Leverage AI agents to orchestrate project management tasks across Linear, Slack, Gmail, Google Calendar, and Pylon for customer support.

Breaking complex prompts into simpler sub-agents is more delightful and efficient than endless iterative prompting to maintain context.

WhisperFlow is highlighted as a leading tool for integrating voice or audio workflows into AI applications, with strong user enthusiasm.

Unsloth offers a fine-tuning solution that appears to simplify model customization, promising more efficient training workflows.

The Agent CLI demo provides command-line tooling to launch, manage, and inspect AI agents built with the agent builder framework.

Deep Agents is a package for orchestrating and debugging multi-agent workflows with built-in tracing to visualize interactions between sub-agents.

Use the Deep Agents package to automatically generate a team of specialized sub-agents via natural language prompts, breaking down complex tasks and o...Show more

Cameron Rohn notes limited documentation around the new workspace keys feature in the Deep Agents platform, highlighting the early-stage nature of mod...Show more

Tom Spencer demonstrates the Deep Agents package, showcasing its modular toolset for building specialized agents like a full-featured podcast producer...Show more

Cameron Rohn shares how his agent builder example went off the rails, composing and attempting to send a random business venture email to his brother ...Show more

Build a developer-facing tool that captures and structures a user's hidden mental model and project context for AI agents to reduce drift and improve ...Show more

Cameron Rohn argues that AI agents must be managed similarly to human employees, requiring clear instructions and ongoing guidance to deliver desired ...Show more

Tom Spencer highlights that AI agent failures are often caused by unspoken assumptions and urges developers to explicitly supply all relevant context—...Show more

Deep Agents offer context-aware AI processing that preserves or improves output quality across multiple chained operations.

Langgraph agent can ingest inputs from Slack channels and other sources and execute intelligent tasks within a workflow canvas.

Cameron observed that chaining AI agents across multiple tools without fresh context reliably caused output quality to deteriorate after a few iterati...Show more

Develop a platform that integrates deterministic workflow building with AI agents like Langgraph, enabling businesses to automate fixed processes and ...Show more

Without injecting fresh context between chained AI agent processes, iterative processing leads to diminishing returns and deteriorating outputs.

Structure multi-agent pipelines as a loop of processing steps followed by context injection to prevent output degradation across chained AI operations...Show more

Combine a deterministic workflow builder with non-deterministic Langgraph agent nodes in one canvas to manage both structured sequences and variable i...Show more