Tasklet takes the "just tell it what to do" approach further than most. You describe a task in conversation, and its agent figures out the tools, the steps, and the execution order on its own. It can even use browser automation to interact with apps that don't have APIs. For quick personal automations where you want zero upfront setup, Tasklet is impressively fast.
The tradeoff is control. Tasklet's agent decides how to do the work, which means it sometimes gets it wrong. There's no visual representation of what will happen before it runs, no mid-workflow approval gates, and no way to see what a run cost you. For an individual prototyping automations, that's fine. For a team running workflows that touch customer data, send external emails, or hit paid APIs, you need more structure.
How they compare
| General Input | Tasklet | |
|---|---|---|
| Natural language workflow creation | ||
| Reviewable workflow before deployment | ||
| Always-on background workflows | ||
| Triggers (schedule, webhook, email) | ||
| Human-in-the-loop approval gates | ||
| Choose any LLM (OpenAI, Anthropic, open source) | ||
| Team workspaces with permissions | ||
| Per-execution cost transparency | ||
| Self-hosted / on-prem deployment | ||
| Browser automation (computer use) | ||
| Credential encryption isolated from AI | ||
| Deterministic code workflows |
When to use Tasklet
Tasklet is the fastest path from "I want this automated" to a running agent. If you're an individual or small team exploring what to automate and want something working in minutes with zero configuration, Tasklet's conversational model delivers. Its browser automation also handles apps that don't offer APIs, which is genuinely useful for scraping or legacy tools.
When to use General Input
General Input is for teams that need to trust what their automations do before they run.
- Review before it runs. General Input generates a structured workflow you can inspect, edit, and approve before deploying. Tasklet's agent decides the approach at runtime, so you don't see what it will do until it does it.
- Real approval gates. Human-in-the-loop steps that pause the workflow and wait for a person to approve, edit, or reject. Not post-run notifications.
- Three workflow modes. App integrations for connecting tools. Deterministic scripts for logic that must run the same way every time. AI agents for tasks that need reasoning. Tasklet only does the agent mode.
- Model choice and cost visibility. Pick any LLM provider and see what every run costs, broken down by step. Tasklet uses a fixed model stack and doesn't surface run costs.
- Enterprise security. Credentials encrypted and isolated from model context. Full audit logs. On-prem deployment for regulated industries. Tasklet is early-stage with SOC 2 still on the roadmap.
Better together
Tasklet is great for exploring what to automate. General Input is where those automations grow up. Use Tasklet to prototype quickly, then rebuild in General Input when the workflow needs team permissions, cost tracking, and the reliability of a reviewable, structured execution.