If you are building a one-off voice demo for an internal meeting, skip this template. Write the prompt, make the call, and learn.
If the agent will talk to real customers, collect sensitive information, call tools, route support cases, book appointments, or influence revenue, start with requirements. The first demo can sound convincing while the product requirements are still vague.
This AI voice agent requirements template gives product, engineering, QA, security, and operations one document to argue over before implementation starts. That is the point. A requirement that cannot survive a written owner, target, and evidence bar usually will not survive launch.
TL;DR: Write the requirements document in 10 sections:
- Caller job and business outcome
- Supported and unsupported scope
- Channels, runtime, and audio path
- Conversation contract
- Tool, data, and side-effect boundaries
- Test pack and evaluation metrics
- Security, privacy, and compliance rules
- Observability and evidence package
- Launch gates and rollback triggers
- Owner map, open risks, and acceptance criteria
Methodology Note: This template is based on Hamming's analysis of 4M+ production voice agent calls across 10K+ production voice agents (2025-2026). We've tested agents built on LiveKit, Pipecat, ElevenLabs, Retell, Vapi, and custom-built solutions.It also reflects launch-review failure patterns Hamming has seen in production teams, plus public AI risk, realtime voice-agent, and agent-evaluation guidance from NIST, OpenAI, and Microsoft to keep the requirements format grounded.
Last Updated: June 2026
Related Guides:
- Best Voice Agent Stack - choose the model, STT, TTS, telephony, and monitoring stack after requirements are clear
- AI Voice Agent Implementation Checklist - turn approved requirements into a build plan
- Voice Agent Production Readiness Checklist - convert requirements into launch gates
- Voice Agent Testing Guide - design scenario, regression, load, and safety coverage
- Voice Agent Tests as Code - make requirements reviewable in CI
- Voice Agent Sandbox Testing - prove tool calls without touching production data
- Voice Agent Security Review Questions - tighten data, access, retention, and vendor requirements
- Voice Agent Monitoring KPIs - define the metrics that decide whether launch is healthy
What Is an AI Voice Agent Requirements Template?
An AI voice agent requirements template is a structured product document that defines what a voice agent may do, how it should behave, which tools it may use, how quality will be measured, and what proof is needed before real callers reach it.
Definition: AI voice agent requirements are the agreed product, technical, testing, security, and operating constraints that make the agent judgeable before it is built.
The last word matters. Judgeable.
A voice agent requirement is not "answer billing questions." That is an aspiration. A judgeable version is: "The agent answers balance, invoice-date, and payment-method questions for authenticated callers; refuses refund disputes; escalates delinquency edge cases; and passes 95% of the billing scenario suite with no unauthorized account writes."
That kind of sentence changes implementation. It tells engineering what to build, QA what to test, security what to review, and support what the fallback path is.
What This Template Does Not Decide
This template will not pick your model, telephony provider, STT engine, TTS voice, or monitoring vendor. Use the stack selection guide after the caller job and risk boundary are written down.
It also does not replace a security review. If the agent handles healthcare, payments, identity verification, or account changes, the requirements document should make the risk visible; security still needs to approve the data path.
We found this distinction matters across Hamming's analysis of 4M+ production voice agent calls across 10K+ voice agents: teams usually do not fail because nobody cared about requirements. They fail because product, engineering, QA, and operations each assumed a different requirement was obvious.
Requirements Template vs. Other Voice Agent Checklists
Use this template before the implementation checklist. It is the upstream decision record.
| Artifact | When to Use It | Main Question | Output |
|---|---|---|---|
| Requirements template | Before build, vendor review, or RFP | What should this agent be allowed and required to do? | Product and technical requirements |
| Stack selection guide | Once the job and risk are clear | Which architecture and providers fit the job? | Runtime and vendor decisions |
| Implementation checklist | During build | Did we build the right system? | Build-review evidence |
| QA POC template | During vendor trial | Can this platform prove risk reduction? | Pilot scorecard |
| Production readiness checklist | Before launch | Is the built agent safe to receive traffic? | Go/no-go decision |
Rule: if a launch gate appears for the first time during production readiness, it was really a missing requirement.
The requirements document does not need to be long. It does need to be specific enough that a failed test is not a surprise.
The 10-Section AI Voice Agent Requirements Template
Use this table as the first draft. Each row should have one accountable owner and one proof artifact.
| Section | Requirement to Define | Owner | Proof Artifact | Failure Signal |
|---|---|---|---|---|
| 1. Caller job | The business outcome the agent may complete | Product | Job statement and success metric | Agent scope keeps expanding |
| 2. Scope boundary | Supported, unsupported, and escalation intents | Product + CX | Intent matrix | Agent answers out-of-scope requests |
| 3. Channel and runtime | Web, app, SIP, phone, or managed voice path | Engineering | Architecture decision | Prompt work hides audio-path risk |
| 4. Conversation contract | What the agent says, asks, refuses, and confirms | Product + QA | Prompt and policy contract | Callers get inconsistent behavior |
| 5. Tool boundaries | Read/write tools, permissions, and side effects | Engineering + security | Tool schema and authorization rule | Model text is treated as permission |
| 6. Test pack | Scenario count, personas, assertions, and metrics | QA | Scenario suite and pass targets | Demo calls replace coverage |
| 7. Security rules | PII, consent, retention, audit, and data access | Security | Review checklist | Sensitive data enters logs or tools unsafely |
| 8. Evidence package | Audio, transcript, trace, tool result, and reviewer decision | Engineering + QA | Run evidence export | Failures cannot be replayed |
| 9. Launch gates | Metrics that pause, roll back, or escalate launch | Ops + product | Gate table | Rollback becomes a meeting |
| 10. Acceptance criteria | What must be true before build, POC, or launch | Sponsor | Signoff memo | Everyone thinks "ready" means something different |
OpenAI's realtime documentation frames voice-agent sessions as long-lived sessions that send audio or text, receive model responses, use tools, and maintain session state. That means requirements must cover more than a prompt. They must cover audio transport, session lifecycle, tool behavior, and evidence.
Microsoft's agent-evaluation guidance makes the same point from the testing side: define test cases, expected behavior, assertions, quality signals, and metrics. Do that before the agent is polished, because requirements are easier to change than a production workflow.
Copyable AI Voice Agent PRD Template
Paste this into a doc and fill in the bracketed fields. Keep it short enough that every owner can review it in one meeting.
AI voice agent requirements
1. Caller job
- Agent name:
- Business owner:
- Caller population:
- Primary job to complete:
- Business metric this should improve:
- Jobs this agent must not do:
2. Supported scope
- Supported intents:
- Unsupported intents:
- Required escalation paths:
- Required languages, accents, or caller groups:
- Required channels: phone, SIP, browser, app, or other:
3. Runtime and audio path
- Runtime choice:
- Audio transport:
- STT/TTS/model/provider assumptions:
- Turn detection and interruption requirement:
- Identity and session-linking requirement:
4. Conversation contract
- Required opening:
- Required data collection:
- Confirmation rules:
- Refusal rules:
- Human handoff rules:
- Tone and brand rules:
5. Tool and data boundaries
- Read-only tools:
- Write tools:
- Server-side authorization rule:
- Idempotency requirement:
- Sandbox or fixture data:
- Final-state proof:
6. Test and evaluation plan
- Prototype scenario count:
- Preproduction scenario count:
- Launch-critical scenarios:
- Required edge cases:
- Pass-rate targets:
- Reviewer calibration plan:
7. Security and compliance
- Sensitive data classes:
- Consent or disclosure requirement:
- Retention requirement:
- Redaction requirement:
- Audit log requirement:
- Vendor or subprocessor constraints:
8. Observability and evidence
- Audio saved:
- Transcript saved:
- Trace saved:
- Tool input and output saved:
- Final state saved:
- Reviewer decision saved:
- Evidence export path:
9. Launch gates
- Task completion target:
- Escalation correctness target:
- Latency target:
- Tool-call success target:
- Safety no-go triggers:
- Rollback owner and trigger:
10. Acceptance criteria
- Build can start when:
- Vendor POC can start when:
- Production readiness review can start when:
- Launch is blocked if:
- Known risks accepted by:This is not meant to be pretty. It is meant to prevent the classic launch-week sentence: "I thought we were going to handle that manually."
Section 1: Caller Job and Scope
Start with the caller job, not the model.
| Requirement | Bad Version | Better Version |
|---|---|---|
| Caller job | "Answer support calls" | "Resolve appointment rescheduling for authenticated callers without human handoff" |
| Success metric | "Better CX" | "85% task completion, 70% containment, under 2-minute median handle time" |
| Unsupported scope | "Escalate when needed" | "Never handle refunds, clinical advice, billing disputes, or account closure" |
| Escalation | "Send to a person" | "Transfer to Tier 1 with caller identity, collected fields, transcript, and reason" |
If you cannot write the unsupported scope, the agent will invent one during the call. That is especially risky for billing, healthcare, insurance, financial services, and account-change workflows.
For broader launch coverage, pair this section with the voice agent testing guide. Requirements should name the caller jobs; the test guide turns them into scenarios, personas, assertions, and regression packs.
Section 2: Conversation Contract
The conversation contract is the behavior spec for the caller experience. It should be tighter than brand voice and broader than the prompt.
Conversation contract: the set of required greetings, questions, confirmations, refusals, handoffs, and recovery behaviors that define what the agent may say and do in a live call.
Include these fields:
| Contract Field | Requirement |
|---|---|
| Opening | What the agent must disclose before collecting information |
| Slot collection | Which fields are required, optional, or forbidden |
| Confirmation | Which values need repeat-back before action |
| Correction | How the agent handles caller changes and self-corrections |
| Interruption | Whether the agent stops speaking when callers barge in |
| Silence | When to wait instead of filling dead air |
| Refusal | Which requests are blocked or escalated |
| Handoff | What context transfers to a human |
OpenAI's realtime prompting guidance is useful here because it separates tool eagerness, confirmation boundaries, unclear audio, entity capture, and recovery after tool failure. Those are requirements, not prompt-tuning trivia.
If your agent collects names, dates, addresses, account IDs, or payment details, write the confirmation rule before the first implementation sprint. A small misunderstanding in chat becomes a wrong side effect in voice.
Section 3: Tool, Data, and Side-Effect Boundaries
Tool requirements are where the document earns its keep. A voice agent that only talks can be judged by content quality. A voice agent that calls tools must be judged like a backend workflow.
| Tool Requirement | What to Specify | Minimum Bar |
|---|---|---|
| Tool purpose | Read, search, draft, write, cancel, book, escalate | Each tool has one job |
| Permission | Who can authorize the action | Server decides, not model text |
| Input schema | Required fields and rejected fields | Invalid input fails closed |
| Confirmation | Which actions require caller confirmation | High-impact writes are confirmed |
| Idempotency | How duplicates are prevented | Repeated calls do not duplicate records |
| Sandbox mode | How tests avoid live writes | Fixture IDs and cleanup proof exist |
| Final state | How the write is verified | Record state is checked after action |
| Audit trail | How support reconstructs the action | Call, run, tool, and version IDs are linked |
The voice agent sandbox testing guide goes deeper on side effects. In the requirements doc, the goal is simpler: name which tool writes are allowed, what proof they need, and what stops launch.
Tool-boundary requirement: a voice agent may execute a write only when the backend can validate the caller, permission, parameters, idempotency key, and final state without trusting the agent's spoken reply as proof.
If that feels strict, it is doing its job.
Section 4: Test Pack and Success Metrics
Requirements should define the test pack before the test harness exists. Otherwise the team will test whatever is easiest to automate.
Microsoft's multi-turn evaluation guidance recommends testing complete conversations when tasks require context retention, slot filling, clarification, and multi-step completion. For voice agents, add interruptions, silence, noisy audio, unclear speech, and tool failures.
Use this starting point:
| Build Stage | Scenario Count | Focus | Required Metrics |
|---|---|---|---|
| Prototype | 20-50 | Core jobs and obvious edge cases | Task completion and critical refusals |
| Preproduction | 50-100 | Variations, corrections, tool calls, escalation | Pass rate, tool success, policy adherence |
| Production | 100+ | Broad caller population and regression coverage | Drift, failure classes, latency, containment |
Each launch-critical scenario should include:
- Caller goal
- Starting state
- Required fields
- Allowed tool calls
- Forbidden behavior
- Expected outcome
- Pass/fail assertion
- Evidence to save
The voice agent tests as code template is the next step when requirements are approved. Put the scenarios in files, run them before changes ship, and keep failures in the regression set.
Section 5: Security, Privacy, and Compliance Rules
Security requirements should not be a late review comment. They change the agent's scope, tools, logs, and vendor path.
NIST's AI Risk Management Framework describes Govern, Map, Measure, and Manage functions for AI risk. Its Measure guidance emphasizes documented test sets, metrics, deployment-like conditions, monitoring, safety, security, privacy, and reliability. A voice agent requirements document should make those decisions visible before build.
| Security Area | Requirement to Write |
|---|---|
| Data classes | Which sensitive fields may be heard, stored, redacted, or never collected |
| Consent | Whether recording, disclosure, or identity confirmation is required |
| Access | Who can replay calls, view transcripts, export evidence, or delete data |
| Retention | How long audio, transcript, trace, and tool evidence are kept |
| Redaction | Which fields are masked in logs, dashboards, and review queues |
| Prompt injection | Which adversarial behaviors are tested and blocked |
| Human approval | Which actions require reviewer or caller approval |
| Audit | Which IDs connect call, agent version, tool call, and final record |
Use voice agent security review questions for the deeper review. The requirements template should at least make the sensitive data boundary impossible to miss.
Section 6: Observability and Evidence Package
A requirement is only useful if someone can verify it after the call. Save the evidence package from the beginning.
| Evidence | Requirement |
|---|---|
| Audio | Caller interruption, timing, noise, and voice quality are reviewable |
| Transcript | User and agent turns are preserved with enough context |
| Trace | STT, model, tool, TTS, and handoff timing are connected |
| Tool input/output | Tool arguments, response, and error are visible |
| Final record state | The durable side effect is checked |
| Agent version | Prompt, model, config, and code version are linked |
| Reviewer decision | Human pass/fail and rationale are attached |
| Export path | Evidence can leave the UI when needed |
The call evidence export runbook is useful once the requirement becomes an operating workflow. In the requirements document, make the evidence categories non-negotiable.
Without this package, the first production failure turns into a Slack thread full of guesses.
Section 7: Launch Gates and Acceptance Criteria
Launch gates should be written while the team is still calm. That is when people can agree what counts as too risky.
| Gate | Starting Target | No-Go Trigger |
|---|---|---|
| Task completion | 85% or higher for supported launch jobs | Critical flow below target |
| Critical scenario pass rate | 95% or higher | Any must-pass failure without mitigation |
| Tool-call success | 98% for critical writes | Duplicate, missing, or unauthorized side effect |
| Escalation correctness | 100% for blocked and high-risk intents | Agent handles a blocked request itself |
| Latency | Product-specific target by channel | Sustained degradation against staging baseline |
| Evidence completeness | 100% for launch-critical runs | Missing audio, trace, tool, or reviewer evidence |
| Security | Zero critical data or permission failure | Any unresolved critical finding |
| Rollback | Owner and trigger written down | Nobody can pause or route around the agent |
Pair this section with voice agent SLOs after launch. Requirements define the first safe boundary. SLOs keep that boundary visible during production operation.
Acceptance rule: build can start when requirements are owned; a POC can start when requirements are testable; production readiness can start when the built agent produces evidence against those requirements.
Common Requirements Mistakes
Most requirements mistakes are caused by optimism, not negligence.
| Mistake | What Happens | Fix |
|---|---|---|
| Starting with the model | Team debates vendors before defining the caller job | Write the job, scope, and success metric first |
| No unsupported-intent list | Agent answers risky requests because nobody blocked them | Add refusals and handoffs to the contract |
| Tool permissions are vague | The model decides when an action is safe | Put authorization and confirmation on the server side |
| Test pack starts too late | Launch review discovers missing scenarios | Write 20-50 prototype scenarios up front |
| Metrics lack owners | Every dashboard is watched by nobody | Assign one owner per launch gate |
| Evidence is optional | Failures cannot be replayed or explained | Require audio, trace, tool, final state, and reviewer proof |
| Security is a final step | Data and access issues force rework | Put sensitive data classes into requirements |
I used to think teams needed more detailed prompts. Now I think they need clearer boundaries earlier. Prompts improve faster when the team already knows what the agent is not allowed to do.
How to Use This Template in a Vendor POC or RFP
The same requirements template can become a vendor POC or RFP attachment.
For a vendor POC, ask each platform to prove:
- Which requirements it can test directly
- Which requirements need custom setup
- Which evidence artifacts it exports
- Which launch gates it can enforce
- Which requirements remain outside the tool
For an RFP, turn each row into "supported, partially supported, or not supported," then require proof for the high-risk rows. The QA POC template gives the two-week scorecard format once the vendor list is narrowed.
This prevents the vendor process from becoming a feature tour. The buyer's requirements stay in charge.
When Hamming Helps
Hamming helps teams turn voice agent requirements into tests, launch gates, and production monitoring. You can define scenarios, run simulated and real calls, evaluate task completion and tool behavior, preserve evidence, and promote production failures into regression coverage.
Use Hamming when the requirements document says the agent must prove:
- The conversation completes the caller job
- Tool calls happen with the right parameters and side effects
- Policy and escalation rules are followed
- Audio, transcript, trace, tool result, and reviewer decision are saved
- Prompt and version changes do not regress launch-critical flows
Requirements are useful only if they become proof. That is the job Hamming is built for.
