The Startup Ideas Podcast

I sit down with Morgan Linton, Cofounder/CTO of Bold Metrics, to break down the same-day release of Claude Opus 4.6 and GPT-5.3 Codex. We walk through exactly how to set up Opus 4.6 in Claude Code, explore the philosophical split between autonomous agent teams and interactive pair-programming, and then put both models to the test by having each one build a Polymarket competitor from scratch, live and unscripted. By the end, you'll know how to configure each model, when to reach for one over the other, and what happened when we let them race head-to-head.

Timestamps

00:00 – Intro

03:26 – Setting Up Opus 4.6 in Claude Code

05:16 – Enabling Agent Teams

08:32 – The Philosophical Divergence between Codex and Opus

11:11 – Core Feature Comparison (Context Window, Benchmarks, Agentic Behavior)

15:27 – Live Demo Setup: Polymarket Build Prompt Design

18:26 – Race Begins

21:02 – Best Model for Vibe Coders

22:12 – Codex Finishes in Under 4 Minutes

26:38 – Opus Agents Still Running, Token Usage Climbing

31:41 – Testing and Reviewing the Codex Build

40:25 – Opus Build Completes, First Look at Results

42:47 – Opus Final Build Reveal

44:22 – Side-by-Side Comparison: Opus Takes This Round

45:40 – Final Takeaways and Recommendations

Key Points

Opus 4.6 and GPT-5.3 Codex dropped within 18 minutes of each other and represent two fundamentally different engineering philosophies — autonomous agents vs. interactive collaboration.

To use Opus 4.6 properly, you must update Claude Code to version 2.1.32+, set the model in settings.json, and explicitly enable the experimental Agent Teams feature.

Opus 4.6's standout feature is multi-agent orchestration: you can spin up parallel agents for research, architecture, UX, and testing — all working simultaneously.

GPT-5.3 Codex's standout feature is mid-task steering: you can interrupt, redirect, and course-correct the model while it's actively building.

In the live head-to-head, Codex finished a Polymarket competitor in under 4 minutes; Opus took significantly longer but produced a more polished UI, richer feature set, and 96 tests vs. Codex's 10.

Agent teams multiply token usage substantially — a single Opus build can consume 150,000–250,000 tokens across all agents.

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com

LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/

The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

Morgan Linton

X/Twitter: https://x.com/morganlinton

Bold Metrics: https://boldmetrics.com

Personal Website: https://linton.ai

I sit down with Matt Van Horn, creator of the "Last 30 Days" skill for Claude Code, as he demonstrates how this tool turns anyone into a real-time research expert. By pulling trending data from X, Reddit, and the web, Last 30 Days supercharges Claude Code prompts with current intelligence. Matt walks through live demos, from discovering popular rap songs to generating cold emails to building a Moltbot competitor, showing how non-engineers can ship products using AI tools with almost no coding background.

Timestamps

00:00 – Intro

01:39 – What Is "Last 30 Days"

03:29 – Live Demo: Most Popular Rap Songs

04:47 – Cold Email Frameworks Demo

07:04 – Growing an X Following Using Recent Data

07:49 – Researching Moltbot to Build a Competitor

08:26 – Best Practices for Last 30 days

09:26 – Growing an X Following Using Recent Data Results

11:17 – Best Practices for Webdesign Research

13:44 – Building an Enterprise Moltbot Clone Live

17:43 – Generating Figma Prompts and Nano Banana Images

21:54 – Advice for Non-Engineers Getting Started with Claude Code

Links Mentioned:

Last 30 Days Skill: https://startup-ideas-pod.link/last30days

Key Points

Last 30 Days searches X, Reddit, and the web for content from the past month, creating highly optimized prompts for Claude Code.

The tool requires Claude Code access, an OpenAI API key (for Reddit data), and an XAI key (for X/Twitter access).

Matt demonstrates using minimal prompts to generate cold email frameworks, research trending topics, and kickstart new product builds.

Compound Engineering serves as a planning tool to turn research into structured project roadmaps.

Non-engineers can ship functional products by combining Claude Code with ChatGPT for troubleshooting errors via screenshots.

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com

LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/

The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

Matt Van Horn

X/Twitter: https://x.com/mvanhorn

I sit down with Kevin Rose for a live screen share where he walks me through “Nylon,” a personal Techmeme-style news engine he vibe-coded to track AI and tech stories. He breaks down how he pulls from RSS, enriches articles with tools like iFramely, Firecrawl, and Gemini, then generates TLDRs and vector embeddings to cluster stories with real nuance. We dig into his “gravity engine,” an editorial scoring system that ranks stories by impact, novelty, and builder relevance. The bigger theme is simple: with today’s models and workflows, a solo builder can ship wild, high-leverage software fast, then refine by cutting features down to the few that matter.

Timestamps:

00:00 – Intro And What Kevin Plans To Demo

03:10 – Techmeme Breakdown And How Signal Gets Ranked

06:44 – RSS Sources, Ingestion, And The Article Pipeline

11:23 – Winner Selection: RSS vs iFramely vs Firecrawl vs Gemini

13:01 – Why iFramely And Firecrawl, Explained

16:37 – TLDRs, Vector Embeddings, And Why They Beat Keyword Search

19:49 – Task Orchestration With trigger.dev And Retries

24:58 – Clusters: Expanding With Search APIs And Discovery

27:07 – The Gravity Engine: Editorial Scoring Rubric

31:31 – Product Management: Gut, Iteration, And Cutting Features

34:53 – Synthetic Audiences And Personal Software

37:03 – What “Success” Looks Like

43:52 – Retention Mechanics And The Idea Browser Example

47:19 – “Blurred Presence” Blog Project From A 12-Year-Old Idea

50:34 – This the best time to build

51:55 – How To Work With Kevin, DIGG Reboot, And VC Today

Keypoints

I watch Kevin’s end-to-end pipeline for turning messy RSS links into clean, enriched, clustered stories.

Kevin uses a “winner” judge to pick the best source of truth per field (summary, main content, metadata).

Vector embeddings plus clustering unlock meaning-level grouping that keyword search misses.

trigger.dev gives durable background jobs, retries, and observability for a solo builder workflow.

His “gravity engine” acts like an editorial layer that prioritizes novelty, impact, and builder relevance.

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com

LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/

The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

Kevin Rose: x: https://x.com/kevinrose

personal website: https://www.kevinrose.com/about

Youtube: https://www.youtube.com/@KevinRose

I sit down with Kitze to unpack how he uses Clawdbot as a personal OS that runs across Discord, Telegram, and other chat surfaces. We walk through his one-gateway setup, persona-based bots, and the way he structures channels and threads to manage customers, home logistics, and engineering work. We also dig into the self-learning angle: giving an agent shell and network access so it can discover devices, build dashboards, and automate workflows end to end. We close with a lightning round of concrete examples you can adapt across your own life and business.

Timestamps

00:00 – Intro

01:42 – The Personal OS Idea

04:20 – Persona Design for Clawdbot

06:00 – Discord As The Control Center

08:23 – Self-Learning Through Shell And Network Access

09:23 – Discord Threads And Agent Workflows

10:13 – Platform Choices: Telegram, Discord, Slack

11:47 – Email Automation, Security, And Model Selection

15:07 – How Agents Change Work

18:00 – Lightning Round of Clawdbot use cases

27:09 – Spellbook: Variable-Driven Prompt Templates

29:15 – Closing Thoughts

Key Points

I treat Clawdbot like a gateway that routes the same core agent into many persona shells for distinct jobs

I keep work organized via Discord sections, channels, and threads so agent output stays searchable

I lean on shell and network access to let the agent discover devices and ship automations that span apps, NAS, and smart home

I use stronger models for high-trust surfaces like email and credentials, and I scope access gradually

I prototype interfaces that turn prompts into parameterized forms so workflows stay reusable and fast

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com

LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/

The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

FIND KITZE ON SOCIAL

X/Twitter: https://x.com/thekitze

Tinkerer Club: https://tinkerer.club

Personal Website:  https://www.kitze.io

I sit down with Alex Finn to break down how he sets up Moltbot (formally Clawdbot) as a proactive AI employee he treats like a teammate named Henry. We walk through the core workflow: Henry sends a daily morning brief, researches while Alex sleeps, and ships work as pull requests for review. Alex explains the setup that makes this work; feeding the bot deep personal and business context, then setting clear expectations for proactive behavior. We cover model strategy (Opus as “brain,” Codex as “muscle”), a “Mission Control” task tracker Henry built, hardware options, and the security mindset around prompt injection and account access.

Timestamps

00:00 – Intro

02:08 – Clawdbot Overview

03:33 – The Morning Brief Workflow

05:01 - Proactive Builds: Trends → Features → Pull Requests

07:27 – The Setup: Context + Expectations For Proactivity

09:38 – The Onboarding Prompt Alex Uses

12:05 – Hunting “Unknown Unknowns” For Real Leverage

12:43 – Using the right Models for cost control

14:18 – Mission Control: A Kanban Tracker Henry Built

17:16 – The future of Human and AI workflow

22:01 – Hardware And Hosting: Cloud vs Local (Mac Mini/Studio)

25:47 – The Productivity Framework

27:10 – The Possible Evolution of Clawdbot

28:53 – Security and Privacy Concerns

33:38 – Closing Thoughts: Tinkering, Opportunity, And Next Steps

Key Points

I get the most leverage when I treat the agent like a proactive teammate with clear expectations and rich context.

Henry delivers compounding value by shipping work for review (pull requests) based on trend monitoring and conversation memory.

I separate “brain” and “muscle” by delegating heavy coding to Codex while using Opus for reasoning and direction.

I track autonomous work with a dedicated “Mission Control” board so progress stays visible over time.

I keep risk contained by controlling environment and account access, especially around email and prompt injection.

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com

LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/

The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

FIND ALEX ON SOCIAL

Youtube: https://www.youtube.com/@AlexFinnOfficial/videos

X/Twitter: https://x.com/AlexFinnX

Creator Buddy: https://www.creatorbuddy.io/