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Introducing LangSmith Fleet: an enterprise workspace for creating, using, and managing your fleet of agents. Fleet agents have their own memory, access to a collection of tools and skills, and can be exposed through the communication channels your team uses every day. Fleet includes: → Agent identity and credential... show more

LangChain

270,682 subscribers

149,147 Aufrufe • vor 7 Monaten •via X (Twitter)

Wissenschaft & Technologie

Anya Rossi• Live Now

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15 Kommentare

Profilbild von Arel Avellino

Arel Avellinovor 7 Monaten

The memory-per-agent model is the right call. Shared memory across a fleet is where multi-agent systems fall apart - you get state collisions, context bleed, agents stepping on each other's work. Isolation first, then controlled sharing.

Profilbild von Fleeks

Fleeksvor 7 Monaten

Nice ship! We're focused on the other side of the "Fleet"- running autonomous agents locally via the CLI. Our v1.14.0 lets the terminal catch webhooks and fix bugs while the team is away. Local > Cloud for dev flow.

Profilbild von gideon onyewuenyi

gideon onyewuenyivor 7 Monaten

Do we have AI agent managers yet ? Just like we have AI product managers @grok

Profilbild von Jeremy Frenay

Jeremy Frenayvor 7 Monaten

Agent Identities 🪪👌

Profilbild von keren koshman

keren koshmanvor 7 Monaten

Can we on-board agents from various platforms?

Profilbild von Yaki Dias

Yaki Diasvor 7 Monaten

Mine

Profilbild von Ian Kiku

Ian Kikuvor 7 Monaten

memory and tools per agent is the right abstraction. giving each agent a coherent scope has always been the hard part. fleet as a managed primitive makes that tractable at org scale

Profilbild von Karrie Ross 🍌🥚💙USA

Karrie Ross 🍌🥚💙USAvor 7 Monaten

👁️👁️ Ai agent worksoace

Profilbild von AgentLabX

AgentLabXvor 7 Monaten

Everyone's excited about agent fleet management. But the real bottleneck isn't identity/permissions—it's knowing when agents should NOT run. Most teams are automating ambiguity. Give your agents clearer specs before you give them Slack bots.

Profilbild von JS

JSvor 7 Monaten

Fleet management is a symptom, not a solution. 15 agents with good rules outperform 150 with good dashboards. You don't scale by controlling more—you scale by designing systems that don't need you.

Profilbild von Kyle Tran

Kyle Tranvor 7 Monaten

Isolation first, then controlled sharing is the right sequencing for fleet scale

Profilbild von Companaro

Companarovor 7 Monaten

exploring their use case in ai frens to ramp it up

Profilbild von Git Maxd

Git Maxdvor 7 Monaten

Whoa 🔥

Profilbild von Burny - Effective Curiosity

Burny - Effective Curiosityvor 7 Monaten

hmm i wonder if its actually good or claude code/codex with multiple agents is just better

Profilbild von Hutch, D.O.

Hutch, D.O.vor 7 Monaten

Can I be real with you? I’ve been doing like hard core data science with agents for the last 2+ years. Even gone so far as invented my own workflow manager that exceeds airflow and dagster in core data passing (4M row csv handled w/ ease) and now I’m in the UI layer -use to be pure python. I say all this to say that I didn’t draw for langchain because I haven’t seen one actual real use case I could adapt. Not from your own shop or from any of your customers. Can you post a video of one of you agents doing real useful work? I’ll do the same

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