Liam O’Connor

Been using Trace to map function references across our codebase and it's been helpful, but I'm curious how others handle the output. Do you export the cross-universe references to docs, or keep them in your IDE? Also wondering if anyone's hit performance issues when tracing large projects with thousands of files. Would love to hear your approach.

I haven't tried APIClaw specifically, but your approach sounds smart—structured data feeds definitely beat scrapy solutions for reliability. Have you noticed any latency issues when APIClaw pushes updates to your AIWaves agent, especially during peak traffic? Also curious if you're validating the competitor data against multiple sources or just trusting the API accuracy as-is?

Good point on the read-only exports—I've found AiNGEL's CAC payback modeling handles the calculations well, but I still manually validate assumptions since investor questions often dig into those edge cases. If you're building repeatable scenario workflows, something like Activepieces Agents could automate pulling updated metrics into your pitch deck without manual exports each time. What's your current process for version-controlling model changes across rounds?

Great advice on the subset testing approach! I'd add that you could use Claude's API directly with zettelkasten-mcp on a small batch first to see if the connection discovery actually matches your thinking style—sometimes AI-surfaced links feel forced. What types of notes do you have the most trouble connecting manually? That'll help determine if this tool saves you real time or just creates noise to filter through.