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Jordan Camas
Professor Denise Maduli-Williams
English C1000
22 September 2026
Writing, Reading, and AI in the Pharmacy Field
Introduction
For this project, I interviewed my friend Victor, a pharmacy technician intern who
is also studying for his PTCB certification exam. I chose the pharmacy field because it
connects to my interest in biological sciences, and since Victor already works inside it,
he gave me an honest, specific look at what writing, reading, and AI really look like on
the job.
Writing in the Field
Writing in pharmacy is short but exact, and every piece has a specific reader:
prescription labels and system entries go to the pharmacist and patient, shift notes like
“patient requested generic” go to whoever works next, and prior authorization forms and
faxes go to doctors’ offices, all so the right person always has an accurate record to act
on. He also logs controlled substance inventory. As he put it, “one wrong number or a
misspelled drug name can cause real problems.” That reframed writing for me: in this
field it's a safety tool, not a style exercise, and the key skill is staying precise even
when things get busy.
Reading & Research in the Field
Victor reads prescriptions all day, some handwritten and hard to decipher, plus drug
labels, procedures, insurance rejection messages, recall notices, and material for his
certification exam. This reading makes him faster and safer: recognizing look-alike drug
names like
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hydroxyzine and hydralazine helps him catch errors before they reach the
pharmacist, and understanding insurance codes lets him fix problems himself
instead of making patients wait. ​
AI in the Field
AI plays a bigger role here than I expected, mostly running in the background:
flagging drug interactions, powering automated dispensing machines, and predicting
inventory reorders. But Victor was clear it assists rather than replaces judgment. He
warned about “alert fatigue,” where too many warnings cause people to click through
without reading, and about privacy, since entering patient information into a public tool
like ChatGPT would violate HIPAA. AI is fine for personal studying, he said, but only if
you double-check it against a real reference. ​
Advice & Personal Connection
Victor's advice: get hands-on experience early, start learning the top 200 drugs
now, pursue PTCB certification, ask questions, and never treat AI as something that will
do the job for you. My prediction about drug-interaction checking and inventory tracking
held up, but I hadn't considered alert fatigue or HIPAA risk, small reminder that the
technology is only as safe as the person double-checking it. This connects directly to
my goals in biological sciences: succeeding here will take more than knowing the
science. I'll need to read dense technical material comfortably, write with real precision,
and understand a tool's limits instead of trusting it blindly, a habit worth building now as
a writer, not later as a professional.