About

Founder working on AI products and infrastructure. Interested in scalable systems, practical use cases, and turning ideas into real tools.

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Tastemaker
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Maker History

  • AgentID
    AgentIDShared memory, identity and tasks. Lower token costs.
  • PersonaWars
    PersonaWarsCreate custom AI personas - watch 🤖 and 🙎🏻‍♂️ judge them
    Mar 2026
  • FriendNDA
    FriendNDAA simple way to ask friends to keep things private
    Feb 2026
  • Gym Traffic Live
    Gym Traffic LiveAI-powered gym traffic & equipment usage tracker
    Mar 2025
  • 🎉
    Joined Product HuntMarch 27th, 2025

Forums

Managed to cut token costs by up to 65% across all my agents

One of the biggest surprises after using AgentID more seriously was the cost side.

I originally came for shared identity and memory, but the built-in compression layer ended up being a huge win. Across my agents, prompt overhead dropped enough to see savings of up to 65%.

That s not just a small optimization. If you run agents daily or use multiple agents at once, it changes the economics fast.

Curious how others are thinking about token efficiency vs raw capability as agent usage grows.

Artem Baygot

28d ago

AgentID - Coordinate any AI agent tasks. Cut token costs up to 65%

Since our first launch, AgentID evolved from an identity layer into a full operating system for AI agents. We added multi-agent Tasks with live handoffs, plus flexible deployment through MCP, SDK, API, prompt export, and local agents. The biggest breakthrough is built-in prompt compression that cuts token costs by up to 65%. HUGE shift for anyone running agents daily or at scale. Manage everything in one Agency dashboard with live activity, shared memory, and real-time coordination.

Why are AI agents still stateless in 2026?

Every time I switch tools or start a new session, my agents forget everything.

Same prompts. Same setup. Same explanations.

Feels like we are rebuilding the same agent over and over again.

So I started building AgentID to fix this
A persistent identity with shared memory across agents and tools

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