Hamel Husain hamelsmu

WonderWise → Spotify: Action Plan

Why We Got Rejected

Three problems collided:

Direct upload = wrong pipeline. Spotify has separate music vs. podcast pipelines. Uploading audio directly triggers automated review that rejects hybrid content — narration gets flagged as "not music," songs get flagged as "not a podcast."
AI-generated songs trigger copyright filters. Spotify's automated content matching (and NMPA takedown systems) flag Suno-generated music because Suno's training data included copyrighted songs. Even though our outputs are original, the audio fingerprint can match fragments in rights databases, triggering false-positive "copyright infringement" claims.
Spotify killed Music+Talk (June 2024). The one format designed for narration+music hybrids no longer exists.

Alumni Customer Research Plan

What To Do Next

Talk to 15-20 alumni. Not a survey. Not 3,000 people. Conversations.

Who to talk to

Pick from Discord based on real signals of struggle, not random selection. Segment across roles (engineer, PM, leader), company stage (startup vs. enterprise), and time since course (3+ months). Prioritize people who asked implementation questions in Discord after the course ended.

Executive Summary: Aishwarya Reganti's Free AI Evals Course vs. Hamel & Shreya's Maven Course

Overall Assessment: Highly Compatible, No Major Contradictions

The courses are complementary rather than competitive, serving different market segments with aligned principles but different depth/breadth.

Key Findings by Video

Lightning Lesson Proposal

Debug Any AI Product in Under an Hour

Hosted by Dr. Marily Nika and Hamel Husain

45 minutes | Virtual (Zoom) | Free to join

Charlotte/Runme vs JupyterLab: Architecture Comparison

This document provides a comprehensive comparison of the Charlotte/Runme notebook architecture versus JupyterLab, analyzing their fundamental design decisions, trade-offs, and the inherent capabilities that are easier or more difficult to implement in each system.

Executive Summary

Aspect	Charlotte/Runme	JupyterLab

PRD: VibeTUI — Terminal UI for Managing Coding Agent Sessions

Introduction

VibeTUI is a terminal-based user interface (TUI) for managing multiple coding agent sessions running in tmux. It provides a unified dashboard to monitor, create, and switch between sessions running Amp, Claude Code, OpenCode, and Codex. The tool is designed for developers who run multiple AI coding agents in parallel and need visibility into what each agent is doing.

VibeTUI runs on a server accessed via SSH, displaying a two-pane interface: a collapsible sidebar showing all sessions with their status, and a main pane displaying the active agent's terminal output.

Goals

Here is the final, consolidated set of 68 flashcard ideas.

I have merged the two sets as requested, which involved combining 78 cards. During this process, I consolidated 10 cards into 5 more comprehensive ones (e.g., merging "persona" testing into "tone/style," and adding code examples to the "choice of evaluator" card). I also pruned 6 cards that were redundant (e.g., duplicate cards on "how to start" or "evals vs. QA").

The bias was to consolidate new concepts into the existing 52 cards where possible, resulting in a stronger, more information-dense final set.

{
  "flashcards": [

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Hamel Husain and Shreya Shankar’s online course, AI Evals for Engineers & PMs, is the #1 highest-grossing course on Maven, and consistently brings in sizable student groups from all of the major AI labs. This is because they teach something crucial: how to build evaluations that actually improve your product, not just generate vanity dashboards.

	"""
	Minimal Air Framework Demo with Background Tasks and Server-Sent Events (SSE)
	"""
	import asyncio
	import random
	from typing import Dict
	import air

	app = air.Air()
	tasks: Dict[int, dict] = {}

	#!/usr/bin/env python3
	# /// script
	# requires-python = ">=3.9"
	# dependencies = [
	# "httpx",
	# "typer",
	# "rich",
	# ]
	# ///
	"""