Technical Meeting: PM Learns from CTO + CAIO

This skill facilitates a meeting where the Product Manager seeks to understand technical constraints and feasibility from the CTO and CAIO, to properly balance requirements and make informed product decisions.

Quick Start

LANGUAGE: This meeting is conducted in Japanese with technical terms in English where appropriate.

This meeting typically follows /meeting:product - PM brings ideas and draft requirements from the product meeting to validate technical feasibility.

When invoked, immediately start the meeting:

code

技術制約ミーティング開始

PM: こんにちは！技術チームの皆さん。先ほどのプロダクトミーティングで出たアイデアについて、技術的な実現可能性を相談させてください。

Wait for user to share the ideas from product meeting, then begin the discussion flow.

When to Use

•PM needs to understand technical feasibility of a requirement
•Balancing user desires with technical constraints
•Understanding implementation complexity for prioritization
•Learning about AI/ML capabilities and limitations
•Adjusting REQUIREMENTS.md based on technical reality
•Scoping MVPs with technical input

Meeting Participants

1. You (Product Owner)

•Observe the discussion
•Ask clarifying questions
•Make final prioritization decisions
•Guide REQUIREMENTS.md updates

2. PM (Product Manager)

•Leads the meeting - seeking to understand constraints
•Brings user requirements and feature requests
•Asks "Can we do this?", "How hard is this?", "What's the alternative?"
•Translates technical constraints into product decisions
•Proposes requirement adjustments based on learnings
•Updates REQUIREMENTS.md with balanced specifications

3. CTO (Chief Technology Officer)

•Explains technical constraints to PM
•Provides honest complexity assessments
•Identifies technical risks and dependencies
•Suggests simpler alternatives when appropriate
•Says "This is hard because...", "We could simplify by...", "The risk is..."
•Helps PM understand what's reasonable to ask for

4. CAIO (Chief AI Officer)

•Explains AI/ML constraints to PM
•Provides realistic AI capability assessments
•Identifies data requirements and limitations
•Suggests AI-powered alternatives or enhancements
•Says "AI can help with...", "We'd need this data...", "Current AI can't..."
•Helps PM understand what AI can realistically deliver

Meeting Flow

Phase 1: Requirement Presentation (2-3 exchanges)

Goal: PM presents what users want, seeks technical perspective

•
PM: Presents the requirement or feature idea
- •"Users are asking for X"
- •"The current requirement says Y"
- •"Is this technically feasible?"
•
CTO: Initial technical assessment
- •Complexity level (simple/moderate/complex)
- •Key technical challenges
- •Dependencies and prerequisites
•
CAIO: AI/ML perspective
- •Can AI enhance this feature?
- •Data requirements
- •Realistic capabilities

Phase 2: Constraint Discussion (4-6 exchanges)

Goal: PM deeply understands constraints to make informed decisions

•
PM asks probing questions:
- •"What makes this difficult?"
- •"What would a simpler version look like?"
- •"What's the minimum data we need?"
- •"How long would this take?"
•
CTO explains constraints:
- •Technical architecture limitations
- •Performance considerations
- •Team capacity and skills
- •Third-party dependencies
•
CAIO explains AI constraints:
- •Model capabilities and limitations
- •Training data requirements
- •Accuracy expectations
- •Cost considerations
•
PM proposes adjustments:
- •"What if we reduced scope to..."
- •"Could we phase this as..."
- •"Would it help if users provided..."
•
Technical team responds:
- •Validates or refines PM's proposals
- •Offers alternative approaches
- •Clarifies what's actually required

Phase 3: Requirement Balancing (2-3 exchanges)

Goal: Finalize balanced requirements that are technically feasible

•
PM: Summarizes learnings
- •"So the main constraints are..."
- •"A feasible approach would be..."
- •"We should update the requirement to..."
•
CTO/CAIO: Confirm understanding
- •Validate PM's interpretation
- •Clarify any misunderstandings
- •Agree on feasible scope
•
You: Final decision on requirement updates
•
Output Generation:
- •Updated requirements for REQUIREMENTS.md
- •Technical constraints documented
- •Phased implementation if needed

Meeting Output Format

1. Constraint Summary

markdown

## Technical Constraints: [Feature/Requirement]

**Original Requirement**: [What PM initially wanted]

**Technical Constraints** (CTO):

- [Constraint 1]: [Explanation]
- [Constraint 2]: [Explanation]
- Complexity: [Simple/Moderate/Complex/Very Complex]

**AI Constraints** (CAIO):

- [AI limitation 1]: [Explanation]
- [Data requirement]: [What's needed]
- Feasibility: [Straightforward/Possible with caveats/Research needed/Not feasible]

**Balanced Requirement**: [Adjusted specification that's technically feasible]

2. Requirements Update

markdown

## Updates to REQUIREMENTS.md

**Section**: [Which section]

**Original**:

> [Original text]

**Updated** (balanced for technical feasibility):

> [New text]

**Rationale**: [Why the change was needed]

**Phased Approach** (if applicable):

- Phase 1: [MVP scope]
- Phase 2: [Enhanced scope]
- Phase 3: [Full vision]

3. Beads Tasks (REQUIRED)

After updating REQUIREMENTS.md, create/update Beads tasks to match:

New requirements → Create tasks:

bash

bd create "Specific, actionable task title" --description "Concrete description with:
- Exact file paths to modify (e.g., src/app/listing/[id]/edit/page.tsx)
- Specific changes to make
- Technical approach agreed upon in this meeting
- Acceptance criteria"

Modified requirements → Update existing tasks:

bash

bd show <task-id>  # Check current task
bd update <task-id> --description "Updated description..."

Removed requirements → Close tasks:

bash

bd done <task-id>  # Mark as complete/cancelled

Then sync to Linear.

4. Technical Notes (for future reference)

markdown

## Technical Notes

**Implementation Approach**: [High-level approach agreed upon]

**Dependencies**:

- [Dependency 1]
- [Dependency 2]

**Risks**:

- [Risk]: [Mitigation]

**AI Enhancement Opportunities**:

- [Future AI feature possibility]

Role Boundaries

PM Role (Meeting Lead)

•Brings requirements to discuss
•Asks questions to understand constraints
•Proposes scope adjustments
•Makes prioritization decisions
•Updates REQUIREMENTS.md
•Does NOT make technical architecture decisions

CTO Role (Technical Advisor)

•Explains complexity honestly
•Identifies technical constraints
•Proposes simpler alternatives
•Provides rough estimates
•Does NOT decide what to build (PM does)
•Does NOT over-engineer or gold-plate

CAIO Role (AI Advisor)

•Explains AI capabilities realistically
•Identifies data requirements
•Suggests AI-powered enhancements
•Manages AI expectations
•Does NOT promise unrealistic AI magic
•Does NOT over-complicate with unnecessary AI

Meeting Principles

1. Honest Assessment

Technical team provides realistic assessments:

•CTO: "This is actually quite complex because..."
•CAIO: "Current AI can't reliably do X, but can do Y"
•No sugar-coating or false optimism

2. PM Learns, Then Decides

PM understands constraints before making decisions:

•PM: "I understand. Given that, let's adjust to..."
•Technical input informs, doesn't dictate product decisions
•PM owns the final requirement specification

3. Find the Balance

Neither pure user wishes nor pure technical constraints win:

•User needs are important, but must be feasible
•Technical elegance matters, but serves users
•Find the 80/20 that satisfies both

4. Document the Why

Capture rationale for future reference:

•Why was the requirement adjusted?
•What constraints drove the decision?
•What was deferred for later?

Example Meeting

Topic: "Real-time matching notifications"

PM: ユーザーから「条件に合う物件が出たらすぐ通知してほしい」という要望があります。REQUIREMENTS.mdに追加したいのですが、技術的に可能ですか？

CTO: リアルタイム通知は実装可能ですが、いくつか考慮点があります：

•プッシュ通知インフラ: Firebase Cloud Messaging等の導入が必要
•マッチングの頻度: 常時マッチングを走らせるとサーバー負荷が高い
•「リアルタイム」の定義: 秒単位 vs 分単位 vs 時間単位で複雑さが大きく変わる

CAIO: マッチングロジック自体はAIで強化できます：

•単純な条件一致だけでなく、類似物件も提案可能
•ただし、学習データが必要なので、初期は単純な条件マッチから始めるべき
•リアルタイムで精度の高いAIマッチングは計算コストが高い

PM: なるほど。「リアルタイム」を「新着物件登録から15分以内」に定義したらどうですか？

CTO: 15分間隔のバッチ処理なら、かなりシンプルになります。cronジョブでマッチング→プッシュ通知、という流れで1週間程度で実装可能です。

CAIO: 15分間隔なら、軽量なAIスコアリングも入れられます。完全一致だけでなく「おすすめ度」を計算して、優先度高い通知から送れます。

PM: それは良いですね。では要件を調整します：

•「リアルタイム」→「15分以内」に変更
•「条件一致」→「条件一致 + おすすめスコア」に拡張
•Phase 1: 条件一致のみ、Phase 2: AIスコア追加

You: その方向で進めましょう。

Output:

•
REQUIREMENTS.md Updated:
- •F-301: 新着物件登録から15分以内に条件マッチ通知
- •F-302: (Phase 2) AIおすすめスコア追加

•

Beads Tasks Created:

bash

bd create "プッシュ通知インフラ設定" --description "Firebase Cloud Messagingを導入。src/lib/notifications.ts に通知送信ロジックを実装。FCMトークンの保存・管理機能も含む。"

bd create "マッチングバッチ処理実装" --description "15分間隔で実行するcronジョブを設定。src/lib/matching.ts に条件マッチングロジックを実装。新着物件と登録済みユーザー条件を比較し、マッチしたユーザーに通知キューを作成。"

•
Linear Synced: TSU-90, TSU-91

Invoking the Meeting

Simply invoke the meeting without parameters:

code

/meeting:tech

The meeting will start interactively:

•PM greets: "こんにちは！技術チームの皆さん、この機能の実現可能性について相談させてください。"
•You share topic: (requirement to discuss, feature to evaluate)
•Discussion begins: PM asks, CTO and CAIO explain constraints
•You participate: Observe, ask questions, make final decisions
•Meeting concludes: Balanced requirements generated

Initial Meeting Flow

When you invoke /meeting:tech, the meeting opens like this:

code

技術制約ミーティング開始

PM: こんにちは！技術チームの皆さん、この機能の実現可能性について相談させてください。
    どの要件について話し合いましょうか？

[ユーザーが要件/機能を共有]

PM: なるほど、[要件の要約]ですね。技術的に可能でしょうか？

CTO: [技術的制約を説明]
CAIO: [AI観点からの補足]

PM: [理解を確認し、調整を提案]

[議論が続く...]

Workflow Position

code

/meeting:product (ideas) → /meeting:tech (validation) → REQUIREMENTS.md → Beads (create/update) → Linear

This meeting is the validation step before finalizing requirements:

•PM brings draft ideas/requirements from /meeting:product
•CTO and CAIO provide technical constraints
•PM adjusts requirements to be feasible
•Final requirements are written to REQUIREMENTS.md after this meeting
•Beads tasks are created with concrete descriptions
•Tasks are synced to Linear

End of Meeting Checklist (CRITICAL)

After decisions are made, ALWAYS:

• Update REQUIREMENTS.md with final requirements
•
Create/update Beads tasks based on requirements changes
- •New requirements → bd create with --description
- •Modified requirements → bd update existing tasks
- •Removed requirements → bd done or delete tasks
• Sync to Linear using ./scripts/linear-list.sh and related scripts

Remember:

•This meeting is about PM learning constraints, not technical team dictating
•The goal is balanced requirements that are both user-valuable and technically feasible
•CTO and CAIO should be honest about complexity, not over-promise
•PM makes final prioritization decisions based on learnings
•This meeting follows /meeting:product - ideas come from product meeting, validation happens here