The Model Thinks.
The Harness Delivers.

Models, tools, memory, guardrails, and more, wired together with no glue code. Configure an agent once and take it straight to production.

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60-second walkthrough

From Blank Canvas
to Governed Runtime

Watch an agent go from setup to running in one minute.

The Harness Is the Product

Everything an agent needs besides the model, ready to use.

Your choice of model

Use Claude Opus, Claude Sonnet, or your own fine-tuned model, whichever fits the task.

Reusable skills

Build a skill once, then add it to any agent.

One gateway for tools

Connect MCP servers, knowledge bases, and web browsing in one secure place.

Guardrails built in

Every input and output is checked for personal data, compliance, and prompt injection.

Memory built in

Agents remember what matters, and each user only sees what they’re allowed to.

Isolated runtimes

Each harness runs in its own runtime, with its own filesystem and shell.

Self-healing runs

When a tool times out or a model errors, the agent retries on its own.

Export to code

Need custom logic? Export the agent as Strands or LangGraph code.

Loop engineering

The Loop Is Where Agents Succeed or Fail

Every agent works in a loop: think, use a tool, check the result, repeat. We handle each step for you.

  1. Context packingKeeps the conversation short so the model focuses on what matters.
  2. Tool executionCalls each tool through the gateway and checks it’s allowed.
  3. Retry and repairFixes timeouts, bad answers, and failed tool calls.
  4. Stop conditionsEnds each run cleanly when it reaches its step, cost, or time limit.

The harness: the loop around the model

What published research shows

Why the Harness Matters

Independent studies that hold the model fixed and change only the harness.

38% → 62% Accuracy on biology data analysis when the same model gets a purpose-built harness. Workman et al., SpatialBench (arXiv 2512.21907) ↗
+14.5 pts Average gain across five benchmarks from changing only the harness (up to +44). Chen et al., HarnessX (arXiv 2606.14249) ↗
14 of 20 Models whose Terminal-Bench 2.0 score changes by 10+ points depending on the harness. Guo et al., Agent System and Harness Design survey (arXiv 2606.20683) ↗
21% → 12% Tasks that timed out on Terminal-Bench 2.0: same model, two different harnesses. Guo et al., Agent System and Harness Design survey (arXiv 2606.20683) ↗

Build It Yourself vs.
Harness Builder

See how much work Harness Builder takes off your team.

TaskBuild It YourselfHarness Builder
Running the agent loop Write and maintain the agent code yourself Set up the agent; the harness runs it
Changing models No easy way to swap models Swap models mid-session, no code
Keeping agents apart Agents share servers, so one problem affects all Each harness gets its own runtime, filesystem, and shell
Reaching tools and data Separate setup and credentials for every tool Connect every tool through one secure gateway
Adding guardrails Build safety checks into every agent Turn on built-in guardrails
Recovering from failure Engineers fix failures by hand Self-heals automatically
Needing custom logic Rebuild on a framework and migrate Export to Strands or LangGraph code

The Controls Are Part of the Harness

Security and compliance come built in.

Certified
HIPAA-compliant
Built to handle protected health information.
ISO/IEC 27001 certified
Information security that’s independently audited.
Fully managed
Hosted by ThinkTrends
No infrastructure for your team to set up or run.
Isolated runtime for every harness
Each harness gets its own runtime, filesystem, and shell.
Provable
Immutable per-action audit trail
Every action is recorded and can’t be changed later.
Signed, attestable agent bundles
Every agent version is signed, so you can prove what’s running.

Export to Code

Generates a runnable project from the current harness spec.

Contract_Review_Analyst · v1 · signed
For developers

Export to Strands or LangGraph

When a use case needs custom orchestration, export the harness as a runnable Python project on the same runtime.

  • Tools still route through the gateway
  • Guardrails, memory, and tracing carry over
  • Each export is tied to a signed harness version

Related Modules

Tools
MCP Server Management
Describe a tool in plain English and it's written, verified, and deployed as a governed MCP server.
Orchestration
Agent Workspaces
Shared surfaces where the agents you build actually run and work alongside your team.
Governance
Policy & Guardrails
PII, policy, and injection shields enforced at runtime on every agent you compose.

Frequently Asked Questions

Common questions about Agent Harness Builder.

What is an agent harness, and why does it matter?+
The model is the brain; the harness is everything else the agent needs to do work — running the orchestration loop, executing tools, managing the context window, persisting state, recovering from failure, and isolating each session. ThinkStack provides that as a managed layer you configure rather than code you write and maintain.
Do we have to write and maintain the agent loop?+
No. Define the model, tools, skills and instructions in configuration, and ThinkStack assembles and runs the loop. Tool timeouts, model errors and partial results are retried and recovered inside the loop rather than by your on-call engineer, and the context window is managed for you so long-running tasks don't lose their thread.
Can we change models without rewriting the agent?+
Yes, including mid-session. Plan with one model, draft with another, classify with a fine-tuned one — context and agent logic carry over, so switching providers doesn't mean rewriting call sites and re-testing by hand. Fine-tuned models from the Model Hub can be bound the same way as hosted ones.
How do agents reach tools, and what's enforced on the way?+
Through a single gateway. MCP servers, skills, knowledge and web browsing are all reached through it, and it enforces policy, identity and tracing on every call — rather than a credential and a client per integration. Each session also runs in its own environment with a filesystem and shell, so nothing leaks between users or runs.
What happens when we outgrow the configured harness?+
You export it rather than rebuild it. One command exports the harness to Strands or LangGraph code running on the same runtime and the same gateway. Tools still route through the gateway, and guardrail bindings and tracing come with it, so custom orchestration doesn't mean leaving the platform or losing the audit trail.