JetBrains Thinkrail

Original Article ↗ Hacker News Discussion ↗

JetBrains’ new Thinkrail project, an AI‑centric “agentic IDE” built on the Pi coding agent and web technologies like TypeScript and Monaco, is prompting mixed reactions from long‑time users. Many are intrigued by its spec‑driven workflow and tighter integration with autonomous coding agents, but question why it isn’t using JetBrains’ own editor engine, why it leans on cloud agents instead of local or containerized ones, and why its README appears to be AI‑generated marketing prose. The broader debate centers on whether heavyweight IDEs still make sense in an era where agents handle most coding tasks, and whether JetBrains’ rapidly multiplying AI products—Air, Thinkrail and others—reflect a coherent strategy or a rushed attempt to catch up with tools like Cursor and Zed.

Overall concept & goals

  • Thinkrail seen as moving toward a “final interface” for agentic dev: a single rail where all project tools/sessions can be rearranged easily (likened to a French cleat wall system).
  • Core value: organizing an agent’s work by project/session so humans can re-engage with context quickly, not just adding another AI sidebar.

Architecture & tech choices

  • Built around Pi as the coding agent; several Pi users are excited, especially once full Pi extension support lands.
  • Stack is TypeScript + Bun + Electron/React (Monaco editor). Some are disappointed it doesn’t use JetBrains’ own editor engine or a native/lightweight stack.
  • Criticism that using TS and Monaco feels like chasing lowest-common-denominator web tooling rather than JetBrains’ traditional strength in native-like IDEs.

AI agents & workflows

  • Strong support for running agents in isolated VMs/containers with strict network/secret controls; some view non-isolated agents as unsafe.
  • Others argue full GUI VMs are wasteful and that agents should mostly automate toward APIs rather than long-term GUI clicking.
  • Debate over agents “doing most of the work”: some report they now mainly supervise and review; others stress LLMs still require heavy oversight.

README / documentation controversy

  • Many criticize the README and SPEC docs as obvious “LLM prose”: verbose, abstract, “claude-y,” and hard to parse.
  • One camp: AI-generated README signals low care and poor taste; if authors won’t handcraft docs, they may also cut corners elsewhere.
  • Counter-camp: content quality matters more than authorship; AI can draft from real specs, with humans reviewing.

JetBrains AI & product strategy

  • Widespread confusion about JetBrains’ AI direction: Air, Thinkrail, earlier attempts like Fleet, and core IDE AI plugins feel fragmented or abandoned.
  • Some speculate Thinkrail is an experiment while Air is the strategic product; others fear both could be short-lived.
  • Longtime users report cancelling subscriptions or using JetBrains IDEs far less, replaced by agent-driven workflows plus lighter editors/CLIs.

Comparisons & sentiment

  • References to Cursor, Zed, various harnesses (Pi, Claude Code, Codex, others) as benchmarks.
  • Mixed mood: nostalgia and goodwill toward JetBrains, interest in Thinkrail’s spec-first idea, but strong skepticism about execution, performance, web-stack choices, and long-term commitment.