PandaProbe — agent engineering platform

Agent IDE

PandaProbe shipped an agent engineering platform on Product Hunt this week. 720 upvotes.

The pitch: build → test → deploy → monitor for agents in one tool. LangSmith and Helicone focus on observability; PandaProbe covers the full lifecycle.

What is it

Five modules:

1. Builder — visual + code agent workflow builder
2. Test — scenario-based auto-tests, prompt-regression detection
3. Deploy — Vercel-style git-push to production
4. Monitor — real-time latency, cost, success rate
5. Trace — agent decision-tree visualization

Integrates OpenAI, Anthropic, Google, Mistral. Compatible with LangChain and LlamaIndex.

First impressions

PH comments — visual builder feels natural, deploy fits git workflow, trace visualization debugs well.

Negatives — some LangChain integration bugs, enterprise audit log incomplete, pricing slightly above LangSmith.

Core features

• Visual + code agent builder
• Scenario auto-tests + prompt regression detection
• Git-push deploy + canary release
• Real-time latency, cost, success rate monitoring
• Decision-tree visualization
• Integrates all major LLMs + LangChain/LlamaIndex

Pricing

• Free: 1,000 requests/month + 1 environment
• Pro: $99/month — 100K requests + 5 environments + canary
• Enterprise: custom — VPC deploy, SSO, audit log

Who it's for

Startups moving agent PoCs to production. Mid-market running multi-agent systems. Enterprise focused on model cost optimization.

Similar tools

LangSmith (observability + evaluation), Helicone (cost tracking), Braintrust (eval). PandaProbe differentiates with full lifecycle coverage.

One-liner

Vercel for agents — git push to monitor in one rail.

3-Line Summary

• PandaProbe ships unified agent build, test, deploy, monitor.
• Lifecycle coverage differentiates from LangSmith and Helicone.
• 720 upvotes — new entrant in agent devtools.

Sources

• Product Hunt — PandaProbe
• PandaProbe official site
• HN — Agent observability discussion