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by Kris Jenkins
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- Mar 26, 20261h 40m
What's Worth Knowing In AI Right Now? (with Henry Garner)
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. -- Support Developer Voices on Patreon: https://patreon.com/DeveloperVoices Support Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/join 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/
- Feb 19, 20261h 26m
Asciinema: Terminal Recording Done Right (with Marcin Kulik)
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. --- Support Developer Voices on Patreon: https://patreon.com/DeveloperVoices Support Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/join 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/ --- 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
- Feb 4, 20261h 41m
Building the SpacetimeDB Database, Game-First (with Tyler Cloutier)
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. -- Support Developer Voices on Patreon: https://patreon.com/DeveloperVoices Support Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/join 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/ -- 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
- Dec 11, 20251h 51m
Will Turso Be The Better SQLite? (with Glauber Costa)
SQLite is embedded everywhere - phones, browsers, IoT devices. It's reliable, battle-tested, and feature-rich. But what if you want concurrent writes? Or CDC for streaming changes? Or vector indexes for AI workloads? The SQLite codebase isn't accepting new contributors, and the test suite that makes it so reliable is proprietary. So how do you evolve an embedded database that's effectively frozen? Glauber Costa spent a decade contributing to the Linux kernel at Red Hat, then helped build Scylla, a high-performance rewrite of Cassandra. Now he's applying those lessons to SQLite. After initially forking SQLite (which produced a working business but failed to attract contributors), his team is taking the bolder path: a complete rewrite in Rust called Turso. The project already has features SQLite lacks - vector search, CDC, browser-native async operation - and is using deterministic simulation testing (inspired by TigerBeetle) to match SQLite's legendary reliability without access to its test suite. The conversation covers why rewrites attract contributors where forks don't, how the Linux kernel maintains quality with thousands of contributors, why Pekka's "pet project" jumped from 32 to 64 contributors in a month, and what it takes to build concurrent writes into an embedded database from scratch. -- Support Developer Voices on Patreon: https://patreon.com/DeveloperVoices Support Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/join Turso: https://turso.tech/ Turso GitHub: https://github.com/tursodatabase/turso libSQL (SQLite fork): https://github.com/tursodatabase/libsql SQLite: https://www.sqlite.org/ Rust: https://rust-lang.org/ ScyllaDB (Cassandra rewrite): https://www.scylladb.com/ Apache Cassandra: https://cassandra.apache.org/ DuckDB (analytical embedded database): https://duckdb.org/ MotherDuck (DuckDB cloud): https://motherduck.com/ dqlite (Canonical distributed SQLite): https://canonical.com/dqlite TigerBeetle (deterministic simulation testing): https://tigerbeetle.com/ Redpanda (Kafka alternative): https://www.redpanda.com/ Linux Kernel: https://kernel.org/ Datadog: https://www.datadoghq.com/ Glauber Costa on X: https://x.com/glcst Glauber Costa on GitHub: https://github.com/glommer 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 3:16 Ten Years Contributing to the Linux Kernel 15:17 From Linux to Startups: OSv and Scylla 26:23 Lessons from Scylla: The Power of Ecosystem Compatibility 33:00 Why SQLite Needs More 37:41 Open Source But Not Open Contribution 48:04 Why a Rewrite Attracted Contributors When a Fork Didn't 57:22 How Deterministic Simulation Testing Works 1:06:17 70% of SQLite in Six Months 1:12:12 Features Beyond SQLite: Vector Search, CDC, and Browser Support 1:19:15 The Challenge of Adding Concurrent Writes 1:25:05 Building a Self-Sustaining Open Source Community 1:30:09 Where Does Turso Fit Against DuckDB? 1:41:00 Could Turso Compete with Postgres? 1:46:21 How Do You Avoid a Toxic Community Culture? 1:50:32 Outro
- Nov 20, 20251h 5m
Can Google's ADK Replace LangChain and MCP? (with Christina Lin)
How do you build systems with AI? Not code-generating assistants, but production systems that use LLMs as part of their processing pipeline. When should you chain multiple agent calls together versus just making one LLM request? And how do you debug, test, and deploy these things? The industry is clearly in exploration mode—we're seeing good ideas implemented badly and expensive mistakes made at scale. But Google needs to get this right more than most companies, because AI is both their biggest opportunity and an existential threat to their search-based business model. Christina Lin from Google joins us to discuss Agent Development Kit (ADK), Google's open-source Python framework for building agentic pipelines. We dig into the fundamental question of when agent pipelines make sense versus traditional code, exploring concepts like separation of concerns for agents, tool calling versus MCP servers, Google's grounding feature for citation-backed responses, and agent memory management. Christina explains A2A (Agent-to-Agent), Google's protocol for distributed agent communication that could replace both LangChain and MCP. We also cover practical concerns like debugging agent workflows, evaluation strategies, and how to think about deploying agents to production. If you're trying to figure out when AI belongs in your processing pipeline, how to structure agent systems, or whether frameworks like ADK solve real problems versus creating new complexity, this episode breaks down Google's approach to making agentic systems practical for production use. -- Support Developer Voices on Patreon: https://patreon.com/DeveloperVoices Support Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/join Google Agent Development Kit Announcement: https://developers.googleblog.com/en/agent-development-kit-easy-to-build-multi-agent-applications/ ADK on GitHub: https://google.github.io/adk-docs/ Google Gemini: https://ai.google.dev/gemini-api Google Vertex AI: https://cloud.google.com/vertex-ai Google AI Studio: https://aistudio.google.com/ Google Grounding with Google Search: https://cloud.google.com/vertex-ai/generative-ai/docs/grounding/overview Model Context Protocol (MCP): https://modelcontextprotocol.io/ Anthropic MCP Servers: https://github.com/modelcontextprotocol/servers LangChain: https://www.langchain.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/
- Oct 31, 20251h 11m
Building Observable Systems with eBPF and Linux (with Mohammed Aboullaite)
How do you monitor distributed systems that span dozens of microservices, multiple languages, and different databases? The old approach of gathering logs from different machines and recompiling apps with profiling flags doesn't scale when you're running thousands of servers. You need a unified strategy that works everywhere, on every component, in every language—and that means tackling the problem from the kernel level up. Mohammed Aboullaite is a backend engineer at Spotify, and he joins us to explore the latest in continuous profiling and observability using eBPF. We dive into how eBPF lets you programmatically peek into the Linux kernel without recompiling it, why companies like Google and Meta run profiling across their entire infrastructure, and how to manage the massive data volumes that continuous profiling generates. Mohammed walks through specific tools like Pyroscope, Pixie, and Parca, explains the security model of loading code into the kernel, and shares practical advice on overhead thresholds, storage strategies, and getting organizational buy-in for continuous profiling. Whether you're debugging performance issues, optimizing for scale, or just want to see what your code is really doing in production, this episode covers everything from packet filters to cultural changes in service of getting a clear view of your software when it hits production. --- Support Developer Voices on Patreon: https://patreon.com/DeveloperVoices Support Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/join eBPF: https://ebpf.io/ Google-Wide Profiling Paper (2010): https://research.google.com/pubs/archive/36575.pdf Google pprof: https://github.com/google/pprof Continuous Profiling Tools: Pyroscope (Grafana): https://grafana.com/oss/pyroscope/ Pixie (CNCF): https://px.dev/ Parca: https://www.parca.dev/ Datadog Continuous Profiler: https://www.datadoghq.com/product/code-profiling/ Supporting Technologies: OpenTelemetry: https://opentelemetry.io/ Grafana: https://grafana.com/ New Relic: https://newrelic.com/ Envoy Proxy: https://www.envoyproxy.io/ Spring Cloud Sleuth: https://spring.io/projects/spring-cloud-sleuth Mohammed Aboullaite: LinkedIn: https://www.linkedin.com/in/aboullaite/ GitHub: https://github.com/aboullaite Website: http://aboullaite.me Twitter/X: https://twitter.com/laytoun 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/
- Oct 9, 20251h 11m
Solving Git's Pain Points with Jujutsu (with Martin von Zweigbergk)
Git might be the most ubiquitous tool in software development, but that doesn't mean it's perfect. What if we could keep Git compatibility while fixing its most frustrating aspects—painful merges, scary rebases, being stuck in conflict states, and the confusing staging area? This week we're joined by Martin von Zweigbergk, creator of Jujutsu (JJ), a Git-compatible version control system that takes a fundamentally different approach. Starting from a simple idea—automatically snapshotting your working copy—Martin has built a tool that reimagines how we interact with version control. We explore the clever algebra behind Jujutsu's conflict handling that lets you store conflicts as commits and move freely through your repository even when things are broken. We discuss why there's no staging area, how the operation log gives you powerful undo/redo capabilities, and why rebasing becomes trivially easy when you can edit any commit in your history and have changes automatically propagate forward. Whether you're a Git power user frustrated by interactive rebases, someone who's lost work to a botched merge, or just curious about how version control could work differently, this conversation offers fresh perspectives on a tool we all take for granted. And if you're working with large monorepos or game development assets, Martin's vision for the future of Jujutsu might be exactly what you've been waiting for. --- Support Developer Voices on Patreon: https://patreon.com/DeveloperVoices Support Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/join Jujutsu (JJ): https://github.com/martinvonz/jj Jujutsu Documentation: https://martinvonz.github.io/jj/ Git: https://git-scm.com/ Mercurial: https://www.mercurial-scm.org/ Rust: https://www.rust-lang.org/ Watchman: https://facebook.github.io/watchman/ Google Piper: https://research.google/pubs/why-google-stores-billions-of-lines-of-code-in-a-single-repository/ 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/
- Sep 24, 20251h 5m
Getting New Technology Adopted (with Dov Katz)
Getting new technology adopted in a large organization can feel like pushing water uphill. The best tools in the world are useless if we're not allowed to use them, and as companies grow, their habits turn into inertia, then into "the way we've always done things." So how do you break through that resistance and get meaningful change to happen? This week's guest is Dov Katz from Morgan Stanley, who specializes in exactly this challenge - driving developer productivity and getting new practices adopted across thousands of developers. We explore the art of organizational change from every angle: How do you get management buy-in? How do you build grassroots developer enthusiasm? When should you use deterministic tools like OpenRewrite versus AI-powered solutions? And what role does open source play in breaking down the walls between competing financial institutions? Whether you're trying to modernize a legacy codebase, reduce technical debt, or just get your team to try that promising new tool you've discovered, this conversation offers practical strategies for navigating the complex dynamics of enterprise software development. Because sometimes the hardest part of our job isn't writing code - it's getting permission to write better code. --- Support Developer Voices on Patreon: https://patreon.com/DeveloperVoices Support Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/join Morgan Stanley: https://www.morganstanley.com/ OpenRewrite: https://docs.openrewrite.org/ Spring Framework: https://spring.io/ Spring Integration: https://spring.io/projects/spring-integration Apache Camel: https://camel.apache.org/ FINOS (FinTech Open Source Foundation): https://www.finos.org/ Linux Foundation: https://www.linuxfoundation.org/ Moderne (Code Remix conference organizers): https://www.moderne.io/ Code Remix Conference: https://www.moderne.io/events 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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About Developer Voices
Deep-dive discussions with the smartest developers we know, explaining what they're working on, how they're trying to move the industry forward, and what we can learn from them.You might find the solution to your next architectural headache, pick up a new programming language, or just hear some good war stories from the frontline of technology.Join your host Kris Jenkins as we try to figure out what tomorrow's computing will look like the best way we know how - by listening directly to the developers' voices.
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