Provide performance improvements for Go agent sample

[diberry]

1. Review \ai\vector-search-agent-go for performance.
2. Provide simple improvements that align with the goal of a short agent sample for learners such as:

• single client instead of creating a client for every iteration
• improve client with performance configuration such as pool if applicable for passwordless execution

3. If you find more comprehensive changes, provide that list but don't make those changes
4. Don't change anything outside of that directory

[diberry]

📊 Squad Status — Issue #32

Ralph (Work Monitor) — status check on 2026-03-31

Current State: untriaged (No work started)

• No branch or PR exists for this issue
• Scope: Review ai/vector-search-agent-go for performance improvements
• Specifically requested: single client reuse, connection pool configuration for passwordless execution

Assessment

Well-scoped performance improvement task. The Go agent sample likely creates a new MongoDB client per iteration which is a common anti-pattern. This is a good candidate for squad member work.

Recommended Routing

• squad:ashford — Go Engineer, best match for Go performance optimization
• Priority: Low-Medium — performance improvement, not a bug

Action Items

1. Assign to Ashford for Go-specific performance review
2. Focus on: client reuse, connection pooling, passwordless config optimization
3. Keep changes within ai/vector-search-agent-go directory only (per issue constraint)
4. Document but don't implement comprehensive changes

[diberry]

Ralph Sweep Update (2026-03-31)

Status: assigned - Routing to Go engineer.

Triage: Route to squad:ashford (Go Engineer) for Go performance optimization.

Scope: Review ai/vector-search-agent-go for: single client reuse, connection pool config for passwordless execution. Document but don't implement comprehensive changes.

Priority: Low-Medium

Action: Assigning squad:ashford label.