Superlinear

An agent that handles new GitHub issues needs to keep working through crashes, restarts, and changes in who's using it. Pi Durable gives you a foundation for building that kind of persistent workflow.

The key is separating agent state from the process running it. Cloudflare Durable Objects can give that state a shared cloud home, with execution triggered by requests and configured wakeups.

In this episode, we explain how the two fit together, use an interrupted refund to examine recovery, and look at shared chat, runtime reloads, and a phone-local agent. We also discuss what stored task state could reveal without advancing the agent.
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_fm
⁠⁠LinkedIn: ⁠⁠https://www.linkedin.com/company/superlinearfm⁠⁠
Brandon Kase: ⁠⁠https://x.com/bkase_⁠⁠
Christine Yip: ⁠⁠https://x.com/christinetyip⁠

Music licensed through Soundstripe. Code: O2UT6CCEQNH4KT0D

Your coding agent can spend more time waiting for tests and builds than writing code. As inference gets faster, tool calls can become a larger share of the wait.

Speeding up that feedback loop means examining which checks run, how they run, and where they run. Crabbox, from Peter Steinberger and the OpenClaw team, keeps agents local while expensive work runs on other machines.

In this episode, we share our experience offloading Electron tests with Crabbox, discuss the tradeoffs of selective testing and parallel verification, and look at faster tools such as Oxlint and a custom Swift linter. We also discuss which optimizations are worth the effort.
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_fm
⁠⁠LinkedIn: ⁠⁠https://www.linkedin.com/company/superlinearfm⁠⁠
Brandon Kase: ⁠⁠https://x.com/bkase_⁠⁠
Christine Yip: ⁠⁠https://x.com/christinetyip⁠

Music licensed through Soundstripe. Code: O2UT6CCEQNH4KT0D

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.

Homepage: ⁠⁠https://superlinear.fm
⁠⁠Twitter: ⁠⁠https://x.com/superlinear_fm
⁠⁠LinkedIn: ⁠⁠https://www.linkedin.com/company/superlinearfm⁠⁠
Brandon Kase: ⁠⁠https://x.com/bkase_⁠⁠
Christine Yip: ⁠⁠https://x.com/christinetyip⁠

Music licensed through Soundstripe. Code: O2UT6CCEQNH4KT0D

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 off. We uncover false proposed rules and integrate a Bend core with checked editing rules into an existing TypeScript app. You can start with one important part of your own project.

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_fm
⁠⁠LinkedIn: ⁠⁠https://www.linkedin.com/company/superlinearfm⁠⁠
Brandon Kase: ⁠⁠https://x.com/bkase_⁠⁠
Christine Yip: ⁠⁠https://x.com/christinetyip⁠

Music licensed through Soundstripe. Code: O2UT6CCEQNH4KT0D

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 routing, local Laya, and how to choose between code, a decision model, a generative model, or a human for each step. 
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_fm
⁠⁠LinkedIn: ⁠⁠https://www.linkedin.com/company/superlinearfm⁠⁠
Brandon Kase: ⁠⁠https://x.com/bkase_⁠⁠
Christine Yip: ⁠⁠https://x.com/christinetyip⁠

Music licensed through Soundstripe. Code: O2UT6CCEQNH4KT0D