Tasklet

Executive Summary

Tasklet is an AI agent automation platform that replaces traditional workflow builders with conversational, long-lived agents. Instead of building step-by-step automations in Zapier or n8n, users describe what they want in plain English and the AI figures out how to execute it. Built by Andrew Lee, co-founder of Firebase, and the team behind the Shortwave email client, Tasklet represents a bet that AI models are now capable enough to handle open-ended automation without rigid workflow definitions.

Attribute	Value
Company	Tasklet.ai (by Shortwave)
Founded	2025
Funding	$9M (Shortwave)
Investors	Union Square Ventures, Lightspeed Venture Partners
Headquarters	San Francisco, CA

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Product Overview

Tasklet fundamentally differs from traditional automation tools by using a single AI agent that handles all tasks through natural language, rather than requiring users to build explicit workflows or state machines. Users describe what they want — "Send me a daily briefing based on my calendar, inbox, and task list" — and the agent determines how to accomplish it, which tools to use, and what integrations to set up.

The product emerged from Shortwave's AI email assistant when users requested automatic execution of prompts they were running repeatedly. The team realized their agent technology could automate far more than email, leading to a standalone product designed for general-purpose business automation.

Key Capabilities

Capability	Description
Plain English Setup	Describe automations conversationally; AI handles implementation
Trigger Types	Scheduled (daily/weekly/custom), email-based, webhooks
Integration Breadth	Thousands of pre-built + any HTTP API + MCP servers + computer use
Long-lived Agents	Maintain ongoing relationship with feedback incorporation
Computer Use	Browser automation as fallback for unsupported services

Product Surfaces

Surface	Description	Availability
Web App	Primary interface for creating and managing agents	GA
Email Integration	Trigger automations from incoming emails	GA
Webhook API	External services can trigger agent runs	GA
Shortwave Integration	Native integration with Shortwave email client	GA

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Technical Architecture

Tasklet uses a two-tier agent architecture:

1. High-level agents maintain instructions and spawn sub-agents for individual runs
2. Run-level agents execute specific tasks and report back

This enables both recurring automation (daily briefings, weekly reports) and ad-hoc assistance within the same framework.

User Request → Tasklet Agent (persistent)
                    ↓
              Run Agent (per execution)
                    ↓
        Integrations / APIs / MCP / Computer Use

Integration Strategy

Tasklet's integration approach prioritizes flexibility over a fixed connector library:

1. Pre-built integrations — Thousands of popular services (Gmail, Slack, Notion, Asana, HubSpot, etc.)
2. HTTP API fallback — Provide any API documentation and credentials; agent figures out the calls
3. MCP servers — Model Context Protocol for specialized integrations
4. Computer use — Browser automation for services without APIs (Anthropic's computer use capability)

Key Technical Details

Aspect	Detail
Deployment	Hosted SaaS
Model(s)	Anthropic Claude (primary)
Context Management	Memory, context compaction, SQL databases for state
Open Source	No

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Strengths

• Radically simple UX — No workflow builder, no node graphs, no code. Just describe what you want and iterate on results. Firebase alumni Michael Lehenbauer notes they're "empowering users with powerful capabilities behind a ruthlessly simple UX."

• Integration depth without lock-in — Pre-built integrations for common tools, but also native support for arbitrary APIs, MCP servers, and browser automation. If a service exists, Tasklet can likely interact with it.

• Error resilience — Unlike workflow products that break on unexpected states, agentic execution can adapt and work around issues. "If you run into an error state in a workflow product... it just breaks. In an agent product, it just kind of figures it out, works around it."

• Proven team — Andrew Lee co-founded Firebase (acquired by Google, now used by millions). The Shortwave team has deep experience building developer tools and AI products.

• Model-forward philosophy — Tasklet bets on rapidly improving model capabilities rather than building constraints around current limitations. As models improve, Tasklet's capabilities automatically expand.

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Cautions

• Reliability concerns for critical tasks — Agentic systems can be unpredictable. For mission-critical automation, deterministic workflow tools may be safer.

• Cost transparency — AI model inference costs can be unpredictable for complex tasks. No public usage-based pricing details beyond the $35/month tier.

• Enterprise features still developing — Logging, security controls, and cost management are "on the roadmap" rather than GA.

• Anthropic model dependency — Primary reliance on Claude means Anthropic outages or pricing changes directly impact Tasklet.

• Early product maturity — Launched October 2025. Limited track record for long-term reliability and edge cases compared to established players like Zapier (10+ years).

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Pricing & Licensing

Tier	Price	Includes
Free	$0	Basic usage, limited runs
Pro	$35/mo	Higher usage limits, 1 computer use instance, data opt-out
Enterprise	Contact	Coming — security controls, logging, cost management

Licensing model: Subscription (SaaS)

Hidden costs: Heavy automation usage may hit limits; computer use (browser automation) adds latency and cost.

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Competitive Positioning

Direct Competitors

Competitor	Differentiation
Zapier	Zapier requires building explicit workflows; Tasklet uses natural language. Zapier has 8,000+ integrations vs. Tasklet's flexible API approach.
n8n	n8n is open-source and self-hosted; Tasklet is hosted SaaS. n8n requires technical users; Tasklet targets non-technical users.
Make	Make (Integromat) has visual data routing; Tasklet has no visual builder — pure conversation.
Lindy	Both use AI agents for personal automation. Lindy focuses on AI assistants; Tasklet focuses on recurring business automation.

When to Choose Tasklet Over Alternatives

• Choose Tasklet when: You want automation without learning workflow builders, and you're comfortable with AI agents making decisions
• Choose Zapier when: You need predictable, deterministic automation with maximum integration breadth
• Choose n8n when: You want self-hosted, open-source automation with full control
• Choose Lindy when: You want an AI personal assistant for ad-hoc tasks rather than recurring automation
• Choose Make when: You need complex data transformations with visual debugging

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Ideal Customer Profile

Best fit:

• Small business owners who need automation but lack technical skills
• Teams tired of maintaining brittle Zapier workflows
• Users comfortable with AI handling implementation details
• People who want "virtual employees" for recurring tasks
• Early adopters willing to trade some reliability for simplicity

Poor fit:

• Enterprise teams requiring audit trails and compliance controls (today)
• Organizations needing deterministic, predictable automation
• Teams with existing investment in n8n/Make/Zapier workflows
• Cost-sensitive users who need predictable pricing at scale

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Viability Assessment

Factor	Assessment
Financial Health	Strong — $9M raised, backed by tier-1 VCs (USV, Lightspeed)
Market Position	Challenger — new entrant in crowded automation space
Innovation Pace	Rapid — shipping weekly during beta, strong roadmap
Community/Ecosystem	Growing — active Product Hunt presence, podcast coverage
Long-term Outlook	Positive — Firebase team track record, strong market thesis

The Shortwave/Tasklet team has exceptional pedigree (Firebase acquisition) and venture backing from Union Square Ventures and Lightspeed. Andrew Lee's thesis — "always bet on the models" — positions Tasklet well if AI capabilities continue advancing rapidly. The risk is whether mainstream users will trust AI agents for business-critical automation before enterprise features mature.

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Bottom Line

Tasklet represents a bold bet that AI models are now capable enough to replace workflow builders entirely. Instead of the "AI assists workflow creation" approach (String, Relay), Tasklet uses AI for both planning and execution — no workflows at all, just agents that figure things out.

Recommended for: Non-technical users who want automation without learning workflow tools, small business owners who need "set and forget" automations, and early adopters comfortable with AI agents making decisions.

Not recommended for: Enterprise buyers requiring audit trails today, teams needing deterministic automation for compliance, or users with complex existing workflow investments.

Outlook: If Andrew Lee's thesis holds — that betting on model improvements is the winning strategy — Tasklet could disrupt the workflow automation market the way Firebase disrupted backend infrastructure. The team has the track record and funding to execute. The question is timing: are models ready for "always-on" business automation, or is Tasklet a year too early?

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Research by Ry Walker Research • methodology