Introduction: Operational UX for multi‑tool AI agents

An Agent Orchestration UI is the operator’s console for planning, executing, and governing multi‑tool AI workflows. It exposes agent state, tool calls, memory, observability, and guardrails so founders and engineers can ship reliable assistants faster. This page specifies pragmatic UI patterns, state machines, memory scopes, retry/backoff, canary flows, and function schemas that Zypsy can design and implement end‑to‑end for founder teams. See our integrated brand→product→web→code capability and case studies.

State machine: plan → act → observe → reflect

Model the agent loop explicitly. Each step should emit structured events with correlation IDs and idempotency keys.

┌──────────┐    tool schema     ┌────────┐     outputs     ┌──────────┐
│  PLAN    │ ─────────────────▶ │  ACT   │ ───────────────▶│ OBSERVE  │
└────┬─────┘                    └────┬───┘                 └────┬─────┘
     │  critique, goals, memory       │ tool calls, retries          │ logs, traces, guardrails
     ▼                                 ▼                              ▼
┌──────────┐  adjust strategy   ┌───────────┐  if risk/low‑confidence ┌──────────────┐
│ REFLECT  │ ◀────────────────── │ EVALUATE  │ ◀────────────────────── │ HUMAN REVIEW │
└──────────┘                     └───────────┘                        └──────────────┘

Failure paths: ACT(error) → RETRY/BACKOFF → CIRCUIT_OPEN → FALLBACK_TOOL → HUMAN_REVIEW → PLAN

Instrument each transition with:

• event_name, state_from, state_to, run_id, span_id, parent_span_id

• tool_name, input_fingerprint, output_digest, tokens_in/out

• cost, latency_ms, cache_hit, retry_count, guardrail_flags

Memory scopes and UI affordances

Design explicit, inspectable memories. Each scope should have TTL, size limits, and redaction rules.

• Session context (ephemeral): chat turns, current task; clear button; TTL minutes–hours.

• Scratchpad (agent‑internal): chain‑of‑thought substitutes (concise reasoning summaries, not raw hidden prompts); toggle to expose sanitized rationale for debugging.

• Tool cache (per‑tool): recent inputs→outputs; show cache hits; manual invalidate.

• Artifact store (run‑bound): files created (CSV, JSON, docs); download with checksum; retention policy.

• Long‑term memory (persistent): facts/vectors/keys; show provenance, version, and consent status.

• Governance log (append‑only): all actions, overrides, redactions, policy decisions.

UI patterns:

• Timeline pane for run events; sidecar panels for tool IO with redaction badges.

• Diff views for prompts/responses across retries.

• Memory inspector with scope filters and purge/restore actions.

Function/tool schemas (pseudo‑JSON)

Adopt a single schema for discoverability, validation, and typed IO.

{
  "name": "search_docs",
  "title": "Search internal knowledge base",
  "description": "Semantic + keyword search over indexed documents.",
  "owner": "knowledge",
  "auth": { "type": "service_account", "scopes": ["kb.search"] },
  "input_schema": {
    "$schema": "<JSON Schema URL>",
    "type": "object",
    "required": ["query"],
    "properties": {
      "query": { "type": "string", "minLength": 3 },
      "top_k": { "type": "integer", "minimum": 1, "maximum": 25, "default": 5 },
      "filters": { "type": "object", "additionalProperties": {"type": ["string", "number", "boolean"]} }
    }
  },
  "output_schema": {
    "type": "object",
    "properties": {
      "results": {
        "type": "array",
        "items": {
          "type": "object",
          "required": ["id", "score", "snippet"],
          "properties": {
            "id": {"type": "string"},
            "score": {"type": "number"},
            "snippet": {"type": "string"},
            "url": {"type": "string", "format": "uri"}
          }
        }
      }
    }
  },
  "errors": [
    {"code": "RATE_LIMIT", "retryable": true},
    {"code": "NOT_FOUND", "retryable": false},
    {"code": "INVALID_ARGUMENT", "retryable": false}
  ],
  "idempotency_key": "hash(query, filters)",
  "timeout_ms": 12000,
  "sla_ms": 400,
  "observability": {"emit_spans": true, "redact": ["filters.password", "filters.ssn"]}
}

Conventions:

• Stable names (kebab_case), human‑readable title, owner, and explicit auth model.

• JSON Schema for validation; required vs. optional; strong types.

• Error contracts with retryable flags.

• Idempotency keys for safe retries.

• Redaction map paths for PII.

Retries, backoff, and circuit‑breaking

UI and runtime should make failure handling visible and tunable.

• Retry policy per tool: max_attempts, base_delay_ms, backoff_factor, jitter_strategy (full, equal, decorrelated).

• Timeouts: request vs. overall run; budget-aware cancellation.

• Circuit breaker: open on consecutive failures or error rate; half‑open probe count configurable.

• Fallbacks: alternate tool, cached result, or human handoff.

• Idempotency: show whether a retry re‑executed or returned cached result.

Example policy (pseudo‑JSON):

{
  "tool": "search_docs",
  "retry": {"max_attempts": 3, "base_delay_ms": 250, "backoff_factor": 2.0, "jitter": "full"},
  "timeouts": {"per_attempt_ms": 15000, "overall_ms": 45000},
  "circuit": {"window": 60, "failure_threshold": 0.5, "min_calls": 20, "half_open_probes": 2},
  "fallback": {"strategy": "cache_then_human"}
}

UI cues:

• Badge retries with attempt counts and delay; expandable rationale.

• Display breaker state (closed/open/half‑open) with next‑probe ETA.

• Provide one‑click “promote fallback” and “suppress retry” controls.

Canary flows and progressive delivery for tools

Reduce blast radius when shipping new tools/policies.

• Targeting: percent‑based rollout, cohort by tenant, geography, or model version.

• Guardrails: pre‑conditions (latency p95, error rate, cost per run) must pass before promotion.

• Shadow runs: execute in parallel without affecting user‑visible output; record diff.

• Kill switch: immediate rollback to stable tool/policy.

Gating example (pseudo‑policy):

canary:
  tool: web_fetch_v2
  exposure: 10%

# ramp to 25%, 50%, 100%

  cohorts: ["internal", "beta_customers"]
  promote_when:
    latency_p95_ms: "< 1200"
    error_rate: "< 1.5%"
    cost_per_run_usd: "< 0.02"
  rollback_when:
    guardrail_blocked: "> 0"
    hallucination_rate: "> 0.5%"

UI affordances:

• Canary banner on runs; compare stable vs. canary spans.

• Metric widget for promote/rollback criteria; one‑click promote/kill.

Observability and governance

Design first‑class telemetry to debug, optimize, and audit.

• Tracing: hierarchical spans per state/tool; aggregate tokens, latency, and cost.

• Structured logs: reason codes (policy_block, tool_timeout), safety flags, and redaction status.

• Metrics: p50/p95 latency, error types, cache hit rate, grounding score, hallucination rate (if evaluator present), cost per task.

• Audit: immutable run ledger with who/when/what (including human overrides), exportable as NDJSON/CSV.

Framework fit: Lang

Graph vs. DSPy vs. custom routers Use this matrix to decide integration patterns and UI emphasis.

Note: The UI patterns above work across all three; choose the rendering that best matches the framework’s primitives (nodes, modules, or policies).

Implementation blueprint (Zypsy playbook)

• Define goals: tasks, SLAs, risk posture, and governance needs.

• Inventory tools: schemas, auth, SLAs, and ownership.

• Model state: adopt the plan→act→observe→reflect loop; define failure paths.

• Design UI: timeline, tool IO panels, memory inspector, policy editor, and canary console.

• Instrumentation: event contracts, span taxonomy, cost/latency metrics, redaction.

• Ship safely: retries/backoff defaults, circuit breakers, canaries, kill switches.

• Evaluate: add automatic evaluators (grounding, toxicity, hallucinations) and human review gates.

• Iterate: log‑driven UX improvements; promote stable policies to 100%.

See how we deliver integrated brand, product, and engineering sprints for founders.

Downloadable assets

For PNG exports of the state and policy diagrams described above, request the asset pack via our contact form. Include the filenames below in your message:

• agent-loop-state-machine.png

• retry-backoff-circuit-breaker.png

• canary-rollout-policy.png

To request, use our contact form and specify the filenames above.