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Production agents need more than a model.
The open-source, OTEL-native platform for the full agent harness — tied to the runs that produced them.
1 on the waitlist
Point tools don't connect
Traces in one tool, prompts in another, evals somewhere else. Each owns a slice. Nothing ties your changes to the production runs that produced them — so learnings reset every release.
One open consolidator for the harness
AgentTrace connects all six harness letters — E·T·C·S·L·V — as one versioned platform stamped on every run. Apache 2.0. Standard OTLP out. We're building it now; nothing is released yet.
Early access
First in when the SDK launches. Self-host the platform or use managed Cloud later — same harness either way.
1 on the waitlist
- OSS SDK + self-hosted platform (Apache 2.0)
- Managed Cloud option — no infra to run
- Follow the build on GitHub
Six letters. One platform.
The model is one input. Reliability lives in Environment, Tools, Context, Safety, Logging, and Verification — connected, not scattered across vendors.
Instrumentation & runtime
OTEL-native SDK with auto-instrumentation for LangGraph, OpenAI, Anthropic, and custom loops. Sits alongside Datadog or Honeycomb — no stack swap.
Tool registry
Every tool your agent can call — schema, version, owner — and which production runs actually used it.
Prompts & context
Versioned prompts with deploy-by-label. Context assembly diffable and linked to the traces it produced.
Policies & guardrails
PII redaction before export, runtime budget guards, and policy flags on traces. Live approval gates on the roadmap.
Full traces
Every span, tool call, retry, token, and cost — a replayable record of each run, with multi-agent topology.
Evals & regression
Replay harness changes against production history. CI gates on the whole harness — not just a prompt in isolation.
Trace → harness → verify → ship
Land through the trace. Grow into prompts, tools, and evals when you need them — one line each, never required upfront.
Trace
init() with zero required args. Auto-detect frameworks. First trace in under 30 seconds — the wedge in.
Harness in code
Version prompts, register tools, set policies — one line each when you need them. All stamped on the run.
Verify before ship
Replay changes against production history. Catch regressions in CI, not from a customer ticket.
Self-host or Cloud
OTLP to any backend, or run the full platform yourself. Managed Cloud for teams who want zero infra.
Questions, answered
Harness engineering, the open consolidator bet, and what we're building.
What is harness engineering?
Everything around the model that makes an agent reliable: Environment (runtime/instrumentation), Tools, Context (prompts and retrieval), Safety (policies, PII, approvals), Logging (traces), and Verification (evals). AgentTrace models all six as one connected harness.
Is it available?
Not yet. The SDK and platform are in active development — spec and strategy are on GitHub, but nothing is released today. Join the waitlist for early access at launch.
How is this different from LangSmith or Langfuse?
They each own one or two slices. AgentTrace connects all six harness letters to the runs that produced them — diff the whole harness, replay changes against production history, gate CI on regressions. OSS, OTEL-native, standard OTLP out.
Will it be open source?
Yes — Apache 2.0 core, fully self-hostable, OTLP to Datadog, Honeycomb, or any backend. Managed Cloud is optional for teams who don't want to run infra.
What's the developer experience goal?
Dead simple: init() with no required args, auto-detect your frameworks, first trace in under 30 seconds. Prompts, tools, evals, and budget guards are one extra line when you need them — never upfront.