LangChain

/goal: Building big features with dcode

Published 2026-07-22 · Duration 8:02

Summary

The video introduces `dcode`, an open-source, model-agnostic coding agent, and its new `/goal` command. This feature enables long-running, persistent tasks by wrapping the standard agent loop in a 'goal loop.' Instead of relying on single-shot requests for large features (like meaty PRs), `/goal` establishes visible acceptance criteria that guide the agent's work over hours. The demonstration shows how to use this mechanism to add native browser control to `dcode`, allowing the user to steer, amend requirements, and inspect progress using tools like LangSmith tracing.

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Key takeaways

  1. The /goal Command 2:50

    The `/goal` command provides a long-running, persistent objective for agents tackling large tasks. It shifts alignment work upfront, making it visible and allowing mid-run tailoring of requirements (3:46).

  2. Goal Loop Mechanism 0:35

    The goal loop wraps the agent's inner action loop. The outer loop continuously checks if actions satisfy the durable acceptance criteria; if not, the goal remains active until evidence satisfies all requirements (0:17).

  3. Steering and Amending Goals 4:40

    Users can inspect the current state with `/goal show` or update/correct requirements mid-run using `/goal amend`, which interprets the message within the context of the active goal (3:46).

Technical details

  • dcode Agent Architecture 45s

    `dcode` is an open-source, model-agnostic coding agent designed for controlling development workflows. It uses a 'goal loop' to manage large features (0:17).

  • Acceptance Criteria Management 160s

    Initial requests are converted into durable acceptance criteria. Users can manually edit these criteria using the `edit criteria` function, ensuring all requirements are visible and tracked (2:15).

  • Debugging Workflows 360s

    LangSmith tracing (`/trace`) allows users to peek under the hood of the agent's execution, providing a detailed breakdown of inputs and work associated with the goal prompt for debugging (4:51).

  • Feature Implementation

    The demonstration successfully added native browser control to `dcode` using Python Playwright API, enabled via a specific browser flag (`/browser`) and completing all tests (7:01).

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