Blazing-fast Rust token usage tracker for Codex and Claude Code with unified reports, live monitoring, CLI/TUI/GUI dashboards.

A recent study by Tencent showed that Elixir had the highest completion rate across models when compared among 20 different programming languages. When combining the results of all 30+ evaluated models, 97.5% of Elixir problems were solved by at least one model, the highest among all languages:

An Elixir program consist of a large number of lightweight, concurrent processes communicating with each other via asynchronous messages. A process receives and handles incoming messages, transforming its internal state in a functional way. Inside a process, all code is sequential. The VM running Elixir, BEAM, normally utilizes all cores of a modern CPU and schedules processes for execution. By running many concurrent processes you can maximize the performance of current hardware.

Asynchronous Tasks and Streaming UIs in Phoenix Liveview

The Top 3 LiveView Form Mistakes (And How to Fix Them)
John Curran •
November 07, 2025

I’ve been writing LiveView since 2020. In that time, I’ve seen the same three form mistakes at multiple companies. Here’s what they are and how to fix them.

1. Slow, laggy forms with scattered logic because form state gets stored in socket assigns and server round-trips get used for dynamic UI (conditional inputs, toggles), instead of keeping that state in hidden form inputs where it belongs.

2. Brittle system where UI and database can’t evolve independently because database schemas get used directly for forms, coupling persistence logic to presentation.

3. Users stuck with valid data but can’t submit because changesets get manually manipulated with Map.put or Map.merge instead of Ecto.Changeset functions, leaving stale errors behind.

The common thread: don’t fight the framework. Keep form state on the client, create embedded schemas for your forms, and use Ecto.Changeset functions to modify changesets.

If you’re running a Phoenix LiveView application and your iOS Safari users are experiencing frozen pages, slow reconnects, or 10+ second hangs after returning from sleep this article is for you.

I’ve been running a production Phoenix LiveView application. The app worked great on desktop, but iPhone users kept reporting the same thing: the page would freeze or hang for several seconds after switching back from another app or unlocking their phone. Sometimes the page would never recover at all.

Here’s what was actually happening and how I fixed it.

timeseries , ecto & postgresql

When you're selling stuff, every click away from your website is a potential lost sale. Customers kept asking us to allow people to buy tickets without leaving their branded site. They loved the service, but wanted to retain brand presence and coherence.

The ask seemed simple enough. Drop a widget on any webpage, show some events, let people check out. But as we dug into it, the technical challenges started stacking up. How do you maintain cart state across page refreshes? How do you track marketing attribution when the purchase happens on someone else's domain? And how do you process payments securely in what is essentially a third party context?

This is the quick post of how we tried a bunch of approaches, hit walls, and eventually landed on Phoenix Channels as our solution.

Hot code upgrades for Elixir and Phoenix apps

Using UUIDv7 with Ecto and PostgreSQL
postgresectoelixirphoenix

Posted on 2026-02-04 by Matt.

Postgres 18 adds support for generating UUIDv7s out of the box; no extensions required. Unfortunately, it's less obvious how to use these for the id in our Ecto schemas. But don't worry, it only requires a few small changes and no new dependencies.

Tidewave

Tidewave is the coding agent for full-stack web app development, deeply integrated with Phoenix, from the database to the UI. See our website for more information.

Phoenix LiveView Calendar with Drag-and-Drop

Markdown for Elixir _

Fast. Extensible. Phoenix-native. AI-ready.

Your Python Stack Can’t Do This

Free link here

The AI industry has a “Python Problem.”

While Python dominates model development, it’s catastrophically unsuited for agent orchestration. If you’re building an “Agent Swarm” with LangChain or AutoGPT on a Python backend, you’re fighting the Global Interpreter Lock (GIL), memory bloat, zombie processes, and concurrency nightmares.

I built a platform that actually scales. Using Elixir and the BEAM VM, I orchestrated millions of stateful, autonomous agents on a single cluster, with sub-millisecond message passing, automatic fault recovery, and zero external message queues.

BEAM OTP: Why Everyone Keeps Reinventing It

What makes BEAM and OTP different from async/await, threads, and actors. Process isolation, supervisors, and why Erlang's model keeps winning 40 years later.