Piroune Balachandran

Marble's persistence is what makes World API useful beyond demos... most generative 3D stays real-time and ephemeral. A programmable endpoint that spits out downloadable assets from text, image, or video opens up actual integration paths. Curious how the Gaussian splat exports hold up in game engines.

Preloop as an MCP proxy for approval gates makes sense... agents with tool access need human checkpoints. The mobile and watch notifications are clever for async approval. Curious how you handle request state TTL when someone takes a few minutes to approve from their phone.

28 hidden risks is a concrete number... GPS and camera model are obvious, but lens corrections and editing software versions can fingerprint devices too. Browser-only approach is the right call here. Curious if DropTidy handles HEIC or just standard JPEG/PNG.

Multi-person meeting scheduling is where most calendar tools tap out. They can block your time, but they dont reason about everyones constraints at once. Curious how Callum handles edge cases like recurring conflicts or attendees across different orgs with limited calendar visibility.

Offloading CAPTCHA handling and HTML normalization to an API layer is a smart move for agent developers. Crustdata positioning itself as the web search layer for AI agents seems very promising. I am curious how the accuracy holds up on sites with robust bot detection.

Offloading CAPTCHA handling and HTML normalization to an API layer makes sense for agent devs. Crustdata positioning as the web search layer for AI agents is smart... curious how the accuracy holds on sites with heavy bot detection like LinkedIn or G2.

Google Sheets as the data layer is smart for small-medium chains... the editing UX beats any custom CMS. Dmitry's question about messy addresses is the real test though. Most no-code locators punt on validation and just pass garbage to the geocoder. Address normalization before the geocode step would make this way more reliable.

AgentEcho's numbered DOM markers plus selector export is what sets it apart from screenshot-and-arrow tools. Devs can actually query those elements in the codebase. Curious if it captures shadow DOM or just top-level nodes.

Privacy Twins is the right approach here. Redacted prompts lose context and the LLM hallucinates around the gaps. For structured data like tables or JSON where field relationships matter, the swap has to preserve schema integrity or downstream processing breaks.

32 parallel coder+judge pairs is a smart setup. The judge comparison logic is the interesting part... wondering if it just checks against torch.compile baseline or if you can define custom metrics like memory footprint or specific tensor core utilization targets.

Pay what you want is smart positioning here. SessionWatcher and CodexBar charge a few bucks, which adds friction when youre already paying $20-200/month for Claude. Curious if you pull from rate limit headers or just parse /usage output... the session vs weekly distinction matters when youre trying to time a reset around a big refactor.

Managing agents from a doc instead of CLI or IDE is an interesting surface choice. The human-as-editor flow (agents commit, you refine before PR) makes sense... curious if Tonkotsu has guardrails for scope creep when multiple agents run in parallel on the same codebase.