How a Remote Company Builds AI Fluency — Em Shreve, Automattic
Summary
Automattic, a fully distributed company, emphasizes that AI fluency requires dedicated, real-time learning rather than simply providing tools. They run intensive, two-week in-person programs for engineers, cross-functional teams, and non-technical staff. The curriculum progresses from foundational skills and responsible AI use to advanced topics like creating custom MCPs, utilizing the hook system of Codecs and Claude, and developing autonomous agents. The program is designed to make every graduate a 'multiplier' through structured knowledge sharing, local meetups, and building practical, company-adopted tools.
Key takeaways
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AI Enablement Requires Dedicated Learning Time
0:55
The core philosophy is that simply handing out AI tools is insufficient; people need real time to learn and experiment to change their way of working. (0:55)
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The Two-Week Immersive Program Model
1:55
The program is structured as 50% facilitated learning (workshops) and 50% real project work, allowing participants to build tools or create new skills/MCPs relevant to their daily tasks. (1:15)
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Scaling Knowledge Through Multipliers
10:19
To ensure reach across the distributed company, graduates are encouraged to become 'multipliers' through a 'guides program' (champions), local AI gettogethers, and AI ride-alongs. (6:19, 7:09)
Technical details
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AI Infrastructure & Development
325s
The curriculum covers foundational skills, spec-driven development, and advanced concepts like creating MCPs (Micro-Capability Platforms) for new functionality. Advanced topics include utilizing the hook system of Codecs and Claude, and building autonomous agents/routines. (3:25)
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Internal Tooling and Governance
524s
Automattic uses an internal MCP server called `context automatic` to rapidly add new tooling sets, allowing for governance and observability layers on custom MCPs. (5:24)
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Project Examples and Adoption
Successful projects built by participants include an agentic analytics system for WooCommerce, a Zendesk connector (adopted company-wide), and a shared skills directory that supports multiple tools (Codecs, Claude, etc.). (12:29)
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Measurement and Improvement
Effectiveness is measured using surveys at 72 hours, 30 days, and 90 days, tracking metrics like 'intentionality' (thoughtful AI application) and 'flow' (integration into workflows). (11:09)
Mentioned resources
- Automattic
- Codecs
- Claude
- context automatic
Channel & topics
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