting code serve as the primary communication medium for AI engineering concepts. The t

LangChain's concept of 'your harness = your memory' explores how the surrounding infrastructure and framework around an AI agent effectively functions as its memory system. The post likely discusses h

All is not lost. Duckerton is still possible. Here is Seedance 2.0 with the same prompt. Media My most popular Sora video was “an Elaborate regency romance where everyone is wearing a live duck for a

haha cool, this worked. an MCP server that allows Claude to build it's own reusable skills https://github.com/yoheinakajima/selfMCP (1473 LoC) basically a server with skills to CRUD skills in this vid

A developer expressed enthusiasm for the emerging convergence of `AGENTS.md`, agent skills (SKILL.md), and tool configuration toward portable, cross-tool interfaces rather than siloed, tool-specifi...

A researcher/practitioner (handle @fofrAI) expressed FOMO on social media about missing the AI Engineer Europe 2026 conference in London, noting their Google DeepMind (GDM) colleagues were attendin...

Google DeepMind's Lyria is an advanced AI music generation model capable of producing high-quality audio — including vocals, lyrics, and instrumentals — across a wide range of genres and styles fro...

Sub-agent Model Selection — Different Tasks, Different Models Your main agent runs Qwen3.6-Plus for quality. But not every subtask needs a flagship model. Now sub-agents can use a different model. Cre

The AI Engineer conference (@aiDotEngineer) is a community and conference series for software engineers building with AI , organized by swyx (@swyx) and his co-founder Ben. The AI Engineer Code S...

this from @Kasparov63 applies to the AI autocrats as well. “he would never sell my personal conversations to the government.” oh, yes, he would. I will point out preemptively that one of the autocrat'

Nick Taylor (@nickytonline) shared a post highlighting a talk at AI Engineer (@aiDotEngineer) featuring Liad Yosef (@liadyosef) and Ido Salomon (@idosal1) on the topic of MCP apps and their importa...