March 5, 2026
Bring popcorn to your calendar
Launch HN: Vela (YC W26) – AI for complex scheduling
AI calendar chaos: “Scheduling solved?” sparks a nerd brawl
TLDR: Vela says its AI can book complex multi-person meetings across channels without fuss. The crowd loves the ambition but debates the “solved” claim—experts cite hard math, others share battle-tested tools, and founders suggest tough arenas like surgeries, making this a promising idea under a microscope.
Two YC brothers dropped Vela, an AI that wrangles messy multi-person scheduling across email, SMS, WhatsApp, Slack, and even phone. The demo promised “no links, no back-and-forth,” and a staffing firm onboarded in 10 minutes. Cue the community drama: academics and engineers immediately side-eyed the bold vibe, with one calling the “Scheduling solved” slogan confusing and reminding everyone that scheduling is a thorny beast. Another flexed a university project where they scheduled 200 interviews using optimization software, basically saying: cool idea, but we’ve been grinding this for years. On the cheer squad, founders chimed in with real-world pain points—like hospital surgeries where nothing takes the time you expect—and hoped Vela’s AI could handle the chaos. In the middle: pragmatists who love the “AI that follows up when people ghost” and handles “y tm wrks” texts, but warn that identity-matching across channels and human etiquette might be the real boss level. The mood: excited yet skeptical, with hot takes about NP-hard problems (translation: extremely tough) and whether Vela is more polished assistant than math wizard. If the calendar is a battlefield, HN showed up with calculators, battle scars, and bocce tournament war stories. Popcorn-worthy
Key Points
- •Vela, founded by brothers Gobhanu and Saatvik (YC W26), automates multi-party, multi-channel scheduling using AI agents.
- •The system integrates across email, SMS, WhatsApp, Slack, and phone, and can connect with existing systems like ATS to handle proposals, confirmations, follow-ups, and rescheduling.
- •An early enterprise customer (a staffing firm) reported Vela automated complex interview scheduling with approximately 10 minutes of onboarding.
- •Vela addresses data challenges by building behavioral datasets (e.g., response latency, channel preferences, follow-up timing, and optimal option counts) to adapt interactions by audience segment.
- •A core technical challenge is maintaining cross-channel state and identity resolution, interpreting temporal language, extracting structured constraints from natural language, and deciding when to clarify versus infer.