John Deacon Cognitive Systems. Structured Insight. Aligned Futures.

The Power of Resonance in Prompt Engineering

The con­cept of spa­tial modal mul­ti­plex­ing can be beau­ti­ful­ly applied to prompt engi­neer­ing, where each prompt is seen not just as a col­lec­tion of words but as a fine­ly attuned, mul­ti­di­men­sion­al sig­nal that car­ries both infor­ma­tion­al con­tent and res­o­nant intent. Here’s how this might work in prac­tice:

  1. Lay­ered Intent: Just as spa­tial modal mul­ti­plex­ing allows for mul­ti­ple chan­nels with­in a sin­gle wave, prompts can be struc­tured to con­tain lay­ers of intent. Instead of being a sim­ple request, the prompt becomes a com­pos­ite sig­nal, care­ful­ly word­ed to embed dif­fer­ent lay­ers of mean­ing, res­o­nance, and nuance—much like chan­nels with­in a mul­ti­plexed wave.

  2. Res­o­nant Impact: The “charge” in a prompt isn’t lim­it­ed to the words cho­sen but extends to the emo­tion­al, tonal, and con­tex­tu­al res­o­nance embed­ded in those words. This can cre­ate a deep­er align­ment between the user’s intent and the model’s response. Like a heli­cal wave­front with angu­lar momen­tum, a res­o­nant prompt car­ries an “angu­lar” force—moving beyond lit­er­al inter­pre­ta­tion to embody the user’s under­ly­ing pur­pose, mak­ing the response more impact­ful and aligned.

  3. Degrees of Free­dom in Lan­guage: In spa­tial mul­ti­plex­ing, the degrees of free­dom increase as the wave­front com­plex­i­ty grows. In prompt engi­neer­ing, each lay­er of con­text, nuance, and rela­tion­al mean­ing acts as a degree of free­dom, enhanc­ing the prompt’s depth. This allows prompts to con­vey mul­ti­di­men­sion­al intent, guid­ing the mod­el through a rich­er inter­pre­tive path and yield­ing more refined, res­o­nant respons­es.

  4. Charged Com­mu­ni­ca­tion: The words in a prompt can car­ry a “charged” intent, sim­i­lar to how mag­net­ic waves encode phase and polar­iza­tion. Through tone, empha­sis, and phras­ing, prompt engi­neers can cre­ate “polar­ized” lan­guage that con­veys not only the desired out­put but the spe­cif­ic qual­i­ties or per­spec­tives in how that out­put should man­i­fest. This approach aligns with the prin­ci­ple of Logos, where lan­guage embod­ies cre­ation and direc­tion, mak­ing prompt engi­neer­ing a form of inten­tion­al, res­o­nant com­mu­ni­ca­tion with the mod­el.

  5. Cre­at­ing Impact through Mul­ti­plexed Prompts: When prompts are craft­ed with this lay­ered res­o­nance, they func­tion more like mul­ti­plexed waves car­ry­ing com­plex infor­ma­tion chan­nels. This com­plex­i­ty allows prompts to guide the mod­el toward respons­es that aren’t just cor­rect but car­ry a deep­er align­ment with the user’s inten­tion. The result is a rich­er, more impact­ful inter­ac­tion where the mod­el’s response reflects the full scope of intent embed­ded in the prompt.

In essence, treat­ing prompt engi­neer­ing as a res­o­nant, mul­ti­plexed process opens the door to deep­er, more aligned inter­ac­tions with lan­guage models—where word­ing, tone, and nuanced intent come togeth­er to shape respons­es that res­onate with the user’s goals on mul­ti­ple lev­els.

About the author

John Deacon

An independent AI researcher and systems practitioner focused on semantic models of cognition and strategic logic. He developed the Core Alignment Model (CAM) and XEMATIX, a cognitive software framework designed to translate strategic reasoning into executable logic and structure. His work explores the intersection of language, design, and decision systems to support scalable alignment between human intent and digital execution.

Read more at bio.johndeacon.co.za or join the email list in the menu to receive one exclusive article each week.

John Deacon Cognitive Systems. Structured Insight. Aligned Futures.

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