Steer is an open-source Python SDK that fixes "Confident Idiot" agents. (Featured on Hacker News Front Page).
It wraps your functions with deterministic guardrails (Regex, JSON Schema) to catch hallucinations in real-time. It then lets you "Teach" fixes via a local dashboard and export the data for fine-tuning.
Steer SDK is an open-source Python library that adds deterministic guardrails to AI agents to catch hallucinations and enforce reliability.
- for
- Developers building autonomous LLM agents who need runtime safety and observability.
- pricing
- open source
- license
- MIT
- v0.1Initial Release: The Teaching Loopa year ago
works withPythonPydanticAI
Key features
6 features of Steer SDK
- Low-latency sidecar — Adds verification with less than 5 ms overhead by running in-process.
- Fail-safe design — Configurable behavior on internal errors to prioritize uptime.
- Zero data exfiltration — Local-first architecture ensures prompts never leave your network.
- Audit-ready logging — Every blocked response is logged with a deterministic reason code.
- Framework patching — Zero-touch reliability for frameworks like PydanticAI via a central policy file.
- Decorator sidecar — Manual control using @capture decorator to inject taught rules at runtime.
Use cases
- Block malformed JSON output from agents and enforce raw JSON formatting
- Redact PII such as emails or keys from agent responses
- Require agents to ask clarifying questions when results are ambiguous
- Prevent brand-voice deviations by filtering low-entropy outputs
- Generate synthetic training pairs from blocked vs taught responses for DPO
Steer SDK vs alternatives
 Steer SDK |  LangChain |  LlamaIndex |  LangGraph |  CrewAI | |
|---|---|---|---|---|---|
| Best for | Deterministic guardrails for AI agents | LLM app development framework | Data-aware LLM retrieval | Stateful agent workflows | Multi-agent coordination |
| Pricing | Open source | Free | Free | Free | Subscription |
| DevHunt upvotes | 0 | 0 | 0 | 0 | 0 |
| Launched | Jan 2026 | — | — | — | — |
- Steer SDK vs LangChain: LangChain is a framework for building LLM apps, not a runtime guardrail layer.
- Steer SDK vs LlamaIndex: LlamaIndex focuses on data-centric retrieval, while Steer enforces output correctness.
- Steer SDK vs LangGraph: LangGraph provides stateful agent orchestration, whereas Steer adds deterministic validation to any agent.
- Steer SDK vs CrewAI: CrewAI manages multi-agent systems; Steer adds safety guards to individual agent outputs.
Steer SDK FAQ
How do I install Steer SDK?+
Run pip install steer-sdk to add the package to your Python environment.
What runtime overhead does Steer add?+
The sidecar verification adds less than 5 ms of latency per request.
Can Steer run without sending data to external services?+
Yes, its core verification logic is local-first and does not exfiltrate data.
How do I define guardrails for my agent?+
Create judges like JsonJudge or SlopJudge and apply them via the @capture decorator or a global policy file.
How can I use the captured failures for model improvement?+
Export blocked vs taught response pairs with steer export to generate DPO training data.
Is Steer compatible with multi-threaded production environments?+
It is thread-safe and tested for high-concurrency deployments.
Summarized by DevHunt from github.com · Oct 13, 2026. Details may change; check the official site.
