<aside> Making large language models truly useful inside organizations
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"Use AI to remove unnecessary work and return time, focus, and creativity back to people."
I help teams do 10x more with half the effort by building context-rich, AI-powered systems that replace manual workflows.
Operating at the intersection of operations and automation, I embed AI into real-world processes - whether that means replacing internal documentation with intelligent bots, building auto-updating research agents, or deploying Slack-based tools that cut meeting time in half.
<aside> Consider the context Before building, I map the work being done, not just the tasks. I gather how humans currently handle the edge cases, what context they rely on, and what "done right" looks like. This becomes the foundation of the agent design.
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<aside> Start with the bottleneck Before writing a line of code, I find the work people hate doing—manual reports, repetitive tagging, reformatting data, context handoffs—and map out how an AI agent or microtool can eliminate it.
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<aside> Design for end users, not engineers Every tool I build feels like part of the team. Natural to use, easy to trust, and fully embedded in existing workflows (Slack, Notion, Google Sheets, email, etc.)
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<aside> Automate the automation process Using LLMs to generate prompts, build backend functions, and write documentation, I reduce build time and get internal tools to production in days, not weeks.
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| Reduces drag | By identifying repetitive or decision-heavy processes, I build AI tools that eliminate unnecessary friction from daily work. |
|---|---|
| Creates leverage | Teams can scale without hiring by offloading routine decisions to context-aware automations. |
| Improves decisions | AI tools surface relevant insights at the right time—turning fragmented data into coordinated action. |
| Enables rapid iteration | Tools are built fast, tested quickly, and updated often. I don't wait for "perfect"—I ship, learn, and refine. |