RamBot
AI implementation & enablement case study
01 · Challenge
Teachers must translate standards, curriculum materials, student needs, and schoolwide expectations into coherent weekly plans and daily instruction. The friction was in organizing many inputs into one usable starting point.
02 · Needs / Context
The solution needed to support existing instructional expectations, accept teacher-provided context, and create editable outputs without replacing professional judgment.
03 · My Role
I identified the workflow need, defined requirements, designed the input and prompt architecture, established output rules, tested drafts, and refined the system.
04 · Analysis / Approach
I mapped the planning workflow, identified required inputs and evidence of alignment, translated the instructional framework into system guidance, and reviewed outputs for clarity, completeness, and usability.
05 · Solution
A custom GPT instructional-planning assistant that converts structured teacher input into standards-aligned planning materials and supports targeted revisions.
06 · Implementation
I developed and iterated the custom GPT, its knowledge base, structured input flow, output expectations, and PowerPoint-generation workflow. Formal case-study documentation is still in progress.
07 · Results / Impact
Validated results, usage data, and stakeholder feedback have not yet been added. This section will be updated only when evidence is available.
08 · Tools
ChatGPT Custom GPT · Prompt architecture · Knowledge-base design · Python / python-pptx · Instructional frameworks
09 · What I Learned / Next Iteration
Useful AI systems require clear requirements, domain expertise, structured inputs, testing, and continuous refinement. Next: document the implementation, gather feedback, and define appropriate measures of usefulness and adoption.