Claude Code adds workflow size controls for agents

// 2h agoPRODUCT UPDATE

Claude Code adds workflow size controls for agents

Claude Code now allows developers to control the scale of multi-agent workflows with presets ranging from small (under 5 agents) to large (under 50 agents), plus an unrestricted mode. The new controls help developers balance context, execution speed, and token usage based on project complexity.

// ANALYSIS

Giving developers direct knobs over agent pool limits is a key step toward making autonomous coding tools predictable and cost-effective.

–**Cost & Token Management**: Capping agent counts prevents runaway subagent spawns from unexpectedly driving up API consumption.
–**Predictable Performance**: Presets (<5, <15, <50) provide simple, practical heuristics tailored to quick fixes versus massive repository refactors.
–**Flexible Default**: Preserving an 'unrestricted' option ensures complex multi-file engineering tasks can still scale up as far as needed.

// TAGS

claude-codeai-codingagentic-workflowsanthropicdevtool

DISCOVERED

2h ago

2026-07-28

PUBLISHED

3h ago

2026-07-28

RELEVANCE

8/ 10

AUTHOR

dani_avila7

// KEEP READING

More AI developer news from the feed

EXPLORE FULL FEED

UPDATE30m ago

Mintlify editor loads pages 9.5x faster

Mintlify has introduced a major performance update to its documentation platform, enabling its editor to load pages 9.5x faster than before. The enhancement aims to reduce latency and friction for developers writing, editing, and managing technical documentation and API reference pages.

NEWS54m ago

David Ha runs K3 locally on M5 Max

AI researcher David Ha (@hardmaru) shared an experiment running the massive K3 language model locally on Apple's M5 Max chip. Operating at a throughput of approximately 0.3 tokens per second, the test demonstrates the capability of high-capacity Apple Silicon unified memory to host huge models, even if the current performance is exceptionally slow.

OPEN SOURCE1h ago

OpenAI open-sources Codex Security CLI

OpenAI has open-sourced Codex Security CLI, a tool designed to help developers discover, validate, and remediate vulnerabilities directly within their local development environment and CI/CD pipelines. By combining local context analysis with AI threat modeling, Codex Security CLI allows engineering teams to scan local repositories, automate security checks in workflows like GitHub Actions, and track security findings over time.