Search: “tutorials”

Multimodal prompting enhances coding agents by enabling them to process and integrate multiple types of input data—such as text, images, and code snippets—simultaneously, improving their ability to un

@loujaybee If they are serious and not afraid of a bit of maths, I would recomend starting off by reading : 1) The Algebraic Mind by @GaryMarcus 2) Book of Why by @yudapearl 3) A Guide for Thinking Hu

This post discusses the evolution of multimodal prompting in AI agent interactions, highlighting how users can now communicate with AI systems using multiple input types beyond text. The author provid

Oh look. The migrant who stomped a white Swedish man to death was a rapist ... because of course he was. Meaning, if the authorities did their fucking job and deported him, Christian Zedig's children

AI-powered security systems will be necessary to detect and defend against AI-based threats, as human security experts cannot match the speed and sophistication of AI attacks. This perspective suggest

Yet we still don't have level-5 self-driving cars, and certainly not self-serving cars that can learn to drive in a few hours of practice like any teenager. We don't even have domestic robots that can

Happy 4th of July everyone. I came here as a kid at 9 years old, not knowing a single word of english, lived on food stamps in section 8 housing. My parents cleaned houses while my sister and I collec

NEW paper worth reading. (bookmark it) The basic idea is to pair a compressive recurrent state with a small exact memory, which helps to recover long-range recall without giving up the efficiency of l

still many industry executives don't get the value of top-tier AI conf like ICML/ICLR/NeurIPS, they'd rather sit on some summit roundtable waxing about AI governance, societal impact or whatever endga

Hot take: I think it's still important to understand the code that our agents write! In this mega thread (based on my AIE talk today), I will explain why that's the case, and show some ideas for how t

huge week of really exciting launches at langchain! big week at langchain, with a lot of launches: 1/ OpenWiki - auto generate a wiki of a github repo 2/ two different voice agent tutorials 3/ Harbor

New research from Google. LLMs hallucinate with high confidence, miss their own knowledge boundaries, and misreport uncertainty. Most fixes bolt calibration on from the outside. RLMF turns the model o

Obvious in retrospect, but I didn't really anticipate: Fable: Performing Final Review of <Awesome Feature> Also Fable: I appear to have introduced a critical security vulnerability. <This model's safe

Our goal is to help security teams shift from reactive triage to proactively fixing what matters, close the critical gaps scanners miss before they become breaches, and return engineering capacity to

Trq212 is presenting a Field Guide to Fable at AI.Engineer World's Fair, indicating renewed interest or development in the Fable project or framework. This presentation likely covers Fable's features,

Great talk by @trq212 ! You mentioned you generated the slides in 4 hours with Fable? These slides were gorgeous!! Most other presenters using AI generated deck look horrible. Can you please share any

This Replit post likely provides a security walkthrough covering four essential security considerations for developers building applications on the Replit platform. The guide appears aimed at app buil

Interrupt 2026 is coming to New York City and London this fall. → Hear from engineers + teams shipping agents in production → Keynotes from @hwchase17 + industry leaders on what's next for agents → Ha

Just published a YouTube video walking through OpenWiki. Setup and configuration, how it works, what it targets, and how to automatically keep your docs up to date. Check it out, and see the OSS GitHu

More and more developers turning to glm5.2 as a daily driver for coding Here’s how to use it with deepagents code You can start building with GLM 5.2 in minutes: 1️⃣ Download dcode 2️⃣ Select your mod

This video provides a quick explanation of Retrieval-Augmented Generation Models (RLMs), outlining their benefits and demonstrating their implementation with DeepAgents. The content likely covers how

tmrw at @aidotengineer i’ll be exploring history’s most beautiful and fertile minds. i’m calling it Imagination Engineering. i’ve been asking myself how to become an idea factory, as originality becom

Fireworks AI announced achieving 446 tokens per second throughput speeds as measured by Artificial Analysis benchmarks, positioning this as their standard performance metric. The company offers custom

it's a sad day when we stop learning. nothing quite replicates the pace and structure of college, but Independent Studies has become my version of continuing education post-grad. some of my favorite c

This post from DAIR.AI recommends resources for developers and organizations scaling applications using open-weight language models, emphasizing the importance of planning infrastructure and deploymen

This post likely discusses technical decisions and design patterns for dynamically displaying subagents within an AI system, documenting the alignment the team reached after encountering implementatio

A big reason that token costs become an issue in organizations is leadership is not making decisions about how to use AI, the processes that need to change as a result, & how to think about multiplaye

A very rare deep dive into Runway's culture, technology and mission, or how to build new worlds. Got to hang with the @runwayml folks during their film festival week, and pull back the curtain in toda

Apologies to those looking forward to @mattpocockuk's keynote, but he had to bow out for personal stuff... ... but he didn't leave us high and dry!!!!!!!!!! happy to announce our final and tenth onlin

https://longcat.chat/blog/longcat-2.0/ People are missing out on how big a deal Longcat 2.0 by Meituan (aka 'Chinese Doordash') is. Near frontier performance, trained on 50k Chinese domestic accelerat

LLM-as-a-Judge explained in ~10 mins. Knowing how to build AI verifiers and judges is one of the most important emerging AI skills today. Here is a quick intro on the topic and where to learn how to a

Masterclass deep-dive into programmatic spawning of subagents - highly encourage taking a look! @colifran_ dropping elite ball knowledge per usual this blog covers 6 common workflow patterns we see wi

this blog covers 6 common workflow patterns we see with dynamic subagents (fanout and synthesize, adversarial verification, etc) if you'd prefer to learn w/ a video, check out this excellent guide fro

Token spending should be understood as organizational research and development rather than purely a productivity cost, representing an investment in discovering how to restructure business processes a

v14 Lite Release Notes: – Distilled the intelligence from HW4 V14 into HW3. This allows HW3 to directly learn how to handle scenarios using HW4 V14 as a guide. This process unlocks the improvements th

Did something happen to Opus 4.8 today? First time I've seen this happen (and I use it daily): it almost totally stopped thinking, even at highest reasoning setting. And answered terribly. I repeated

Fleet agents can be shared in channels where your company is already doing work. Slack, Teams, etc Video from Caspar showing how to bring them into Slack! For agents to spread through a company they h

NEW paper worth reading. Reasoning-data curation is expensive because scoring a trace usually means reading it to the end. This new work from UCLA shows you may not have to. The quality of a reasoning

the future of AI is multi-model (including a majority of open-source ones provided by @huggingface of course!)! How to keep AI spend flat while token usage grows exponentially: Not with friction and s

The old BBC 'Industrial Revelations' series is a great overview of what makes an Industrial Revolution Steam alone wasn't enough, it required thousands of skilled workers figuring out how to apply thi

🧑‍🏫3hr Long Deep Agents Course Great course from a member of the community on Deep Agents Covers task planning, file systems for context management, subagent-spawning, and long-term memory https://www

> Better Caching – Cache misses are the easiest way to drive your cost up. All of our requests are cache aware, so we’re reusing a warm cache wherever possible. We do this for you in Deep Agents - see

How to keep AI spend flat while token usage grows exponentially: Not with friction and spend alerts. With better defaults, routing, and caching. Better Defaults (not Usage Caps) – Engineers can choose

If you use LLM-as-judge, this one is worth reading. (bookmark it) It's actually one of the most effective ways to use LLM-as-a-Judge for evals. Holistic judge scores hide both their reasoning and thei

This is very interesting. Coinbase seems to have lowered their token spend ($$) to about half, by 1) routing to cheap inference like GLM 5.2 and Kimi 2.7 that are still pretty performant 2) Smart rout

This post by Filip Hric explains how to interpret AI code review benchmarks, specifically breaking down key evaluation metrics like precision and recall that are commonly used to assess code review to