Agent Harness Architect: Production AI System Designer & Failure Simulator

Harness Layer Settings Resilient (94%)

Active Architecture Profile

Layer 1: Model Adapter

Base Model:

Call Timeout: 15000ms

Layer 2: Tool Registry & Permissions

Strict JSON Schema Dry-Run Flag

Rate Limit (call/min):

Layer 3: Session & State Store

Storage Engine:

Max History Turns:

Layer 4: Execution Sandbox

Isolation Level:

Strict Egress Filtering

Layer 5: Verification & Loop Guards

Max Step Iterations:

Human Gate on Writes/Refunds

Inject Real-World Stress Tests

Active Harness Topology (DeepSeek Thesis) Status: Guarded

1. Model Adapter Layer DeepSeek-V3 | Temp: 0.2 | Timeout: 15s | Streaming JSON Parser

Ready

2. Tool Registry & Permissions Strict Schemas [Active] | Dry-Run Interceptor [Enabled] | Rate Limit: 30 rpm

Ready

3. Session & State Store Ephemeral Redis + Snapshot diffing | Limit: 20 turns | Zero Memory Drift

Ready

4. Execution Sandbox gVisor MicroVM Container | Egress Whitelist Active | Non-Root FS

Isolated

5. Verification & Loop Guards Circuit Breaker (Max: 8 steps) | Human Approval Policy: db_write, refund_issue

Armed

Harness Execution & Interceptor Trace Log Real-Time Event Stream

00:00.00 HARNESS_INIT All 5 harness plugins initialized with deterministic telemetry. Awaiting action.

Harness Telemetry Breaker: Armed

Total Tool Calls

Tokens Consumed

Tools Intercepted

42ms

P99 Guard Latency

Active Circuit Breaker State

Circuit Breaker: Nominal (No safety violations detected).

Interception & State Snapshot

Step	Target Action	Interception Verdict
No actions logged yet.

2026 Production Incident Recovery

When an agent enters a hallucination trap or calls unverified mutating APIs, the harness wraps the model call in a bounded transactional envelope, restores the previous snapshot, and serves a structured fallback without model re-querying.

A harness blueprint distinguishes configured limits from scripted demonstrations

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The nominal harness has five layers: model, tools, session, sandbox and verification. Its resilience score starts at fifty. Strict schemas add ten, dry run ten, container isolation fifteen, egress filtering five and human confirmation ten, reaching one hundred. At three pixels per point baseline measures one hundred fifty, all additions one hundred fifty and total three hundred. These are assigned UI points. Choosing a model name does not call that model, and exported settings do not create a sandbox, database or authentication system. The cyclic scenario resets all user configuration to nominal, then plays five scripted tool entries. Their tokens are eighteen hundred, twenty four hundred, thirty two hundred, thirty four hundred and thirty four hundred, summing fourteen thousand two hundred. The terminal snapshot assigns five calls, three executed and two blocked. At fifty pixels per call the bars are two hundred fifty, one hundred fifty and one hundred. The breaker is named max iterations exceeded despite configured maximum eight and only five observed steps. That name describes the scripted demonstration, not a validated limit comparison or actual refund interception. The context scenario advances displayed tokens by thirty two thousand each tick: thirty two, sixty four then ninety six thousand. It logs a forty eight thousand compaction but does not reduce the displayed ninety six thousand or update the exported runtime metrics. At one pixel per four hundred tokens the display bar is two hundred forty and logged removal one hundred twenty. The zombie scenario logs five thousand idle milliseconds after a five hundred millisecond timer. Settings for rate limit, storage and max turns have no change listeners here. Native JSON captures configured state and persisted metrics; display text, timing labels and exported counters need separate checks.