Lindy vs Manus

Lindy lets you build personal or business AI agents without writing code: connect your email, calendar, CRM, and other apps, then configure an agent with triggers (e.g., "a new email arrives") and actions (e.g., "draft a reply," "add to CRM," "schedule a follow-up"). Pre-built templates cover common workflows like inbox triage, meeting scheduling, and lead qualification, which can be customized rather than built from scratch. Agents run continuously in the background, acting on new events as they happen rather than only when triggered manually. The free tier supports a small number of tasks and agents, enough to test a single workflow; paid plans starting around $49.99/mo raise task limits and allow more agents and integrations. Building genuinely useful agents takes some iteration — overly broad instructions tend to produce inconsistent results — and costs scale with both the number of agents and the volume of tasks they handle.

Manus is a general-purpose autonomous agent: give it a goal in plain language, and it plans a sequence of steps — searching the web, writing and executing code, creating files — inside its own cloud sandbox, with a live view of its progress and reasoning as it works. Unlike narrow coding agents, Manus is aimed at open-ended deliverables: research reports with citations, data analysis with spreadsheets and charts, simple websites, or slide decks, produced as downloadable files at the end of a run. The free tier provides a limited number of tasks/credits per month, enough to evaluate the agent on a real task; paid plans starting around $39/mo provide significantly more credits for regular use. Complex, multi-stage tasks can consume credits quickly, and while Manus is impressively autonomous, results on ambiguous or large-scope requests still benefit from human review and follow-up refinement.

• + No-code builder for personal/business AI assistants
• + Pre-built templates for common workflows
• + Connects to email, calendar, CRM, and more
• + Agents run continuously in the background

• – Free tier limited to a small number of tasks/credits
• – Effective agents take iteration to configure well
• – Pricing increases with task volume and agent count

• + Handles broad, open-ended tasks autonomously
• + Works in its own sandboxed cloud environment with live progress
• + Produces ready-to-use deliverables (files, slides, mini-apps)
• + Free tier available to try

• – Credit-based usage can be consumed quickly on complex tasks
• – Ambiguous tasks still need human review
• – Can be slower than specialized tools for simple jobs