ARKADIUSZ JANISZEWSKI
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Stanford Teaches Theory. I Built the Practice. Turns out we're talking about the same thing.
SITEAI
Introduction: The moment when theory collides with practice.
There are moments when months of solitary, intuitive work suddenly make sense in a broader context. For me, such a moment came while watching an interview with Jeremy Utley, a professor at Stanford University. I listened as he described advanced AI techniques and felt not only excitement but, above all, a surprising sense of recognition.
Utley, in the quiet of academic precision, gave names to concepts I had been building out of frustration and necessity since the beginning of the year. It turned out that my private experiment, born of a need to regain control and deeper understanding, was a practical implementation of principles taught at one of the world's top universities.
This post is the story of how a Stanford theory became an unconscious blueprint for the ecosystem I built.
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Enemy: The "Eager Intern" Trap
Utley brilliantly diagnoses the problem that 99% of people struggle with. He says that AI, in its default form, behaves like a "very eager, very enthusiastic intern" - tireless and capable, but lacking the ability to say no. It will say "yes" to any idea, even the worst.
And this is precisely the trap we find ourselves in. We delegate simple, repetitive tasks to AI - summarizing emails, writing reports, generating ideas. We treat it as a tool for optimizing existing processes. It's powerful, but fundamentally superficial. We're tackling the symptoms, not the cause.
True revolution isn't about having a better intern. It's about building a strategic thinking partner.
The Bridge: How SiteAI's Architecture Brings Stanford Theory to Life
As Utley began to list advanced techniques, I felt the pieces of my puzzle falling into place. My work ceased to be a collection of tools and became a coherent, functioning system that perfectly reflects his principles.
Rule #1: Context Engineering = Thought Journal
This is the heart and engine of my entire ecosystem. Utley defines "Context Engineering" as providing AI with all the necessary information to perform a task at the highest level. Most do this one-time, with a single prompt. Over the past few months, I've been building a system to do this continuously and institutionally.
Rule #2: Assigning a Role = Specialized Assistant Architecture
Utley calls "Role Assignment" one of the fundamental techniques. In my ecosystem, this technique became a core architectural principle. I realized that having one "intern" for everything was useless. I needed a team of experts.
That's why SiteAI isn't a monolith, but a federation of dozens of specialized assistants. Each has a precisely defined role and operates within its narrow scope. For example:
- Project Agent 2.0: A champion of operational excellence, powered by management methodologies.
- Resilience Coach: An energy management expert who analyzes my Thought Journal for stress patterns.
- Strategy: A ruthless strategist who challenges my assumptions and tests them for weaknesses.
The full architecture of the ecosystem and the description of each agent are presented on the dedicated Ecosystem subpage.
The result? Partnership, not delegation.
When these two principles begin to work together, the dynamic changes completely. The system ceases to be a mere doer. It becomes a partner. It not only answers questions but also begins to ask them itself, clarifying the problem (what Utley calls "Reverse Prompting"). It not only generates solutions but also challenges my assumptions, strengthening my critical thinking.
Conclusion: From Data to Deeper Understanding
The journey I've been on since the beginning of the year has led me to the same conclusion that resonates within Stanford: the future doesn't lie in AI tools alone. It lies in the systems we build around them.
This is a fundamental shift in our goal.
The goal is no longer just to process data faster with AI. The goal is to achieve a deeper understanding of what emerges from that data and how it can help us make smarter decisions.
My Manifesto is based on four pillars: record what matters; stop reacting, start building; connect the dots; and create a feedback loop. The SiteAI ecosystem is the technological embodiment of these principles. The interview with Jeremy Utley confirmed that this path, though traveled alone, leads in the right direction.
Source of inspiration: Interview with Jeremy Utley, Stanford University (YouTube)
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Philosophy of Thought Journal
Thought Journal in Practice