Conductor CEO Charlie Holtz Walks Us Through His AI Coding Setup
The founder of an AI agent orchestrator explains how he uses his own product to build his own product and why code is becoming sawdust.
June 4thA 17-minute field report from a solo indie developer who wired his AI agents directly into his simulator, browser, crash tracker, and code review system — and stopped babysitting them.
Giving AI coding agents direct access to the simulator, browser, and telemetry tools they need to verify their own fixes eliminates the manual feedback loop that makes solo development slow.
The highest-leverage change in this workflow is closing the verification loop: instead of fixing a bug and then manually checking it, you give Claude Code an iOS simulator via Xcode Build MCP or a Chrome instance via --chrome so it can test its own changes and keep looping until they pass. The same logic applies to production debugging — connecting Sentry, Supabase, and Axiom as CLIs or MCPs lets the agent investigate a crash report in three minutes instead of 45. For code review, Greptile auto-grades every PR and Claude Code is told to iterate until it hits a 5/5. The tool layer runs on cMux (low RAM, sidebar, notifications) and the model setting is Opus 4.7 at max thinking for most tasks, with GPT-5.5 extra-high reserved for complex multi-file bugs where Opus tends to fix one thing and break two others.
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Sets up the video as an advanced update. Declares 70/30 split: Opus 4.7 in Claude Code vs GPT-5.5 in Cursor.

Xcode Build MCP lets Claude Code control the iOS simulator: build, tap, screenshot, read logs. Keeps Xcode closed 90% of the time.

claude --chrome gives Claude a live Chrome instance. Cursor has a built-in browser. Old manual loop diagram vs. new autonomous loop.

Sentry CLI, Supabase MCP, Axiom CLI all wired into Claude Code. Crash investigation drops from 45 minutes to 3. CLI preferred over MCP for token efficiency.

Sponsored. Every PR auto-reviewed and scored 1-5. Claude Code loops until 5/5. Beat Cursor BugBot across 60 real PRs.

/remote-control syncs session to the Claude mobile app. Boris (Claude Code creator) called this his top hack. Config tip: auto-start on launch.

Project sidebar, per-instance notifications, runs 20 Claude Code instances on 64GB M4 Max without issue vs. 5 instances choking in Cursor.

Opus 4.7 + max thinking on $200/mo plan. Flag to auto-start max thinking. Most people complaining about quality are on Sonnet medium.

CLAUDE_CODE_NO_FLICKER=1 beta flag: pinned input bar, clickable cursor position.

Complex multi-file bugs where Opus fixes one thing and breaks two others. GPT-5.5 extra-high at 1M context wins here. Burns Cursor Ultra credits fast.

Has the $100/mo plan but prefers Cursor UX. Will revisit if Codex iOS app ships.

Four-point summary: automated testing, MCPs/CLIs, Greptile, slash config. Ends with dog cameo.
The reason AI coding agents stall is not that they are not smart enough — it is that they cannot see whether their fix worked, so they stop and wait for a human who is not there.
“I let Claude code run for like twenty, thirty minutes, and then by the time I get back, the issue is fixed.”
“The old me would spend an hour digging through logs... now Claude Code does it in like three minutes.”
“Over half the time they have it set to SONNET and medium thinking. And I tell them, okay, well, that's why.”
“GPT-5.5 extra high, 1,000,000 context window is better than Opus 4.7 max thinking at majority of tasks, especially if the task is very complex.”
“$400 a month in AI tooling, but because I make a living building apps, that cost is totally worth it.”
See every word as it's spoken — crank it to 2× and still catch all of it. The same dual-channel trick behind Amazon's Kindle + Audible.
Chris Raroque builds productivity apps solo and ships PRs every day — and for months, every fix meant a manual loop: implement, switch to Xcode, run simulator, check, screenshot, paste back, repeat. This video is about what replaced that loop: AI agents that test their own work, review their own PRs, and keep iterating until the job is done.
Instead of the developer verifying each agent fix manually, the agent is given the tools to verify its own work and instructed to keep looping until it passes.
Replaces human code review for a solo developer by chaining AI code review with AI remediation until a quality threshold is met.
When a service offers both a CLI and an MCP, prefer the CLI: it uses fewer context window tokens and agents navigate it more reliably.
“if you like this content, check out my Instagram and TikTok. I post almost every other day about building productivity apps. And obviously if you like this content, don't forget to subscribe.”
Soft and personal. Directs to social channels before subscribe ask. No aggressive pitch.
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17:00The founder of an AI agent orchestrator explains how he uses his own product to build his own product and why code is becoming sawdust.
June 4thAlex Finn distills Boris Czerny's X thread into 7 executable Claude Code workflow steps — from parallel terminals to end-of-session verification.
January 6thThe engineer who built Claude Code explains how he ships 20-30 pull requests a day without writing a single line by hand.
March 4thJosh Pigford built and sold Baremetrics, now runs five AI products solo — and his Claude Code skill stack is the most systematic one on record.
May 31stA 13-minute sprint through 27 production habits distilled from 500+ hours inside Claude Code.
March 29thEverything you need to know about Claude Code skills — what they are, how they load, how to trigger them, and how to build benchmarked custom ones — in under ten minutes.
March 16th