Timely vs Cursor
Side-by-side trajectory, velocity, and editorial themes.
Timely repositions Memory.app as the time tracker that understands AI-tool work.
The dominant theme is AI-aware activity capture. Memory.app — Timely's local capture agent — now distinguishes Claude Desktop, Claude Code, Cowork, Codex, and Cursor Agents as discrete tools, pulls real window titles and URLs, and scrubs credentials from captured URLs before storage. Around that, Timely keeps grinding through platform work: inline project creation, OAuth auto-refresh, project audit logs, native changelog page, and integration manager improvements.
Timely is racing to be the time tracker that knows what AI tools you used and what you used them for. The Memory capture layer is being rebuilt assuming AI tools, agents, and chat sessions are first-class workstreams, not generic 'browser activity.' The platform updates underneath — audit logs, integration housekeeping, OAuth resilience — are keeping the enterprise surface presentable while the differentiation work happens in capture.
Expect support for more AI tools (Anthropic console, ChatGPT Desktop, Gemini, copilots inside IDEs) and richer project attribution heuristics that tie a conversation or branch to a billable project automatically. Privacy controls around AI activity capture are the natural next product question.
Stacking platform plays — SDK, security agents, fleet environments — in a single sprint.
Cursor is firing on multiple platform-expansion fronts at once. In the past month it has shipped: a programmable SDK that exposes its agent runtime to third-party developers, a Security Review surface with always-on PR security and vulnerability-scanning agents, configurable multi-repo development environments for cloud agents, and admin-side controls (model gating, soft spend limits, granular usage analytics). The cadence is weekly; the substance is platform-grade rather than feature-grade.
Cursor is migrating from "AI-native IDE" to "platform for AI engineering at organizational scale." The SDK turns it into infrastructure for other builders, Security Review creates a recurring always-on agent surface inside customer codebases, and multi-repo environments make fleets of parallel agents actually plausible in real engineering setups. Each release lowers the marginal cost of running many agents against one company's code.
Expect a bundled "agent fleet" tier for enterprise — environments, security agents, SDK access, model governance, and seat-level analytics priced together — within a quarter. Watch for tighter hooks into CI and observability so the output of these agent fleets becomes auditable and measurable, not just shippable.
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