Coolhand vs LangSmith
LangSmith now has a beta feature that can open a PR too. The real difference isn't whether a PR shows up — it's whether that happens continuously, on your infrastructure, without someone clicking "fix."
What is LangSmith?
LangSmith is LangChain's observability and evaluation platform — tracing, a Prompt Hub, LLM-as-judge and pairwise evaluators, human annotation queues, and alerting, all framework-agnostic (it works fine without LangChain or LangGraph). It's the best-known name in this space, backed by a $1.25B valuation as of late 2025.
In May 2026, LangChain shipped LangSmith Engine in public beta: roughly every six hours it re-scans production traces, clusters recurring failures into named issues, diagnoses them against your connected GitHub repo, and — when a person acts on a specific issue — drafts a code or prompt change and opens a PR for review. It's a genuine step toward what Coolhand already does by default, and we think that's worth being upfront about rather than pretending it doesn't exist.
What Coolhand actually does
Coolhand watches your production AI agents continuously. When something breaks — a hard error, a quality regression, a spike in cost — it diagnoses the root cause against your actual code, drafts the fix, and opens it as a pull request in your repo. Nothing merges without a human reviewing it first. Alongside that, an open-source skill audits your codebase for places to capture feedback that's already happening — edits, approvals, corrections — instead of asking you to build a new annotation queue. Cost and quality dashboards then show whether all of this is actually working, in dollars and quality-trend terms, not just "traces logged."
Where Coolhand excels: it's the only thing in this loop that turns a diagnosed problem into a reviewable code change on its own, continuously and without per-issue manual triggering. It doesn't need an annotation team, a dedicated eval engineer, or someone babysitting a dashboard — the loop runs in the background and only asks for your attention when there's a PR to review.
That's the gap LangSmith mostly still leaves open: Engine can draft a fix, but only per-issue, only when someone acts on a clustered issue, and its code-fix drafting currently targets apps built on LangChain, LangGraph, or Deep Agents. Coolhand runs the same loop continuously and drafts fixes regardless of the framework or model provider you're already using.
Coolhand vs LangSmith, feature by feature
| Capability | LangSmith | Coolhand |
|---|---|---|
| Primary purpose | Trace, evaluate, and manage prompts for LLM apps | Continuously diagnose production issues and ship the fix as a PR |
| Tracing depth | Deep — production dashboards, full-text/JSON search, trajectory clustering | Request-level logs built for diagnosis, not a dedicated trace explorer |
| Evaluation | LLM-as-judge, pairwise comparison, human annotation queues, datasets | Correctness and sentiment evaluators feeding the diagnosis loop |
| Human feedback | Manual annotation queues | Passive capture from your app's existing UI — no queue to build or staff |
| Opens a PR with a fix | Yes, via "Engine" (public beta) — but only when a person acts on a specific issue, and code-fix drafting currently targets LangChain/LangGraph/Deep Agents apps | Yes — continuous, always on, framework- and provider-agnostic |
| Ingestion | Python/TS/Go/Java SDKs, OpenTelemetry support | Ruby/Python/Node SDKs and provider proxies; no OpenTelemetry endpoint yet |
| Self-hostable server | Enterprise tier only (BYOC or self-hosted on Kubernetes) | No — managed service only (SDKs, CLI, and widget are open source) |
| ROI reporting | Cost and token dashboards; ROI framing is on you | Cost-per-outcome and quality-trend dashboards built in |
| Pricing entry point | Free up to 5k traces/month, then $39/seat/month Plus | Free up to 10M tokens/week |
When you need both
If your team already lives in LangSmith for prompt versioning and trace search — especially if you're deep in the LangChain/LangGraph ecosystem — there's no reason to give that up. LangSmith Engine is a real capability, but it's opt-in and per-issue: someone still has to notice the clustered failure and act on it, and its code-fix drafting currently targets apps built on LangChain, LangGraph, or Deep Agents. Coolhand's loop runs continuously in the background, is framework- and provider-agnostic, and is purpose-built end to end for diagnose → fix → feedback → ROI rather than being a feature bolted onto a trace-first tool.
You need both once you want LangSmith's depth on trace search and prompt management, plus a fix-and- feedback loop that doesn't depend on someone remembering to check the Engine queue.
How to use them together
Keep LangSmith for prompt version control, trace search, and any LangGraph-specific tooling your team relies on. Run Coolhand alongside it against the same production traffic so it's continuously diagnosing and proposing fixes without anyone having to trigger it. If LangSmith Engine flags and fixes something first, great — Coolhand's PRs and LangSmith's are just two independent proposals your team reviews the same way any other PR gets reviewed.
The practical split: LangSmith is where you go to inspect a trace or manage a prompt version by hand; Coolhand is what's already watching in the background so you don't have to.
Compare Coolhand to other tools
Frequently asked questions
Does LangSmith open pull requests?
Yes. LangSmith Engine (public beta, May 2026) clusters production failures into issues and can draft a code or prompt change as a PR when someone acts on an issue; its code-fix drafting currently targets apps built on LangChain, LangGraph, or Deep Agents. Coolhand runs the same loop continuously and drafts fixes framework- and provider-agnostically.
Is Coolhand a replacement for LangSmith?
No. If your team lives in LangSmith for prompt versioning and trace search — especially in the LangChain/LangGraph ecosystem — there's no reason to give that up. Coolhand runs alongside it, continuously diagnosing and proposing fixes.
What's the difference between Coolhand and LangSmith Engine?
LangSmith Engine is opt-in and per-issue and re-scans on a schedule. Coolhand's loop runs continuously in the background and is purpose-built end to end for diagnose → fix → feedback → ROI.
Can I use Coolhand and LangSmith together?
Yes. Keep LangSmith for prompt version control and trace search, and run Coolhand on the same production traffic so it's continuously diagnosing and proposing fixes without anyone triggering it.