Show HN: Plandex – an AI coding engine for complex tasks

Original Article ↗ Hacker News Discussion ↗

Overall Reaction

  • Many commenters find Plandex promising as an AI coding tool for larger, multi-step tasks.
  • Some are skeptical that it does anything substantively beyond “trivial web projects” or what ChatGPT already does with manual copy‑paste.
  • Several users report real productivity gains on non-trivial work (e.g., infrastructure, billing backends, SPAs), but still needing human oversight.

Positioning vs Other Tools (Copilot, aider, GitHub bots)

  • Compared to Copilot, Plandex is praised for:
    • Working across multiple files, not just around the cursor.
    • Having a persistent, branching “plan” with saved conversation states.
    • Showing diffs before applying changes and allowing selective acceptance.
  • Compared to aider:
    • Plandex emphasizes multi-step plans, version-controlled sandboxes, branches, and a diff-review TUI.
    • aider emphasizes tight native git integration, chat-style UX, and using existing git workflows for undo/branches.
  • Some prefer GitHub Issue → PR bots; others find that flow clunky and like Plandex’s tighter loop and CLI.

Architecture, Git, and UX

  • Plandex uses a client–server model with Go backend, PostgreSQL, filesystem, and git combined into a transactional system.
  • Plans are version-controlled separately from the repo, which:
    • Avoids mixing user and AI changes.
    • Works even in non-git directories.
  • Diff-review TUI gets mixed feedback:
    • Some like side-by-side review and sandboxing.
    • Others want plain git diff output or an “auto-apply” mode and to rely on their existing diff tools.

Models, Costs, and Context

  • Currently relies mainly on OpenAI (gpt-4-turbo); no fine-tuning yet.
  • Roadmap includes supporting Claude, Gemini, Mistral, open source models, and local APIs like OpenRouter/Together/ollama, with function-calling support as a key requirement.
  • Reported cost: “meaty” tasks for under ~$1; more complex or iterative tasks can reach $1–2.
  • Uses gradual summarization for long plans and aims to be less aggressive than ChatGPT’s opaque strategy.

Capabilities, Limitations, and Future Features

  • Handles multi-file edits, AWS infra, billing backends, CLI/HTTP handlers, TUIs, and bug-hunting, but still makes syntax and “noob-level” mistakes.
  • Reliability of file patching improved using chain-of-thought around line ranges, but still needs human review.
  • Lacks automated test-running and execution, though workflows using test output as context are suggested; automated checks are on the roadmap.
  • Plans to add multimodal (vision) models, more frontends (web UI, plugins), Azure/custom endpoints, and collaboration features.
  • Cloud offering exists alongside self-hosting; server adds state, DB, and future sharing features, which some question vs the subscription price.