← Back to AI Insights
Gemini Executive Synthesis

Velt's Activity Logs, an SDK feature for tracking actions of both human users and AI agents.

Technical Positioning
Addresses the accountability gap in products integrating AI agents by providing a unified, immutable activity log for both human and agent actions, ensuring consistent workflow accountability.
SaaS Insight & Market Implications
The proliferation of AI agents within products introduces a critical accountability gap: agent actions are often untracked, unlike human activities. Velt's Activity Logs directly addresses this by providing a unified, immutable record for both human and AI agent actions. This solution is crucial for maintaining workflow integrity, auditing, and compliance in AI-augmented environments. The problem statement "Most products have no idea what their AI agents did yesterday" highlights a significant oversight in current AI integration strategies. This product capitalizes on the growing need for governance and transparency in AI-driven workflows, indicating a strong market demand for robust logging and accountability features in collaboration SDKs.
Proprietary Technical Taxonomy
collaboration SDKs Comments presence real-time editing (CRDT) recording notifications AI agents Activity Logs

Raw Developer Origin & Technical Request

Source Icon Hacker News Apr 3, 2026
Show HN: Most products have no idea what their AI agents did yesterday

We build collaboration SDKs at Velt (YC W22). Comments, presence, real-time editing (CRDT), recording, notifications.A pattern we keep seeing: products add AI agents that write, edit, and approve things. Human actions get logged. Agent actions don't. Same workflow, different accountability.We shipped Activity Logs to fix this.Same record for humans and AI agents. Immutable by default. Auto-captures collaboration events, plus createActivity() for your own.Curious how others are handling this.

Developer Debate & Comments

No active discussions extracted for this entry yet.

Engagement Signals

3
Upvotes
0
Comments

Cross-Market Term Frequency

Quantifies the cross-market adoption of foundational terms like AI agents and recording by tracking occurrence frequency across active SaaS architectures and enterprise developer debates.