“AutoResearch-based AutoAgent, evolved by Andrew Cupsy, uses a for-loop running program.mmd through Cloud Code or Codeex to self-improve the agent harness and achieved #1 on both the spreadsheet and terminal branches.”

#9 ▶️ Okay, this unleashed my agent AI Jason Breaks down Cloud Code’s three-layer memory system (hot in cloud.md, warm in memory.md, and background autodream consolidation) and Herb’s agent’s autonomous skill and memory reviewer sub-agents to enable AI agents that self-evolve over time. AutoResearch-based AutoAgent, evolved by Andrew Cupsy, uses a for-loop running program.mmd through Cloud Code or Codeex to self-improve the agent harness and achieved #1 on both the spreadsheet and terminal branches. Cloud Code’s auto-memory feature writes memory files into a project-local .cloud_code/memory folder indexed in memory.md (hot memory), retrieves them on demand as warm memory, and runs an asynchronous autodream process to consolidate and update outdated entries after each session. Herb’s agent spawns a Skill Reviewer sub-agent after 10 uninterrupted steps to auto-generate or patch skills via a Skill Manager with a Python-based safety scan and a Memory Reviewer agent every 10 turns to extract persona and project facts into user.md and memory.md (each capped at ~4,000 characters).

“Leverages agent-engineering tools Claude Code, Codeex, and Google AI Studio to auto-generate comprehensive code in minutes.”

#9 ▶️ 23 AI Trends keeping me up at night Greg Isenberg Explains how to use ideabrowser.com and AI agent engineering platforms like Claude Code, Codeex, and Google AI Studio to build, launch, and acquire a first customer for a startup in under one hour. Grabs a validated idea from ideabrowser.com by 9:00 a.m., completes a basic build by 9:15 a.m., finishes an MVP by 9:45 a.m., and lands the first customer by 10:00 a.m. Leverages agent-engineering tools Claude Code, Codeex, and Google AI Studio to auto-generate comprehensive code in minutes. Secures payment with Stripe and uses an existing email list or audience to convert the first customer within one hour of ideation.

“He launches 3–5 parallel Claude Code “explore” sub-agents to gather context, generates a spinner wheel flowchart in Flowy (animation timing adjusted from 3 000 ms to 4 000 ms), then commands Claude Code to build the feature (passing TypeScript checks) and uses Codeex (alias “Carl”) on the git diff to catch a pointer-dot misalignment and suggest refactoring into components and constants.”

#5 ▶️ DIY dev tools: How this engineer created “Flowy” to visualize his plans and accelerate coding How I AI Podcast CJ Hess uses his custom tool Flowy with Claude Code skills to transform JSON definitions into interactive flowcharts and intermediate-fidelity UI mockups that guide AI-assisted feature planning and coding. Flowy parses JSON files in a “flowy” folder—defining nodes, edges, style properties and icons—to render browser-based flowcharts and UI mockups, with an integrated editor that saves edits back to JSON. CJ Hess created three Flowy Claude Code skills in Markdown (overview, flowchart, UI mockup) and iteratively refined them by prompting Claude to fix layout spacing, pastel note text contrast, and add a semantic color system. He launches 3–5 parallel Claude Code “explore” sub-agents to gather context, generates a spinner wheel flowchart in Flowy (animation timing adjusted from 3 000 ms to 4 000 ms), then commands Claude Code to build the feature (passing TypeScript checks) and uses Codeex (alias “Carl”) on the git diff to catch a pointer-dot misalignment and suggest refactoring into components and constants.