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Calendly launches AI meeting note-taker, plans Callie assistant

Calendly launched an AI product suite that includes Callie (beta), an AI scheduling assistant that can join email threads to coordinate meetings, and Calendly Notetaker, an AI meeting assistant that records audio/video, transcribes sessions, generates summaries, action items and follow-up messages, and links recaps to contacts and event types. Notetaker integrates with Zoom, Google Meet and Microsoft Teams; beta customers have used it for more than 100,000 recordings and report saving 3–4 hours per week by eliminating manual note-taking. The features began rolling out August 19, 2026 for English-language accounts, with new Standard Plus and Teams Plus plans bundling scheduling and AI capabilities. Calendly positions the tools for heavy meeting users in outward-facing roles like sales and marketing, is testing system-audio transcription, and says the assistant will proactively inform participants when recording and allow users to leave to address privacy concerns.

Prioritize Strategic Work When Everything Feels Urgent

This MarTech contributor outlines a system for prioritizing marketing work across a large business unit by linking every task to OKRs and KPIs, limiting strategic priorities to three per time horizon, measuring effort ROI, and using project-management tools plus AI automation to shift routine work. The author cites Asana and TMetric research on time spent off-strategy and in meetings, describes an "AI process map" to track which tasks are manual, AI-assisted, or AI-automated, and sets a departmental minimum that growth-focused work should represent at least 20% of tracked time.

LLM Invented a Detailed, Nonexistent Company Website

A measurement study of six Chinese LLM APIs found a model confidently describing a nonexistent localized corporate website (airtable.cn), including pricing in RMB and a China-specific privacy policy. The author logged 4,023 valid responses across the corpus, discovered the domain was registered to a private individual and returned HTTP 502, and observed that seven of eight tested brand .cn domains were not owned by the brands. To detect these operationally convincing hallucinations the author recommends lightweight predicate checks on extracted URLs, simple WHOIS/DNS/HTTP lookups, repeated phrasing checks (ask the same factual question multiple ways) and strict provenance metadata for every row. The harness and validation scripts are published under CC BY 4.0 on GitHub.