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Product Requirements Document (PRD): AI-Generated Meeting Summaries & Action Items

1. Document Overview & Objective

1.1 Product Name

Huddle Intelligent Summaries (Internal Codename: Project Cue)

1.2 Target Audience

Engineering Leads, Frontend/Backend Engineers, and Product Designers.

1.3 Objective

Build an automated, post-meeting intelligence feature for Huddle that processes meeting transcripts to extract structured decisions, generate comprehensive summaries, and assign action items to attendees. The feature must account for real-world messy transcript data (speaker errors, uninvited participants) and adhere to strict safety boundaries regarding action item assignments and automated distribution.

1.4 Background & Scenario

Huddle is a video-meeting application currently utilized by 3,000 enterprise and mid-market companies. * Existing Infrastructure: Meetings are automatically recorded and transcribed with basic speaker labeling. Attendee lists are reliably synchronized from the originating calendar invite. * Current State & Pain Point: Users currently rely on manual post-meeting note-taking, leading to dropped tasks, misaligned follow-ups, and fragmented alignment. * Value Proposition: Automating meeting wrap-ups directly inside Huddle saves hours of manual administrative overhead per week⁴, driving higher platform stickiness and daily active use.

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2. Core User Stories & Personas

2.1 Personas

• The Engineering Manager (User): Attends 5–6 back-to-back technical syncs daily. Needs clear, unequivocal records of architectural decisions and precise engineering follow-ups without digging through raw, messy transcripts.
• The Account Executive / Sales Rep (User): Operates on rapid customer cadences. Requires immediate, zero-friction distribution of post-meeting action items to stakeholders without manual typing.
• The Engineering & Design Leads (Builders): Require explicit edge-case handling, system constraints, deterministic UI layouts, and scalable pipeline specs to build and ship the feature efficiently.

2.2 Key User Stories

1. As a meeting participant, I want Huddle to automatically generate a structured summary and action item list the moment a meeting concludes, so I don't have to spend time writing manual recap notes.
2. As an attendee with assigned tasks, I want clear ownership labels on my action items so there is never any ambiguity about who is driving a deliverable.
3. As a sales representative, I want my action items emailed to me automatically as soon as the meeting ends, so I can immediately execute client follow-ups.
4. As a meeting host, I want to review, edit, or override incorrect speaker attributions or bad action assignments before summaries are locked or shared externally.

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3. Detailed Functional Requirements

3.1 Data Inputs & Pre-Processing Pipeline

The AI summarization engine triggers asynchronously via webhook immediately upon meeting termination (`recording.ended`).

• Input A: Transcript with Speaker Labels: Full text payload containing timestamped utterances, text strings, and speaker IDs. Known limitation: Speaker labels suffer from an 8% error rate, primarily caused by cross-talk, overlapping dialogue, or multi-person huddle rooms.
• Input B: Calendar Invite Attendee List: Ground-truth list of officially invited participants (Email, Name, Role).¹ Known limitation: 15% of meetings include an uninvited participant (e.g., ad-hoc joiners via shared link).
• Input C: Meeting Metadata: Duration, title, organization ID, and recording URL.

3.2 Summarization & Extraction Logic (LLM Pipeline)

The backend processing pipeline must execute three logical passes: 1. Meeting Overview Generation: Condense the transcript into a 3–5 sentence executive summary alongside 3 key thematic highlights. 2. Decision Extraction: Isolate explicit agreements, architectural choices, or policy resolutions made during the call. Format as an bulleted list of declarative statements (e.g., "Decided to migrate the primary auth service to OAuth2 by Q3"). 3. Action Item Extraction & Assignment Engine: * Extract explicit tasks, owners, and deadlines. * Crucial Constraint (Safety Guardrail): The engine must never assign an action item to someone who was not present in the meeting. * Resolution Strategy for Uninvited Attendees: If an uninvited participant (who joined without a calendar invite) is identified as the owner of a task, the system must cross-reference their presence against the audio/transcript participant logs. If verified present, they are added to a dynamic "Extended Participants" list for assignment validation. If their identity cannot be verified or they were absent, the task defaults to unassigned or falls back to the meeting host with a UI warning flag².

3.3 Sales Request: Automated Instant Emailing

• Requirement: Sales teams have requested that action items be emailed automatically to their owners the second a meeting ends.
• Product Specification & Guardrail: Due to the 8% speaker label error rate and potential hallucination risks, fully autonomous external emailing on meeting close creates high business risk.
• Implementation Design:
• Implement an Opt-In Workspace Policy configured by organization admins.
• For workspaces with "Auto-Send Sales Recaps" enabled, summaries and assigned action items are dispatched via email to internal organization members immediately upon processing completion.³
• For external participants or non-opt-in workspaces, a 10-minute "Grace Period / Review Window" notification banner appears in the Huddle desktop client, allowing hosts to review and edit assignments before dispatch.

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4. User Experience & Interface (UX/UI) Specifications

4.1 Post-Meeting View (Huddle Web & Desktop App)

Upon meeting conclusion, a new tab labeled "AI Summary" appears alongside the existing "Transcript" and "Recording" tabs within the meeting details drawer.

``` +-------------------------------------------------------------------+ | Huddle Meeting: Q3 Architecture Sync [Share] [Export]| +-------------------------------------------------------------------+ | Tabs: [Overview] [Transcript] [Recording] | |-------------------------------------------------------------------| | EXECUTIVE SUMMARY | | The team reviewed the Q3 scaling bottlenecks. Consensus was | | reached on moving auth infrastructure to OAuth2. Database latency | | issues will be mitigated via Redis caching layers. | | | | KEY DECISIONS | | • Migrate core auth service to OAuth2 by August 15. [Edit] | | • Adopt Redis cluster for session state caching. [Edit] | | | | ACTION ITEMS | | [x] Investigate OAuth2 token expiry edge cases | | Owner: Sarah Jenkins (Calendar Invite) | Due: Next Tuesday | | [ ] Set up staging Redis cluster | | Owner: Unassigned ⚠️ (Verify Attendee) | Due: Friday | | | | [Send Sales Recap Email Now] [Approve & Lock] | +-------------------------------------------------------------------+ ```

4.2 Interactive States & Edge-Case UI Handling

• Unassigned / Unverified Owner State: If the model detects an action item owner who was an uninvited participant or has an ambiguous speaker label, render a yellow warning badge: `⚠️ Unverified Owner — Click to Reassign`.
• Inline Editing: Every decision and action item card features an inline pencil icon allowing hosts or assignees to edit text, change owners via a searchable dropdown of confirmed attendees, or delete hallucinated items.

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5. Technical Architecture & Engineering Guidelines

5.1 Pipeline Flow & Data Schema

1. Webhook Listener: Receives `meeting.ended` event containing metadata and storage URIs.
2. Context Aggregator: Merges calendar invite list (`invitedusers[]`) with actual audio track speaker diarization outputs (`detectedspeakers[]`).
3. LLM Structured Extraction: Prompt engineering optimized for JSON output schema enforcement (using strict JSON mode / function calling):

```json { "meetingid": "string", "summary": "string", "decisions": ["string"], "actionitems": [ { "task": "string", "assigneeemail": "string | null", "assigneename": "string", "isverifiedattendee": boolean, "due_date": "ISO-8601 | null" } ] } ```

5.2 Error Handling & Fallbacks

• Speaker Label Inaccuracy (8% Error Rate): Mitigation via UI feedback loops. If an assignee name has low confidence score (< 0.85) from the diarization model, flag the action item with a review indicator in the UI.
• Uninvited Participant Handling (15% Occurrences): The validation layer must query the roster of active audio streams. If an email is missing from the calendar invite but present in audio metadata, tag them as `guest_participant` and permit assignment only if their voiceprint or explicit self-identification ("Hi, this is Dave from Finance joining late") is logged in the transcript text. Otherwise, fail-safe to unassigned.

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6. Non-Functional Requirements & Constraints

• Latency: Summary generation and database write must complete within < 120 seconds of meeting termination for a standard 45-minute meeting.
• Security & Privacy: Meeting transcripts and summaries must be encrypted at rest (AES-256) and in transit (TLS 1.3). Customer data must never be used to train foundational models across tenant boundaries.
• Reliability: 99.9% pipeline uptime. In the event of an LLM timeout or parsing failure, the system must gracefully fall back to displaying raw transcripts with an error banner stating "AI summary generation delayed. Click to retry."

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7. Metrics & Success Criteria (KPIs)

1. Adoption Rate: % of completed meetings where users view, edit, or export the AI summary (Target: > 40% within 30 days post-launch).
2. Action Item Completion Rate: Increase in marked-complete action items compared to legacy manual workflows.
3. Accuracy & Correction Rate: Frequency of manual edits made to action item owners and speaker assignments (Target: < 5% manual override rate, validating low false-positive rates for uninvited attendee checks).
4. Sales Workflow Efficiency: Reduction in post-call administrative turnaround time reported by enterprise sales teams using the automated email dispatch feature.

PRD: AI Meeting Summaries with Decisions and Action Items

Status: Draft for engineering and design leads Product: Huddle

1. Problem

Huddle records and transcribes meetings with speaker labels, but attendees still write their own notes afterward. Notes are late, inconsistent, or never written, so decisions get lost and action items have no clear owner. We will generate a summary after each meeting that lists decisions and proposes action items with owners.

2. Goals and non-goals

Goals - Produce a summary within 5 minutes of meeting end: decisions, action items (task, owner, due date if stated), and open questions. - Never assign an action item to someone who was not in the meeting (hard constraint, see §4). - Keep the host's review to under 60 seconds for a typical meeting.

Non-goals (v1) - Fully automatic emailing of action items to owners (see §3). - Cross-meeting task tracking or integrations with Jira, Asana, and similar tools. - Summaries for meetings without a transcript.

3. Decision on the Sales request

Sales asked for action items to be emailed automatically to owners the moment a meeting ends. We are not building that for v1. Instead, we will send the draft summary to the host at meeting end. The host can send it to owners with one click, and owners are emailed on send.

Reasons: - Speaker labels are wrong about 8% of the time. An automatic email would sometimes tell a real person they own a task they never agreed to. Because it goes out with no human check, the error becomes visible to a customer's colleagues. - Email is irreversible, so a wrong or non-attendee assignment cannot be quietly fixed afterward. - The underlying Sales need is that owners hear about their tasks quickly and nothing falls through the cracks. A host prompt at meeting end with one-click send meets that need at the cost of a few seconds.

Path to automation: Auto-send will be an opt-in, per-workspace setting, considered after launch once the gates in §9 are met. It would send only high-confidence, presence-verified items and leave everything else for host review. Engineering should build the send pipeline so that auto-send is later a policy change rather than a rebuild.

4. The hard constraint: who can own an action item

Rule: An action item's owner must be a participant who was actually in the meeting when the item was discussed. Anyone else is ineligible.

This rule cannot rely on the calendar invite, and it cannot rely on the model behaving well.

Attendance source. The eligible-owner roster is built from Huddle's session join/leave logs, not from the calendar invite. This handles both failure modes: - Invitees who never joined are not on the roster. - The roughly 15% of meetings with uninvited joiners include those people, matched to a user account when possible.

Presence at time of item. A person is eligible for an item only if they were in the session at the timestamp of the relevant utterance. Someone who left at minute 10 cannot own an item from minute 40.

Enforcement is structural, not prompt-based. 1. The extraction step receives the roster as a list of participant IDs and must return an owner ID from that list or `null`. 2. A deterministic validator runs after the model. It rejects any owner ID not on the roster or not present at the item's timestamp, and it converts that item to unassigned. 3. The UI and email layers accept only validated owner IDs. There is no free-text owner field on the model output path. 4. Names mentioned in the transcript who were not present ("have Dana look at it") produce an unassigned item. The text may keep the speaker's wording, but Dana gets no assignment and no email.

Shared rooms. A room device usually appears as one participant, so individuals in the room are not in the presence log. We cannot verify that a named person is in the room. Such items become unassigned by default, and the host can attest who was in the room during review (§6). That attestation counts as human-verified presence.

Uninvited joiners without an account (guests) can be eligible owners, shown by display name. They receive email only if the host supplies an address during review. We never guess addresses.

5. Handling speaker-label errors

The 8% label error rate is concentrated in crosstalk and shared rooms. Eligible-owner enforcement does not solve it, because a mislabel can still pick the wrong person who was present. Mitigations:

Confidence tiers (High/Medium/Low) are stored on each item, shown to the host in review, and used later to gate auto-send. Thresholds are set empirically during the evaluation in §9. The tiers themselves are a v1 requirement.

6. User experience

Host flow 1. The meeting ends and the host gets a notification: "Summary ready to review." 2. The review screen lists: - Decisions as short statements, each linked to the transcript moment. - Action items with the task, owner chip, due date if stated, and a confidence indicator. - Unassigned items grouped at the top of the actions list, so gaps are visible. 3. The host can edit text, reassign from a picker limited to eligible people, delete items, or add room attendees ("Who was in the room?"). Adding room attendees makes them eligible for items in the room segments. 4. Send emails each owner their own items plus the decisions. Unassigned items go to no one.

Design requirements - Every item has a "jump to source" link that plays the transcript segment. Reviewing should be verification, not re-listening. - The owner picker never offers non-attendees. If the host wants to assign to an absent person, show a separate option, "Send as a follow-up (not from the meeting)," which is a different item type with clearly different wording and no "you agreed to" language. Design to decide whether this ships in v1; the default is that it does not. - Low-confidence owners appear as suggestions ("Suggested: Sam") and never as assignments. - Email copy says "Action item from Meeting name, date", includes the source excerpt, and offers a "This isn't mine" link that notifies the host. This gives owners a correction path. - If the host does not review, send a reminder at 24 hours. Nothing is sent to owners without host action in v1.

7. Functional requirements

1. Roster service: builds the per-meeting roster with join/leave intervals from session logs and links to user accounts where possible.
2. Extraction: from the transcript and roster, produce decisions, action items, and unassigned items. Each action item has task text, owner ID or null, due date or null, source timestamps, and a confidence tier.
3. Validator: enforces §4 as code with unit tests, independent of the model, and logs every rejection.
4. Review UI: as described in §6, on web and desktop. Mobile is view-only for v1.
5. Delivery: per-owner emails on host send, with a record of who was emailed. Sends are idempotent, and edits after sending trigger an explicit "send update" action.
6. Audit log: stores for each item the model output, validator result, host edits, and send events.
7. Admin setting: workspace-level toggle for summaries, plus retention aligned with existing transcript retention.

8. Edge cases to specify and test

• Invitee never joined but is mentioned as owner.
• Uninvited joiner takes an action; the guest has no account.
• Person leaves and rejoins (multiple intervals).
• Two people share a first name; ownership must resolve by roster, and ambiguity means unassigned.
• Whole meeting in a shared room (all items default unassigned until the host attests).
• Multiple languages, or a transcript with large gaps.
• Nobody commits to anything: show "No action items detected" rather than inventing some.

9. Success metrics and launch gates

Launch gates (must all pass) - Zero non-attendee assignments across a labeled evaluation set of at least 500 meetings, deliberately oversampled for uninvited joiners, shared rooms, no-show invitees, and crosstalk. Any production occurrence afterward is a Sev-1 incident. - Among High-confidence items, wrong-attendee assignment rate of 3% or less (target, to be validated against the evaluation set; propose a stricter figure if data supports it). - Median summary delivery within 5 minutes of meeting end.

Post-launch metrics - Share of meetings where the host sends the summary within 1 hour. - Host edit rate per item, and owner "This isn't mine" rate. - Share of action items left unassigned. Some is healthy, but a high rate means the model is too timid.

Auto-send criteria (future): two consecutive months of High-tier precision above the agreed bar and no non-attendee incidents. Sales and Support are consulted before enabling.

10. Risks and open questions

• Sales disagreement. Sales may see the host step as friction. We should share §3 with them early and offer a pilot of auto-send with a few design-partner accounts after the gates are met.
• Hosts skipping review. If sending rates are low, the fix is better reminders and faster review, not removing the check.
• Presence data quality. Do our session logs reliably capture join/leave for all clients and dial-in users? Engineering to confirm in week 1.
• Guest privacy. Can we email or display guest names without consent, given customer policies? Legal to advise.
• Room attestation. Is host attestation adequate for the constraint, or should room participants confirm individually? Recommend host attestation for v1.
• Follow-up items for absent people. Ship in v1 or defer? Design and Product to decide.

11. Milestones

1. Weeks 1–2: roster service, presence data audit, evaluation set labeling begins.
2. Weeks 3–5: extraction, validator, confidence tiers, offline evaluation.
3. Weeks 4–7: review UI and email delivery, in parallel.
4. Weeks 8–9: internal dogfood, gate review.
5. Week 10: limited beta with design-partner customers, including Sales' accounts.