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What's New With Opus 4.7

The Opus 4.7 launch extends across the whole platform. Five lessons cover the new Claude family, Managed Agents, Advisor Strategy, Task Budgets, and the three smaller updates customers ask about most. Each lesson includes an activity to lock in the key framings before your next customer conversation.

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About this course

Partners who've presented on Claude before usually know how to tell the model story. Opus 4.7 benchmarks well, the use cases are clear, and the migration recommendation is straightforward. What’s more challenging is the platform conversation that comes right after it.

Opus 4.7 is Anthropic's most capable model to date, with meaningful gains in agentic coding, enterprise workflows, and long-running autonomous tasks. SWE-bench Pro moved from 53.4% to 64.3%, and SWE-bench Verified from 80.8% to 87.6%. The multimodal reasoning got stronger too, now processing images up to 2,576 pixels with no changes to existing API calls. The harder conversation is what else shipped alongside it.

What changes the most for partners is Claude Managed Agents. Historically, running a production agent meant the customer handled the infrastructure themselves: sandboxing, memory, state management, tool execution. Managed Agents handles that for them. The Agent SDK gave partners the building blocks. Managed Agents is the managed service built on those same blocks. The engineering effort shifts away from infrastructure and toward the end-user experience. Multi-agent coordination comes with it, so agents can spawn and direct other agents to parallelize work without the customer managing the orchestration.

On the cost side, Advisor Strategy works differently. Sonnet or Haiku runs the request and calls out to Opus mid-request when it needs more reasoning depth, all inside a single API request. Once the advisor is added to the tools array, the model decides when to escalate. Opus returns roughly a 700-token plan and the customer pays executor rates on everything else.

Task Budgets tackle the second cost problem: runaway token spend across long agentic loops. The soft limit applies to the whole loop rather than a single request. For example, a research task can drop from 44,000 tokens to 11,000 when a 25,000-token budget is set. The final lesson covers three smaller updates: higher image resolution with no API changes required, the new xhigh effort level that sits between high and max, and /ultrareview in the Claude CLI for first-party terminal-based code review.

This course gives you the information you need:

  • How to position the full 4.7 release and explain what each platform feature changes for a customer's build
  • How to frame Advisor Strategy's cost mechanics and when the pattern is worth surfacing
  • How to explain Task Budgets and walk a customer through the validation step before shipping
  • How to explain the image resolution, xhigh, and /ultrareview updates without overselling them

By the end, you'll be ready to lead the Opus 4.7 platform conversation and handle questions that come up early.

 

Curriculum

  • Opus 4.7 and the Claude Model Family
  • Claude Managed Agents
  • Advisor Strategy
  • Task Budgets
  • Other New Features

About this course

Partners who've presented on Claude before usually know how to tell the model story. Opus 4.7 benchmarks well, the use cases are clear, and the migration recommendation is straightforward. What’s more challenging is the platform conversation that comes right after it.

Opus 4.7 is Anthropic's most capable model to date, with meaningful gains in agentic coding, enterprise workflows, and long-running autonomous tasks. SWE-bench Pro moved from 53.4% to 64.3%, and SWE-bench Verified from 80.8% to 87.6%. The multimodal reasoning got stronger too, now processing images up to 2,576 pixels with no changes to existing API calls. The harder conversation is what else shipped alongside it.

What changes the most for partners is Claude Managed Agents. Historically, running a production agent meant the customer handled the infrastructure themselves: sandboxing, memory, state management, tool execution. Managed Agents handles that for them. The Agent SDK gave partners the building blocks. Managed Agents is the managed service built on those same blocks. The engineering effort shifts away from infrastructure and toward the end-user experience. Multi-agent coordination comes with it, so agents can spawn and direct other agents to parallelize work without the customer managing the orchestration.

On the cost side, Advisor Strategy works differently. Sonnet or Haiku runs the request and calls out to Opus mid-request when it needs more reasoning depth, all inside a single API request. Once the advisor is added to the tools array, the model decides when to escalate. Opus returns roughly a 700-token plan and the customer pays executor rates on everything else.

Task Budgets tackle the second cost problem: runaway token spend across long agentic loops. The soft limit applies to the whole loop rather than a single request. For example, a research task can drop from 44,000 tokens to 11,000 when a 25,000-token budget is set. The final lesson covers three smaller updates: higher image resolution with no API changes required, the new xhigh effort level that sits between high and max, and /ultrareview in the Claude CLI for first-party terminal-based code review.

This course gives you the information you need:

  • How to position the full 4.7 release and explain what each platform feature changes for a customer's build
  • How to frame Advisor Strategy's cost mechanics and when the pattern is worth surfacing
  • How to explain Task Budgets and walk a customer through the validation step before shipping
  • How to explain the image resolution, xhigh, and /ultrareview updates without overselling them

By the end, you'll be ready to lead the Opus 4.7 platform conversation and handle questions that come up early.

 

Curriculum

  • Opus 4.7 and the Claude Model Family
  • Claude Managed Agents
  • Advisor Strategy
  • Task Budgets
  • Other New Features