AI tool comparison
Google ADK vs Jet AI Agents
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Agent Frameworks
Google ADK
Google's open-source multi-agent framework built for production from day one
75%
Panel ship
—
Community
Paid
Entry
Google Agent Development Kit (ADK) is an open-source Python framework for building, evaluating, and deploying multi-agent systems at production scale. It handles orchestration with built-in tool calling, memory management, structured output, streaming, and first-class connectors for Vertex AI, Gemini, and any OpenAI-compatible API. ADK's philosophy is agent-as-code rather than visual builders. Agents are Python classes with typed inputs/outputs, making them testable, versionable, and CI/CD-compatible from day one. The framework includes an evaluation harness, artifact management, session persistence, and failure recovery — all the production plumbing that most agent frameworks leave to the developer. The multi-agent layer handles spawning, communication, and coordination between agents as a platform primitive rather than custom glue code. With 8,200+ GitHub stars since its April release, ADK is already one of the most-watched agent frameworks. The combination of Google's infrastructure backing, Apache 2.0 licensing, and pragmatic production focus sets it apart from research-oriented frameworks. It's the entry point to Google's broader agentic infrastructure stack, including the newly announced 8th-gen TPUs.
AI Agents
Jet AI Agents
Build business AI agents with 200+ integrations in minutes, no code
75%
Panel ship
—
Community
Free
Entry
Jet AI Agents is a no-code platform for building and deploying business AI agents across marketing, sales, operations, and support workflows. Teams connect it to their data sources, drag-and-drop UI components into place, and deploy agents that take action rather than just display dashboards. It integrates with 200+ tools including Slack, WhatsApp, Telegram, and popular CRMs. Backed by Y Combinator and built by founders Anton Svetlov and Denis Kildishev, Jet supports both Claude (Anthropic) and OpenAI models as its inference layer, giving teams flexibility on which LLM powers their agents. The platform maintains a 4.43-star rating on Product Hunt with users praising its low learning curve and ability to handle complex external data source integrations without engineering help. Jet AI Agents debuted at #2 on Product Hunt's daily leaderboard on April 27, 2026. For non-technical business teams that want to automate multi-step workflows across SaaS tools — without filing tickets to engineering — Jet offers a polished on-ramp with a free tier to start. The YC backing suggests runway for the enterprise integrations that will make or break the platform.
Reviewer scorecard
“The evaluation harness and session persistence are what make this real. Most frameworks give you the happy path and leave you to build all the production scaffolding yourself. ADK ships with the hard parts included, which is why it hit 8K stars so fast.”
“YC pedigree and 200+ integrations is a solid combination. The dual Claude/OpenAI model support means you're not locked in, and the API-first architecture makes it extensible beyond the visual builder. Worth a pilot for ops teams tired of Zapier's limitations.”
“Google has a graveyard of developer platforms it's abandoned — Stadia, Firebase, Cloud Functions v1. Betting your production agent infrastructure on Google's continued commitment to an open-source framework is a real risk, especially when LangChain and CrewAI have two years of community momentum.”
“The no-code agent builder space is brutally competitive — n8n, Make, Relay, and a dozen YC graduates are fighting for the same seat. 'Build in minutes' claims rarely survive contact with enterprise data schemas. Test your actual use case before committing.”
“Google is making a stack bet: ADK → Vertex AI → 8th-gen TPUs. If that stack wins, ADK becomes the Rails of agentic AI — the default framework for the majority of production deployments. The infrastructure integration is the moat that makes this more than just another orchestration layer.”
“Business teams that can build and own their own agents without engineering dependencies is a structural shift in how companies will operate. Jet is betting on the right abstraction layer capturing this market — YC's validation makes the bet credible.”
“Typed inputs and outputs for agents finally makes multi-agent pipelines debuggable. I can build a research → draft → review → publish pipeline and actually understand what's happening at each stage — instead of debugging opaque string-passing between prompts.”
“As someone who runs content workflows across Slack, Notion, and Google Workspace, having an agent that takes action across all three without code is genuinely useful. The visual builder is clean and the free tier gives enough to prototype a real workflow.”
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