How I AI

I got a few hours of early-access testing with Anthropic’s newly released model Opus 4.8. I walk through real coding, design, and strategy tasks across Claude Code and Claude Cowork, and give you my unfiltered view on what impressed me and what didn’t.
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What you’ll learn:
Where Opus 4.8 excels: greenfield prototypes, one-shot features, and fast execution
Where it struggles: the last 10%, edge cases in existing codebases, and hallucinations
How Opus 4.8 compares to Opus 4.7 on business strategy work
Why I’m still reaching for Opus 4.7 on data-heavy strategy and roadmap work
The new features shipping alongside the model: dynamic workflows with parallel subagents and effort control in Claude.ai and Cowork
The prompting and harness strategy I’d use to get the most out of it
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In this episode, we cover:
(00:00) Introduction to Opus 4.8 
(00:44) Benchmark performance and pricing
(01:53) First coding test: Building a prototyping tool
(03:00) Where it failed: The last 10% problem
(03:27) The hallucination problem
(04:23) Testing Opus 4.8 on existing codebases
(05:24) The ambition test: Building games for a 9-year-old
(07:03) Business strategy test: 4.7 vs 4.8
(08:23) The roadmap test
(09:17) Final verdict
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References:
• System Card: Claude Opus 4.8: https://cdn.sanity.io/files/4zrzovbb/website/c886650a2e96fc0925c805a1a7ca77314ccbf4a6.pdf
• Introducing Claude Opus 4.8 on X: https://x.com/claudeai/status/2060042702150930686?s=20
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Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

In this 30-minute episode, I walk through my favorite feature in Codex: the /goal command. I show how Goals transform AI from a turn-based assistant that needs constant ‘what’s next?’ prompting into an autonomous agent that can work for hours on complex, multi-step tasks. I share three real examples: eliminating thousands of Sentry errors, cleaning 3,900 emails down to 68, and organizing hundreds of Linear tasks.

What you’ll learn:
What Goals are and how they differ from standard prompts
How I used /goal to eliminate hundreds of error logs in my codebase over a five-hour autonomous run
The non-technical use cases that make Goals incredibly powerful: cleaning up 3,900 emails in under four hours and organizing hundreds of project management tasks in Linear
How to write effective /goal prompts with measurable outcomes, verification methods, and constraints
When not to use Goals and what makes a strong versus weak Goal
Why Goals represent a fundamental shift in how we work with AI, from babysitting the model to managing it
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Brought to you by:
Mercury—Radically different banking loved by over 300K entrepreneurs
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In this episode, we cover:
(00:00) Introduction
(01:50) What is /goal and when should you use it?
(02:45) The difference between prompts and Goal-based loops
(04:06) Claire’s first five-hour 45-minute autonomous coding task
(05:05) How to manage a Goal lifecycle: view, pause, resume, and clear
(06:06) How to write strong goals: outcomes vs. outputs
(07:34) The six components of effective Goals
(08:57) Example: Reducing P95 checkout latency with /goal
(09:36) Demo: Using /goal to eliminate Sentry errors in ChatPRD
(13:18) Demo: Burning down Vercel API errors
(17:28) Non-technical use case: Cleaning 3,900 emails with /goal
(21:24) Demo: Using /goal to clean up Linear project tasks
(24:41) When not to use /goal
(26:10) Why /goal changes everything
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Tools referenced:
• Codex: https://openai.com/codex/
• Sentry: https://sentry.io/
• Vercel: https://vercel.com/
• Linear: https://linear.app/
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Other reference:
• OpenAI blog post “Using Goals in Codex”: https://developers.openai.com/cookbook/examples/codex/using_goals_in_codex
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Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

Felix Rieseberg is the engineering lead for Claude Cowork and Claude Code Desktop at Anthropic. He previously spent five years at Slack building developer tools. In this episode, Felix demonstrates how he uses Claude to solve real-life problems: analyzing floor plans to build interactive 3D house walkthroughs, automatically tracking promises he makes on Twitter, and building a $20 hardware device that physically approves Claude actions with a button press.

What you’ll learn:
How to use Claude Cowork to turn a 2D floor plan into an interactive 3D walkthrough where you can move furniture around
The “go one abstraction layer up” philosophy: why you should never manually enter data Claude can find itself
How to use your email as an inventory database for furniture, clothing, and personal purchases
When to use Opus vs. Sonnet 4.6 (hint: it’s about how well you can scope the problem, not technical complexity)
How live artifacts work and why they’re powerful for dashboards that refresh with real-time data from your connectors
The product philosophy behind making latency delightful
How to build your own $20 hardware device using Claude Code (no hardware experience required)
Why Felix never reads the code Claude writes and judges it purely on output
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Brought to you by:
Magic Patterns—Prototypes that look like your product
Guru—The AI layer of truth
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In this episode, we cover:
(00:00) Introduction to Felix Rieseberg
(02:40) Felix’s role at Anthropic
(03:25) The multiple tabs in Claude and why they exist
(05:55) Using Claude Cowork to design a new house using floor plans
(09:52) When to use Opus versus Sonnet 4.6
(12:37) Building an interactive 3D furniture planner
(14:30) Using your email as a source of truth for personal inventory
(15:58) The anti-to-do list: going one abstraction layer up
(23:14) Introduction to live artifacts
(26:02) Building a personal dashboard with live data
(28:37) Being polite to Claude (and why it matters for your humanity)
(30:28) Claude interaction tips
(32:33) Looking at the daily dashboard
(33:55) How live artifacts work with connectors
(35:02) Redesigning the dashboard
(37:55) The biggest gap: people don’t know what problems AI can solve
(41:52) The reverse interview
(42:30) Making latency delightful through asynchronous design
(44:05) The redesigned dashboard
(45:28) AI should free up your creative energy
(46:44) Building a $20 hardware Claude buddy
(52:33) Why kids are magical AI users
(54:30) Recap and final thoughts
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Tools referenced:
• Claude Cowork: https://www.anthropic.com/product/claude-cowork
• Claude Code: https://claude.ai/code
• Claude for Chrome: https://code.claude.com/docs/en/chrome
• Claude Desktop: https://claude.ai/download
• Live Artifacts: https://support.claude.com/en/articles/14729249-use-live-artifacts-in-claude-cowork
• Connectors (Spotify, Gmail, Calendar, Notion): https://claude.ai/settings/connectors
• Slack: https://slack.com/
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Where to find Felix Rieseberg:
Website: https://felixrieseberg.com/
LinkedIn: https://www.linkedin.com/in/felixrieseberg/
X: https://x.com/felixrieseberg
GitHub: https://github.com/felixrieseberg
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Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

Today is day one of Google I/O 2026, and I walk through every major announcement live—from the new Gemini 3.5 model family to Anti-Gravity 2.0, Google AI Studio, Gemini’s consumer redesign, the Omni video model, Flow, Stitch, and Pomelli. I test them in real time and tell you exactly which ones delivered.

What you’ll learn:
How Gemini 3.5 Flash benchmarks against Claude and GPT models on speed and agentic coding tasks
How Anti-Gravity 2.0’s new features (projects, scheduled tasks, subagents, slash commands) compare to Codex and Claude Code
Why the /grill-me slash command could be a more aggressive alternative to Claude Code’s clarification flow—and how to use it
How Google AI Studio’s new Workspace integration is designed to own the internal productivity app use case
How Google’s new creative tools work in practice: Omni (video generation), Flow (cinematic video editing and character consistency), Stitch (streaming UI design with inline edits), and Pomelli (brand identity and asset generation)
Why Google’s launch-to-availability gap is still a problem—and what to do when a featured product doesn’t actually work yet
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Brought to you by:
Magic Patterns—Prototypes that look like your product
Thoughtspot—Build AI-powered analytics into your product
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In this episode, we cover:
(00:00) Google I/O 2026 day 1 overview
(01:47) Gemini 3.5 flash
(04:19) Antigravity updates
(06:32) CLI test and agent features
(07:59) Core agent features released today—May 19th, 2026
(09:43) New slash commands
(11:20) Antigravity test results and takeaways
(12:25) AI Studio updates
(13:52) Access issues
(15:20) Gemini redesign
(17:24) Gemini image gen test
(19:16) Omni (video generation)
(22:56) Flow (cinematic editing)
(24:31) Avatar creation test
(26:45) Pomelli and Stitch
(31:13) Recap and final thoughts
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Tools referenced:
• Gemini 3.5 Flash: https://deepmind.google/technologies/gemini/
• Antigravity: https://antigravity.google/
• Google AI Studio: https://aistudio.google.com/
• Google Gemini: https://gemini.google.com/
• Omni (video generation): https://gemini.google/overview/video-generation/
• Google Flow: https://flow.google/
• Stitch: https://stitch.withgoogle.com/
• Pomelli (Google brand tool): https://labs.google.com/pomelli/about/
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Other references:
• Google I/O 2026 announcements: https://blog.google/innovation-and-ai/sundar-pichai-io-2026/
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Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

Thariq Shihipar is an engineer at Anthropic working on the Claude Code team. He’s spent the past several months experimenting with HTML as a replacement for Markdown in planning and implementation workflows, discovering that richer visual formats lead to better human engagement—and, ultimately, better products. In this episode, filmed at Anthropic’s Code with Claude event in San Francisco, Thariq demonstrates how to use HTML artifacts to create interactive plans, build throwaway UIs for specific problems, and maintain living design systems that travel with your codebase.

What you’ll learn:
Why HTML has replaced Markdown as the ideal format for AI agent communication and planning
How to brainstorm in HTML to get visual mockups and interactive demos instead of text lists
The technique for building throwaway micro-UIs to edit specific parts of your plan
How to create a living design system in HTML that lives in your repo and travels with every project
Why “complexity has to earn its keep” and how HTML helps you stay in the loop without over-constraining Claude
The prompting technique that gives Claude flexibility while ensuring that you get what you need
Why 99% of your AI-generated tokens should go to planning, interfaces, and communication—not production code
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Brought to you by:
Celigo—Intelligent automation built for AI
Persona—Trusted identity verification for any use case
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In this episode, we cover:
(00:00) Introduction
(02:39) HTML as the new Markdown
(04:30) The compute allocator mindset
(05:51) How HTML makes specs more engaging
(06:48) Demo: Brainstorming in HTML with Claude Code
(09:24) From brainstorm to full implementation plan
(11:20) Prompting philosophy: Trust Claude but give it constraints
(13:50) The future of PRDs and tech specs
(18:16) Making HTML specs editable
(20:23) The abundance mindset
(24:17) Just-in-time documentation and throwaway software
(25:39) Using plans as artifacts for implementation
(26:39) Demo: Living design systems in HTML
(30:16) Adding comments and annotations to HTML plans
(31:42) Recap: The HTML workflow
(32:21) Lightning round and final thoughts
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Tools referenced:
• Claude Code: https://claude.ai/code
• Claude Design: https://claude.ai/design
• AWS: https://aws.amazon.com/
• Figma: https://www.figma.com/
• GitHub: https://github.com/
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Other references:
• Anthropic Code with Claude event: https://claude.com/code-with-claude
• SpaceX partnership announcement: https://www.anthropic.com/news/higher-limits-spacex
• Jevons paradox: https://en.wikipedia.org/wiki/Jevons_paradox
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Where to find Thariq Shihipar:
Website: https://www.thariq.io/
LinkedIn: https://www.linkedin.com/in/thariqshihipar/
X: https://x.com/trq212
GitHub: https://github.com/ThariqS
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Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].