About us
Enterprise AI isn't about demo day — it's about deployment day.
We're a community for practitioners building, deploying, and scaling AI inside enterprises. Not proofs-of-concept that gather dust. Not buzzwords. Not slideware. We're here to tackle the hard problems: integration, deploying, governance, monitoring, security, ROI, and the messy middle between pilot and production.
We regularly invite tech leads, engineers, data scientists, and decision-makers from enterprises to:
- Discuss with practitioners who've shipped AI in production at scale
- Share the hard-earned lessons — what broke, what worked, what they'd do differently
- Showcase real solutions to real enterprise problems
You belong here if you're:
- A developer, engineer, or data scientist building AI into enterprise systems
- A tech lead or architect designing AI infrastructure and pipelines
- A tech decision-maker evaluating, adopting, or governing AI in your organization
- Anyone who wants to move beyond the hype and learn what actually works in production
If you’d like to speak at our meetups, co-host your events, or inquire about partnership opportunities, please feel free to reach out to us.
https://www.aicamp.ai
Upcoming events
1
AI Deep Dive (Virtual) - Building Self-Improving Agents
·OnlineOnlineImportant: Register on the event website to receive the joining link. (rsvp on meetup will NOT receive anything).
This is virtual event for our AI global community, please double-check your local time. Can't make it live? Register anyway to receive the webinar recording.
Join Snowflake to learn how to build self-improving agents
Tech Talk: Your Agent Should Fix Itself: Building Self-Improving Agents
Speaker: Elliot Botwick, Principal AI/ML Architect, Snowflake
Abstract: In this talk, we will share how coding agents help developers build high quality agents faster.
A key insight from building agents in production is that high quality agents operate with their goals, plans and actions aligned. We introduce the Agent Goal-Plan-Action (Agent GPA) framework to capture this insight, which achieved state of the art benchmarks on TRAIL/GAIA with 95% error coverage and 86% error localization.
The Agent GPA framework assesses the full agent's process:- Was the goal achieved efficiently?
- Did the plan make sense?
- Were the right tools used?
- Did the agent follow through?
Without visibility into these steps, teams risk deploying agents that look reliable but create hidden costs in production. Inaccuracies can waste compute, inflate latency and lead to the wrong business decisions, all of which erode trust at scale.
We will show how to use coding agents to automate the process of measuring and improving your agent's GPA by using optimization skills that take advantage of the GPA evaluation framework. By the end, you’ll be able to use coding agents and the GPA framework to identify common agent failures, improve their agent and make it ready for production.Venue:
Virtual, join from anywhereMore virtual sessions:
14 attendees
Past events
189
