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Claude Code Just Got WAY More Powerful

I break down the biggest announcements from Anthropic’s “Code with Claude” event and what they actually mean for builders shipping AI products today. From scheduled AI routines to outcome-based agents, multi-agent orchestration, and new memory systems, I walk through the features she’s most excited to use immediately—and how they could reshape the future of agentic software. *What you’ll learn:* 1. How Claude Code routines let you automate recurring workflows on schedules or webhooks 2. What “Outcomes” are and how rubric-based agent grading works 3. How multi-agent orchestration enables specialized AI teams with different roles and tools 4. Why Anthropic’s new “Dreams” memory system matters for long-term agent behavior 5. The biggest launch today (higher rate limits!) 6. How I think about building practical agentic products today *Links and resources:* • Code with Claude: https://claude.com/code-with-claude • Claude Code Routines Docs: https://code.claude.com/docs/en/routines • Define Outcomes Docs: https://platform.claude.com/docs/en/managed-agents/define-outcomes • Dreams Docs: https://platform.claude.com/docs/en/managed-agents/dreams • Multi-Agent Docs: https://platform.claude.com/docs/en/managed-agents/multi-agent • Managed Agent Webhooks Docs: https://platform.claude.com/docs/en/managed-agents/webhooks#supported-event-types • Codex (OpenAI): https://openai.com/codex • GitHub: https://github.com _Production and marketing by https://penname.co/._ _For inquiries about sponsoring the podcast, email jordan@penname.co._

Claire Vohost
May 7, 202611mWatch on YouTube ↗

CHAPTERS

  1. 0:04 – 0:34

    What launched at Code with Claude: 5 practical updates (overview)

    Claire recaps attending Anthropic’s first developer event, Code with Claude, and previews five launches that improve Claude Code and Claude Managed Agents. She frames the episode as a fast, builder-focused tour of what shipped and why it matters.

    • Context: Anthropic’s first developer event and what changed
    • Focus on what’s usable immediately in Claude Code and the API
    • Promise: explain how each feature works plus ideas for what to build
    • Goal: quick, under-10-minute walkthrough
  2. 0:34 – 1:04

    Claude Code “Routines”: scheduling agent work like cron jobs

    Claude Code now supports “routines,” letting you trigger actions on a schedule—similar to cron—directly inside the app. Claire highlights this as a long-awaited quality-of-life improvement for recurring agent workflows.

    • Routines add scheduled automation inside Claude Code
    • Can run routines locally or remotely
    • Designed for recurring tasks you previously kicked off manually
    • Comparable to cron-based automation she liked in OpenClaw
  3. 1:04 – 2:37

    Live example: weekly changelog → customer newsletter draft

    Claire sets up a routine to generate a weekly newsletter from a project’s changelog.md. She shows how to specify instructions, timing (Mondays at 6 a.m.), and the project folder, then explains how she’d operationalize the output.

    • Routine prompt: read docs/changelog.md and draft customer-facing newsletter
    • Filter guidance: avoid internal topics like tech debt/security unless customer-relevant
    • Schedule configuration: weekly on Mondays at 6:00 a.m.
    • Operational ideas: export HTML, integrate with newsletter tools or ping Slack
  4. 2:37 – 3:07

    Routine triggers & integrations: cron, HTTP, GitHub webhooks + connectors

    She explains the three trigger types for routines and how they can integrate with connected services. This turns Claude Code into an automation hub that can react to time, webhooks, or GitHub events.

    • Three triggers: cron schedule, HTTP webhook, GitHub webhook
    • Routines can be invoked by other systems via webhooks
    • Connectors (e.g., Slack, GitHub) can be used inside routines
    • Choice of execution: cloud-run or laptop/local
  5. 3:07 – 4:08

    Outcomes in Claude Managed Agents: define “done” with a rubric

    Anthropic introduces “Outcomes,” a managed-agent feature where you specify success criteria and let the agent iterate until it meets them. Claire compares it to goal-seeking loops elsewhere and emphasizes rubric-based evaluation.

    • Outcomes let you define what “done” looks like for an agent
    • Anchored on a rubric (markdown) provided inline or via Files API
    • Agent can self-grade using a grader and iterate up to ~20 times
    • Useful primitive for reliability in agentic products
  6. 4:08 – 5:09

    Concrete Outcomes use case: iterating a PRD until it’s ship-ready

    Using PRDs as an example, Claire describes how an outcomes-driven agent could repeatedly refine a document through feedback-style cycles. She notes the product potential for exposing this capability to end users.

    • Define a “ship-ready PRD” rubric, then iterate until it passes
    • Automates feedback loops: priorities, feasibility, completeness
    • Agent repeatedly improves the artifact rather than one-shot drafting
    • Can be productized (e.g., in ChatPRD) as a customer-facing workflow
  7. 5:09 – 5:39

    Multi-agent teams via API: orchestrator + delegates in one workspace

    Claude Managed Agents now supports explicit multi-agent frameworks where multiple agents collaborate against the same container/filesystem. Claire highlights programmable hierarchy and per-agent tool configuration.

    • Programmatically define teams of agents through the API
    • Shared environment: same container and filesystem
    • Hierarchy supported: orchestrator coordinating delegates
    • Scale: up to ~25 agents working together
  8. 5:39 – 6:39

    Example multi-agent setup for PRDs: strategy, critic, and technical review

    Claire proposes a practical team composition for building stronger PRDs by combining different perspectives. Each sub-agent can have distinct tools and responsibilities while the orchestrator integrates their outputs.

    • PRD orchestrator drives overall workflow and merges results
    • Strategy agent emulates a CPO/product leadership voice
    • Critic agent stress-tests logic and finds gaps
    • End/engineering review agent can use GitHub/tools to optimize implementation
  9. 6:39 – 8:42

    Dreams (research preview): consolidating agent memory across sessions

    “Dreams” is positioned as an agent memory primitive that can review many past sessions and write key memories to disk on demand. Claire explains memory as practical markdown artifacts and why on-demand consolidation is useful.

    • Agent memory as markdown files saved to the agent’s filesystem
    • Dreams: call over a list of sessions to extract important memories
    • Moves beyond event-hook memory writing (session close, explicit command)
    • Currently research preview; Claire hasn’t accessed it yet
  10. 8:42 – 9:12

    Beyond memory: the missing primitive is “forgetting”

    Claire notes that the ecosystem talks a lot about memory but not enough about forgetting. She suggests a complementary “purge” concept to remove stale or harmful memories for healthier long-term agent behavior.

    • Forgetting is under-discussed compared to memory accumulation
    • Long-lived agents may need intentional memory pruning
    • Potential future primitive: purge/forget workflows
    • Highlights evolving thinking about agent state management
  11. 9:12 – 9:43

    Limits increased: more Claude Code usage + higher API rate limits

    She covers the headline operational update: higher usage limits across plans and removal of peak hours for some tiers. API rate limits for Opus also increase, enabling more throughput for builders.

    • Claude Code 5-hour limits doubled across Pro/Max/Team/Enterprise seats
    • Peak hours going away for Pro and Max plans
    • Opus API rate limits increased
    • Net effect: more continuous building and heavier agent workflows
  12. 9:43 – 11:14

    Wrap-up: why these primitives matter for building agentic products

    Claire summarizes the five launches and positions them as practical building blocks—automation, iterative success criteria, coordinated teams, and durable memory—plus better capacity. She closes with her take that Anthropic is aiming to be the agent platform of choice.

    • Recap: Routines, Outcomes, Multi-agent orchestration, Dreams, usage increases
    • Emphasis on immediate practicality vs. “mind-blowing” demos
    • Signals direction: agent primitives and platform-first strategy
    • Call to action: experiment, build, and share feedback
  13. 11:14 – 11:37

    Outro: subscribe, comment, and find the show on podcast platforms

    Claire ends with standard show outro and where to follow/listen. She asks viewers to like, subscribe, comment, and leave ratings on podcast apps.

    • Like/subscribe and leave a comment
    • Available on Apple Podcasts, Spotify, and other apps
    • Ratings/reviews help discovery
    • Website: howiai pod.com

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