Scaling AI-Assisted Development

Today we discuss lessons from our previous episode with John Nunemaker, focusing on the Conductor tool and how multi-workspace, multi-agent workflows can speed up coding and bug fixing. Brendan shares his experimenting with parallelizing six Rollbar error fixes at once by generating prompts and running them in separate Conductor workspaces. They compare this with a one-agent-at-a-time workflow and debate whether closed-loop setups (ports, databases, dependencies) could make parallel work trustworthy and reduce context-switching costs. They also cover using full Honeybadger/XML reports for faster debugging, using Claude Code from a phone to create PRs, challenges syncing session history, and broader AI product strategy like APIs/MCP, and RAG. 00:00 Catch Up And Recap 00:43 Conductor Workflow Overview 02:40 Parallel Rollbar Fixes 04:35 Manual Testing And Setup Hurdles 06:33 Debugging With Full Reports 08:46 Ports Docker And Dependencies 11:50 Parallelism Versus Focus 14:57 Closed Loop Trust And Context 18:24 Merge Conflicts And Acceptance Gaps 22:16 Review Bottleneck And Output Surge 25:26 Fixing Gallery Uploads 26:39 Multi Select Challenges 28:27 Branching Without Conductor 31:28 Claude Mobile Workflow 32:34 Session Sync Friction 34:44 AI Brain For SaaS 38:01 APIs And MCP Table Stakes 41:49 Internal AI Assistants 43:46 Access And Safety Concerns 46:31 Second Brain Revival 49:03 RAG Tooling Experiments 50:04 Wrap Up And Listener Feedback LINKS - Ryan's Website - Brendan's X/Twitter - Brendan's Bluesky Questions or comments, email us at railsbusinesspod@gmail.com Send us Fan Mail