There’s a lot of excitement about what AI (specifically the latest wave of LLM-anchored AI) can do, and how AI-first companies are different from the prior generations of companies. There are a lot of important and real opportunities at hand, but I find that many of these conversations occur at such an abstract altitude that they border on meaningless. Sort of like saying that your company could be much better if you merely adopted more software. That’s certainly true, but it’s not a particularly helpful claim.

On the ProjectVRM list, John Wunderlich shared a find that makes clear how advanced and widespread  AI-based shopping recommendation has gone so far (and not just with ChatGPT and Amazon). Here it is: Envisioning Recommendations on an LLM-Based Agent Platform: Can LLM-based agents take recommender systems to the next level? It's by Jizhi Zhang, Keqin Bao, Wenjie…

 This study explores the neural and behavioral consequences of LLM-assisted essay writing. Participants were divided into three groups: LLM, Search Engine…

Playing Minesweeper with Augmented Reasoning

Meet Clara – your private, on-device AI assistant & agent builder. Complete AI development suite with LumaUI, ComfyUI, N8N automation, and local LLMs. No cloud, no data sharing.

My smartest friends have bananas arguments about LLM coding.

LLM “reasoning” is so cooked they turned my name into a verb

Important new study from Apple

A solo D&D experiment turned into a lesson in building agentic AI apps, connecting LLM prompt tuning, Model Context Protocol and Spring AI.

How the Elixir community can survive — and thrive — in an age of LLMs.

Introduction With the rise of "vibe-coding," it's easy to forget that LLMs offer much more than just code generation. Their real strength lies in language.

The hype about the potentials (it’s always future potential, never real current use) of AI has discarded its last cycle (“reasoning models”/”deep research”, both terms being factually untrue and deeply deceiving at best) and moved to a new double whammy of “agentic AI” and “Vibe Coding”. Now “agentic AI” basically just means that some LLM […]

Ash AI is a new extension for Ash Framework, enabling LLM integration for Elixir apps. Use Ash's declarative approach to take advantage of structured outputs, secure tool calling and to build MCP servers with ease.

The LLMs are here and they’ve already taken over large parts of the internet and of professional writing.

A deep dive into the novel Chain-of-Draft (CoD) Prompting that reducing LLM inference cost and latency like never before.

Just be careful not to shave off too many bits ... These things are known to hallucinate as it is

Your All-in-One Learning Portal: GeeksforGeeks is a comprehensive educational platform that empowers learners across domains-spanning computer science and programming, school education, upskilling, commerce, software tools, competitive exams, and more.

Elixir implementation of a LangChain style framework that lets Elixir projects integrate with and leverage LLMs. - brainlid/langchain

A New Software Development Lifecycle for LLMs

The landscape of Large Language Models (LLMs) is evolving rapidly, with powerful and open models being released at an unprecedented pace. As these technologies advance, so does the potential to integrate them into our existing systems. Traditionally, we've built systems with distinct layers such as the Application layer and Data Persistence layer.

LLMs and Vibe Coding are there. But why? Because our tech is not that advanced and we're disempowered by it. Make tech not suck, and you'll need no LLMs.

I finally use an LLM in an area where it's pretty good.

LLM scrapers are taking down FOSS projects' infrastructure, and it's getting worse.

Reviewing the capabilities and limitations of LLM agents in software development and their impact on skilled and less skilled developers.

Online discussions about using Large Language Models to help write code inevitably produce comments from developers who’s experiences have been disappointing. They often ask what they’re doing wrong—how come some …

Here comes the AI autumn, a season of change that will usher in a new chapter for these incredible technologies.

[Simon Willison] has put together a list of how, exactly, one goes about using a large language models (LLM) to help write code. If you have wondered just what the workflow and techniques look like…

Exploration of using mechanisms provided by Elixir/OTP to build LLM powered applications

Unstract is an open-source, no-code platform purpose-built for extracting data from unstructured documents using LLMs, with high accuracy. Easily deploy API and ETL pipelines for your unstructured data.