Why inputs determine AI output quality

In this episode, I sit down with Professor Ras Mic for a beginner-friendly crash course on using Claude Code (and AI coding agents in general) without feeling overwhelmed by the terminal. We break down why your output is only as good as your inputs and how thinking in features + tests turns “vague app ideas” into real, shippable products. Was walks me through a better planning workflow using Claude Code’s Ask User Question Tool, which forces clarity on UI/UX decisions, trade-offs, and technical constraints before you build. We also talk about when not to use “Ralph” automation, why context windows matter, and how taste + audacity are the real differentiators in 2026 software.

Timestamps

00:00 – Intro

01:22 – Claude Code Best Practices

05:31 – Claude Code Plan Mode

09:30 – The Ask User Question Tool

14:52 – Don’t start with Ralph automation (get reps first)

16:36 – What are “Ralph loops” and why plans and documentation matter most

18:41 – Ras’s Ralph setup: progress tracking + tests + linting

23:48 – Tips & tricks: don’t obsess over MCP/skills/plugins

27:44 – Scroll-stopping software wins

Key Points

• Your results improve fast when you treat AI agents like junior engineers: clear inputs → clean outputs.

• The biggest unlock is planning in features + tests, not broad product descriptions.

• Claude Code’s Ask User Question Tool forces real clarity on workflow, UI/UX, costs, and technical decisions.

• If you haven’t shipped anything, don’t hide behind automation—build manually before using “Ralph.”

• Context management matters: long sessions can degrade quality, so restart earlier than you think.

Numbered Section Summaries

1. The Real Reason People Get “AI Slop” I frame the episode around a simple idea: if you feed agents sloppy instructions, you’ll get sloppy output. Ras explains that models are now good enough that the failure mode is usually unclear inputs, not model quality.

2. How To Think Like A Product Builder (Features First): Ras pushes a practical mindset: don’t describe “the product,” describe the features that make the product real. If you can list the core features clearly, you can actually direct an agent to build them correctly.

3. The Missing Piece: Tests Between Features: We talk about the shift from “generate code” to “build something serious.” The move is writing and running tests after each feature, so you don’t stack feature two on top of a broken feature one.

4. Why Default Planning Mode Isn’t Enough: Ras shows the standard flow: open plan mode, ask Claude to write a PRD, and get a basic roadmap. The issue is it leaves too many assumptions—especially around UI/UX and workflow details.

5. The Ask User Question Tool (The Planning Upgrade): This is the big unlock. Ras demonstrates how the Ask User Question Tool interrogates you with increasingly specific questions (workflow, cost handling, database/hosting, UI style, storage, etc.) so the plan becomes dramatically more precise.

6. Spend Time Upfront Or Pay For It Later: We connect the dots: better planning reduces back-and-forth, reduces token burn, and prevents “I built the app but it’s not what I wanted.” The interview-style planning forces trade-offs early instead of late.

7. Don’t Use Ralph Until You’ve Built Without It: Ras makes a strong case for reps: if you can’t ship something end-to-end yet, automation won’t save you—it’ll just move faster in the wrong direction. Build feature-by-feature manually first, then graduate to loops.

8. Practical Tips: Context Discipline + Taste Wins: Ras shares a few operational habits: don’t obsess over tools like MCP/plugins, keep context usage under control, and restart sessions before quality degrades. We wrap on a bigger point: in 2026, “audacity + taste” is what makes software stand out.

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