Superlinear is a podcast about emerging practices for building with AI and coding agents.
Hosted by Brandon Kase and Christine Yip.
Homepage: https://superlinear.fm
Twitter: https://x.com/superlinear_fm
LinkedIn: https://www.linkedin.com/company/superline...
Brandon Kase: https://x.com/bkase_
Christine Yip: https://x.com/christinetyip
Exact, Goose, Rune: Rewrite for Speed with Coding Agents
We used coding agents to rewrite jq, a JSON tool, in Goose and measured roughly 2x the speed of jaq, its Rust counterpart, on holdout workloads on an M4. We could test an unfamiliar language without first learning to implement the port ourselves. This week Kit Langton & OpenCode released Rune and Expo released Exact. Two new Rust, cross-platform, low memory, high speed, hot-reload UI frameworks. We ported an existing native iOS app to both on desktop and iOS. We get: Native performance, ...
5 Nov 2026TRANSCRIPT
Adapting Poteto's (Creator of pstack) Statechart Skill: Catch Bugs Before Coding
Lauren Tan, creator of pstack, explains how to use statecharts to catch bugs before coding by turning counterexamples into product decisions.
Host Superlinear interviews Lauren Tan about her coding agent that revolutionizes formal verification by finding properties, selecting tools, and generating maintainable checks.
22 Oct 2026TRANSCRIPT
Pi Durable: The Missing Piece for AI Agents That Keep Working
Host Evan Higgins interviews Cloudflare's Maya Karkal about building resilient AI agents with Pi Durable and Cloudflare Durable Objects for persistent workflows.
15 Oct 2026TRANSCRIPT
How to Make Coding Agents Faster: Crabbox + 3 Fixes
Peter Steinberger and the OpenClaw team discuss optimizing coding agents by localizing work with Crabbox and implementing three key fixes to accelerate feedback loops.
7 Oct 2026TRANSCRIPT
How to Build AI Agents Like Dots, Instinct, Muse & Grok Bot
How do you build an agent like Dots, Muse, Instinct, or Grok Bot? Start high up the stack, and move down only when you need more control. YC F26-startup Agent 37 founder, Vishnu Krishnaprasad, explains when to use Hermes, OpenClaw, or Pi, why each user needs a separate sandbox, and how to turn a proven manual workflow into skills. He also demos a Dots-like agent built on Hermes. Superlinear is a podcast about emerging practices for building with AI. Hosted by Brandon Kase and Christine Yip....
2 Oct 2026TRANSCRIPT
How to Build and Verify Agent-Written Code with Bend2
Bend2 puts code and proofs in the same language, so coding agents can write both. Tests check examples. A checked proof can establish that a specific rule holds for every allowed input. This is formal verification, an additional verification layer alongside types and tests. You still need to review whether the rule captures the behavior you actually want. In this episode, we show how to choose rules worth proving, get the agent to finish the proofs, and decide where the extra effort pays of...
24 Sept 2026TRANSCRIPT
Jev and Decision Models: A New Layer for AI Agents
Your coding agent does not need a frontier LLM call for every judgment. Deciding which tests to run, which skill to load, or whether a prompt needs more context can be a bounded question. Jev and other decision models return typed choices, scores, or yes/no probabilities quickly enough to sit inside repeated workflows. A valid answer can still be wrong, so placement and fallback rules matter. We show a live prompt checker and a small, six-commit test-selection experiment, then explore agent...
18 Sept 2026TRANSCRIPT
The Fall 2026 Workflow for Starting Projects with Coding Agents
GPT-6 Astra and Fable 5.1 are changing how we start new software projects: Less harness engineering, less process, less prescribing. More deliberate steering on the few decisions that compound through the whole project. We walk through the Codex conversation of an actual project that we built: where we applied engineering judgment, what we left to the model, and how we planned verification so the agent could detect mistakes and keep building autonomously. From the first ramble to the...
11 Sept 2026
New Model Dropped? 4 Ways to De-slop Your Project
Your project still carries decisions made before the latest model arrived: tests for removed features, slow checks, outdated code, and instructions that keep accumulating. A new model is a useful prompt to revisit those decisions. Give your agent a concrete problem to investigate, then review what its proposed changes would improve or put at risk. In this episode, we cover four maintenance tasks through our own projects: pruning low-value code and tests, turning recurring mistakes into lint...
3 Sept 2026
Give Coding Agents Eyes Beyond the Chat: Screen Recordings, Session History, and Devices
Your coding agent can inspect its own chat, but it cannot see you switching between browser research, documents, local files, and devices. Screen recordings can turn that invisible work into model context effectively with video native models like Gemini. In this episode, we show how Screenpipe exposed Christine acting as the context bridge around Codex, and Brandon's workflow for recording focused work sessions, compressing them to 720p at one frame per second, splitting them into 15-minute...
28 Aug 2026TRANSCRIPT
Your Agent Isn't Bad at Design. Your Workflow Is
AI can generate a website in seconds. So why does so much AI-generated design still look generic? The problem may not be the model. It may be the workflow. In this episode, we break down three real things we built: the Superlinear website, a custom minimap for our podcast editor, and a 3D game character. We show how breaking design into intermediate steps can give you better results and more places to steer. Superlinear is a podcast about emerging practices for building with AI. Hosted by ...
18 Aug 2026
Context Hygiene for Coding Agents: Murder, Lobotomy, or Diary
A million-token context window doesn’t mean you should fill it. Every piece of information you keep in a coding agent’s active context has a cost. Not just in tokens and dollars, but in the model’s attention. In this episode, we explore context hygiene for coding agents: how to decide what deserves to stay in active context, what to move elsewhere, and when to throw context away entirely. Superlinear is a podcast about emerging practices for building with AI. Hosted by Brandon Kase and Chr...
12 Aug 2026TRANSCRIPT
Beyond Root-Level Harness Engineering: A Different Environment for Every Task
Harness engineering usually happens at the root level of a project. However, it should go much deeper. Frontend work, debugging, performance optimization, reviews, and other hard tasks can each have their own purpose-built environment, and even sub-agents inside those tasks can have different harnesses. Superlinear is a podcast about emerging practices for building with AI. Hosted by Brandon Kase and Christine Yip. Homepage: https://superlinear.fm Twitter: https://x.com/superlinear_f...
28 Jul 2026TRANSCRIPT
4 Emerging Practices in Agentic Engineering
Coding agents are becoming more capable, but getting better results increasingly depends on the systems, interfaces, and feedback loops we build around them. In this episode of the Superlinear podcast, we unpack four emerging practices in agentic engineering: → Shifting left in your agent harness → Using precise expert language to communicate intent → Choosing deliberately between MCP, CLI tools, Bash, and Code Mode → Using test oracles to help agents explore, verify, and reproduce complex ...
24 Jul 2026TRANSCRIPT
Understanding Loops and Graphs in Modern Coding Agents
When you ask Fable or GPT-5.6 Sol to complete a task, it feels like you’re talking to one agent. But behind that single conversation, the harness may be spawning multiple sub-agents, giving each one a fresh context window, running them in parallel, and passing summaries between them. You gave one prompt. It built a graph. In this episode of Superlinear, Christine Yip and Brandon Kase unpack how modern agent harnesses grow from simple agent loops into hidden graphs of sub-...
24 Jul 2026TRANSCRIPT
Point, Don't Describe: A Better Way to Work With AI Agents
Most AI workflows still happen in one-dimensional chat. But the best tools are moving toward higher-dimensional interactions: visual, spatial feedback loops where humans can point instead of describe. 00:00 Intro 00:35 Why text is “one-dimensional” and visual interfaces feel higher bandwidth 04:06 The render → annotate → translate loop 05:27 Planotator for giving feedback on plans and specs 07:00 Agentation, Claude, and Codex for frontend feedback 08:47 Building spatial feedback mode into a ...
Inside a recent episode
Exact, Goose, Rune: Rewrite for Speed with Coding Agents
Published 12 Nov 2026 · Transcript excerpt
[…] And then on the sort of lack of feature side in the language... That's something that might mean that Goose actually doesn't work. It's not a magic bullet. You can't just point it at any program and make it way faster because some of them don't fit the kinds of things that Goose improves performance on. […]
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