AI is changing the way we all build software — that much seems clear. But the landscape is moving so fast that even the people paid to keep up are struggling. MCP or skills? Fine-tune or just prompt? LangChain or let a thousand agents loose? With almost 70 competing technologies and a shelf life of maybe six months on any advice, how do you figure out what's actually worth your time?

Henry Garner is CTO of JUXT, a consultancy with about 150 senior engineers working at the coalface of AI-assisted development, including building AI platforms for tier-one banks. JUXT publishes a quarterly AI Radar — 68 technologies rated and reviewed — and Henry's been watching his own team go through the full adoption arc, from "spicy autocomplete" skepticism through to building Byzantine-fault-tolerant distributed systems over a weekend with Claude. Along the way we cover MCP vs skills, Conway's Law for LLMs, neurosymbolic AI and the unexpected return of Prolog, the "Ralph Wiggum loop" for getting agents to converge on correct implementations, and Allium — a new behavioral specification language Henry's co-authored that sits between human prose and TLA+, aiming to give LLMs just enough structure to pin down what a system should do without falling into waterfall thinking.

If you're trying to make sense of the AI tooling landscape, or you've hit that wall where your agents keep drifting away from what you actually wanted, Henry's thesis — velocity through clarity of intent — might well help out yours.

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JUXT: https://www.juxt.pro/

JUXT AI Radar: https://www.juxt.pro/ai-radar/

Allium on GitHub: https://github.com/juxt/allium

Allium Documentation: https://juxt.github.io/allium/

Composition at a Distance (Henry's blog post): https://www.juxt.pro/blog/composition-at-a-distance/

A New Vocabulary for an Old Problem (Henry's blog post): https://www.juxt.pro/blog/new-vocabulary-for-an-old-problem/

Model Context Protocol (MCP): https://modelcontextprotocol.io/

LangChain: https://www.langchain.com/

LangGraph: https://www.langchain.com/langgraph

Gas Town (Steve Yegge): https://github.com/steveyegge/gastown

Kiro (spec-driven AI IDE): https://kiro.dev/

Phoenix (LLM observability): https://github.com/Arize-ai/phoenix

Temporal: https://temporal.io/

Taalas (LLM-on-a-chip): https://taalas.com/

Kris on Bluesky: https://bsky.app/profile/krisajenkins.bsky.social

Kris on Mastodon: http://mastodon.social/@krisajenkins

Kris on LinkedIn: https://www.linkedin.com/in/krisjenkins/

I have a theory that only bad projects get finished — good ones keep finding new things to do. Asciinema is a case in point. What started as a way to share terminal sessions with friends has, over 14 years, grown into a full suite of tools covering recording, hosting, playback, and live streaming — and been rebuilt multiple times along the way. So what does it actually take to record and replay a terminal session faithfully in a browser?

Joining us for this conversation is Marcin Kulik, Asciinema's creator. The project's architecture has passed through almost every interesting corner of software engineering: a Python recorder built around pseudo-terminals (PTY), a ClojureScript terminal emulator for the browser that hit performance limits with immutable data structures and garbage collection pressure, a move to Rust compiled to WebAssembly, a Go experiment that didn't last, and a new Rust CLI for concurrent live streaming backed by an Elixir/Phoenix server that calls Rust code via NIFs. The same Rust terminal emulator library now powers all three components — the browser player, the server, and the CLI.

If you've ever looked at those terminal animations embedded in a README and wondered what's underneath them, or if you're interested in how a passionate open-source developer navigates 14 years of language changes and rewrites, this conversation has plenty to offer.

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Asciinema: https://asciinema.org

Asciinema Docs: https://docs.asciinema.org

Asciinema CLI (GitHub): https://github.com/asciinema/asciinema

Asciinema Player (GitHub): https://github.com/asciinema/asciinema-player

Asciinema Server (GitHub): https://github.com/asciinema/asciinema-server

AVT - Rust terminal emulator library: https://github.com/asciinema/avt

vt-clj - the original ClojureScript terminal emulator: https://github.com/asciinema/vt-clj

Paul Williams' ANSI/VT100 State Machine Parser: https://vt100.net/emu/dec_ansi_parser

Rust: https://www.rust-lang.org

WebAssembly: https://webassembly.org

SolidJS: https://www.solidjs.com

Elixir: https://elixir-lang.org

Phoenix Framework: https://www.phoenixframework.org

Rustler (Rust NIFs for Elixir/Erlang): https://github.com/rusterlium/rustler

Clojure: https://clojure.org

ClojureScript: https://clojurescript.org

cmatrix: https://github.com/abishekvashok/cmatrix

Marcin Kulik on GitHub: https://github.com/ku1ik

Marcin Kulik on Mastodon: https://hachyderm.io/@ku1ik

Marcin Kulik on asciinema.org: https://asciinema.org/~ku1ik

"They're Made Out of Meat" demo: https://asciinema.org/a/746358

Kris on Bluesky: https://bsky.app/profile/krisajenkins.bsky.social

Kris on Mastodon: http://mastodon.social/@krisajenkins

Kris on LinkedIn: https://www.linkedin.com/in/krisjenkins/

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0:00 Intro

2:28 What Is Asciinema?

4:48 How Asciinema Started

9:51 The Problem of Parsing Terminal Output

14:07 Building a Cross-Platform Recorder

17:01 Rewriting the Parser in ClojureScript

22:19 The Hidden Complexity of Terminals

29:28 Rendering Terminals in the Browser

39:47 When ClojureScript Can't Keep Up

45:28 Moving to Rust and WebAssembly

52:01 The Go Experiment

57:43 Adding Live Terminal Streaming

1:07:12 Can You Scrub Back in a Live Stream?

1:14:40 Editing Recordings

1:25:27 Outro

Eighteen months ago, Tyler Cloutier appeared on the show with what sounded like an ambitious (some might say crazy) plan: build a new distributed database from scratch, then use it to power a massively multiplayer online game. That's two of the hardest problems in software, tackled simultaneously. But sometimes the best infrastructure comes from solving your own impossible problems.

The game, Bitcraft, has now launched on Steam. SpacetimeDB has hit version 1.0. And Tyler returns to share what actually happened when theory met production reality. We cover the launch day performance disasters (including a cascading failure caused by logging while holding a lock), why single-threaded execution running entirely from L1 cache can outperform sophisticated multi-threaded approaches by two orders of magnitude, and how the database's reducer model - borrowed from functional programming - enables zero-downtime code deployments. We also get into how SpacetimeDB is expanding beyond games with TypeScript support and React hooks that make building real-time multiplayer web apps surprisingly simple.

If you're building anything where multiple users need to see the same data update in real time - which, as Tyler points out, describes most successful applications from Figma to Facebook - SpacetimeDB's approach of treating every app as a multiplayer game might be worth understanding.

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SpacetimeDB: https://spacetimedb.com/

SpacetimeDB on GitHub: https://github.com/clockworklabs/SpacetimeDB

Our previous episode with Tyler: https://youtu.be/roEsJcQYjd8

Clockwork Labs: https://clockworklabs.io/

Bitcraft Online: https://bitcraftonline.com/

Bitcraft on Steam: https://store.steampowered.com/app/3454650/BitCraft_Online

WebAssembly: https://webassembly.org/

Flecs (ECS for C/C++): https://www.flecs.dev/flecs/

TigerBeetle: https://tigerbeetle.com/

CockroachDB: https://www.cockroachlabs.com/

Google Cloud Spanner: https://cloud.google.com/spanner

Erlang: https://www.erlang.org/

Apache Kafka: https://kafka.apache.org/

Tyler Cloutier on X: https://x.com/TylerFCloutier

Tyler Cloutier on LinkedIn: https://www.linkedin.com/in/tylercloutier/

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Kris on Bluesky: https://bsky.app/profile/krisajenkins.bsky.social

Kris on Mastodon: http://mastodon.social/@krisajenkins

Kris on LinkedIn: https://www.linkedin.com/in/krisjenkins/

0:00 Intro

2:01 The Architecture of SpacetimeDB

5:01 Client-Side Prediction in Multiplayer Games

11:00 Reducers and Event Streaming

15:00 Launching Bitcraft on Steam

19:00 Debugging Launch Performance Problems

26:56 Hot-Swapping Server Code Without Downtime

30:01 In-Memory Tables and Query Optimization

42:00 Is SpacetimeDB Only For Games?

51:00 Performance Benchmarking For Web Workloads

55:00 Why Single-Threaded Beats Multi-Threaded

1:00:01 Multi-Version Concurrency Control Trade-offs

1:05:01 Sharding Data Across Multiple Nodes

1:10:56 Inter-Module Communication and Actor Models

1:17:00 Replication and the Write-Ahead Log

1:24:00 Supported Client Languages

1:29:00 Getting Started With SpacetimeDB

1:39:02 Outro