There's this narrative that prompt engineering is dying because models got smarter. I don't buy it. The gap between people who get mediocre outputs and people who get exceptional ones is still huge — we see it daily through Fahhim.
The frameworks that keep delivering for us: ICDF (Instruction, Context, Data, Format) for structured tasks, and a simple rule — always show the model an example of the output you want. That single habit fixes most weak responses.
What's your most-used technique? I'm always collecting new patterns.
I wrote this up in more detail in the full blog post — The Complete Guide to Prompt Engineering in 2026 — with the deeper context, data, and code. Give it a read if you're curious.
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