“Unusual was obliged to invent a lot of the magic he did, working from normal rules and half-remembered tales from outdated books.”
— Susanna Clarke, Jonathan Unusual & Mr Norrell
Fairy tales, myths, and fantasy fiction are filled with magic spells. You say “abracadabra” and one thing profound occurs.1 Say “open sesame” and the door swings open.
It seems that that is additionally a helpful metaphor for what occurs with giant language fashions.
I first received this concept from David Griffiths’s O’Reilly course on utilizing AI to spice up your productiveness. He gave a easy instance. You possibly can inform ChatGPT “Arrange my process listing utilizing the Eisenhower four-sided field.” And it simply is aware of what to do, even for those who your self know nothing about Normal Dwight D. Eisenhower’s strategy to resolution making. David then suggests his college students as a substitute attempt “Arrange my process listing utilizing Getting Issues Carried out,” or simply “Use GTD.” Every of these phrases is shorthand for techniques of thought, practices, and conventions that the mannequin has discovered from human tradition.
These are magic phrases. They’re magic not as a result of they do one thing unworldly and sudden however as a result of they’ve the ability to summon patterns which have been encoded within the mannequin. The phrases act as keys, unlocking context and even total workflows.
All of us use magic phrases in our prompts. We are saying one thing like “Replace my resume” or “Draft a Substack submit” with out pondering how a lot detailed prompting we’d should do to create that output if the LLM didn’t already know the magic phrase.
Each subject has a specialised language whose phrases are recognized solely to its initiates. We will be fanciful and faux they’re magic spells, however the actuality is that every of them is known as a type of fuzzy perform name to an LLM, bringing in a physique of context and unlocking a set of behaviors and capabilities. After we ask an LLM to put in writing a program in Javascript relatively than Python, we’re utilizing considered one of these fuzzy perform calls. After we ask for output as an .md file, we’re doing the identical. In contrast to a perform name in a standard programming language, it doesn’t at all times return the identical consequence, which is why builders have a possibility to boost the magic.
From Prompts to Purposes
The following mild bulb went off for me in a dialog with Claire Vo, the creator of an AI software known as ChatPRD. Claire spent years as a product supervisor, and as quickly as ChatGPT grew to become obtainable, started utilizing it to assist her write product requirement paperwork or PRDs. Each product supervisor is aware of what a PRD is. When Claire prompted ChatGPT to “write a PRD,” it didn’t want a protracted preamble. That one acronym carried a long time {of professional} observe. However Claire went additional. She refined her prompts, improved them, and taught ChatGPT the right way to suppose like her. Over time, she had skilled a system, not on the mannequin degree, however on the degree of context and workflow.
Subsequent, Claire turned her workflow right into a product. That product is a software program interface that wraps up a lot of associated magic phrases right into a helpful package deal. It controls entry to her personalized magic spell, so to talk. Claire added detailed prompts, integrations with different instruments, entry management, and a complete lot of conventional programming in a next-generation software that makes use of a mixture of conventional software program code and “magical” fuzzy perform calls to an LLM. ChatPRD even interviews customers to be taught extra about their objectives, customizing the appliance for every group and use case.
Claire’s quickstart information to ChatPRD is a superb instance of what a magic-word (fuzzy perform name) software appears like.
It’s also possible to see how magic phrases are crafted into magic spells and the way these spells are even a part of the structure of functions like Claude Code via the explorations of builders like Jesse Vincent and Simon Willison.
In “How I’m Utilizing Coding Brokers in September, 2025,” Jesse first describes how his claude.md file supplies a base immediate that “encodes a bunch of course of documentation and guidelines that do a fairly good job conserving Claude on monitor.” After which his workflow calls on a bunch of specialised prompts he has created (i.e., “spells” that give clearer and extra customized which means to particular magic phrases) like “brainstorm,” “plan,” “architect,” “implement,” “debug,” and so forth. Word how inside these prompts, he might use further magic phrases like DRY, YAGNI, and TDD, which check with particular programming methodologies. For instance, right here’s his planning immediate (boldface mine):
Nice. I would like your assist to put in writing out a complete implementation plan.
Assume that the engineer has zero context for our codebase and questionablestyle. doc every part they should know. which recordsdata to the touch for everyprocess, code, testing, docs they may have to examine. the right way to take a look at it.givethem the entire plan as bite-sized duties. DRY. YAGNI. TDD. frequent commits.
Assume they're a talented developer, however know nearly nothing about ourtoolset or downside area. assume they do not know good take a look at designveryeffectively.
please write out this plan, in full element, into docs/plans/
However Jesse didn’t cease there. He constructed a undertaking known as Superpowers, which makes use of Claude’s not too long ago introduced plug-in structure to “give Claude Code superpowers with a complete expertise library of confirmed strategies, patterns, and instruments.” Asserting the undertaking, he wrote:
Expertise are what give your brokers Superpowers. The primary time they actually popped up on my radar was a couple of weeks in the past when Anthropic rolled out improved Workplace doc creation. When the function rolled out, I went poking round a bit – I requested Claude to inform me all about its new expertise. And it was solely too completely happy to dish…. [Be sure to follow this link! – TOR]
One of many first expertise I taught Superpowers was The way to create expertise. That has meant that after I wished to do one thing like add git worktree workflows to Superpowers, it was a matter of describing how I wished the workflows to go…after which Claude put the items collectively and added a pair notes to the prevailing expertise that wanted to clue future-Claude into utilizing worktrees.
After studying Jesse’s submit, Simon Willison did a bit extra digging into the unique doc dealing with expertise that Claude had introduced and that had sparked Jesse’s brainstorm. He famous:
Expertise are extra than simply prompts although: the repository additionally consists of dozens of pre-written Python scripts for performing frequent operations.
pdf/scripts/fill_fillable_fields.py for instance is a customized CLI software that makes use of pypdf to seek out after which fill in a bunch of PDF type fields, specified as JSON, then render out the ensuing mixed PDF.
It is a actually refined set of instruments for doc manipulation, and I really like that Anthropic have made these seen—presumably intentionally—to customers of Claude who know the right way to ask for them.
You possibly can see what’s occurring right here. Magic phrases are being enhanced and given a extra rigorous definition, and new ones are being added to what, in fantasy tales, they name a “grimoire,” or guide of spells. Microsoft calls such spells “metacognitive recipes,” an exquisite time period that ought to get broadly adopted, although on this article I’m going to stay with my fanciful analogy to magic.
At O’Reilly, we’re working with a really totally different set of magic phrases. For instance, we’re constructing a system for exactly focused competency-based studying, via which our clients can skip what they already know, grasp what they want, and show what they’ve discovered. It additionally offers company studying system managers the flexibility to assign studying objectives and to measure the ROI on their funding.
It seems that there are dozens of studying frameworks (and that’s itself a magic phrase). Within the design of our personal specialised studying framework, we’re invoking Bloom’s taxonomy, SFIA, and the Dreyfus Mannequin of Talent Acquisition. However when a buyer says, “We love your strategy, however we use LTEM,” we will invoke that framework as a substitute. Each company buyer additionally has its personal specialised tech stack. So we’re exploring the right way to use magic phrases to let no matter we construct adapt dynamically not solely to our finish customers’ studying wants however to the tech stack and to the educational framework that already exists at every firm.
That may be a nightmare if we needed to assist dozens of various studying frameworks utilizing conventional processes. However the issue appears way more tractable if we’re in a position to invoke the correct magic phrases. That’s what I imply after I say that magic phrases are a vital constructing block within the subsequent era of software programming.
The Structure of Magic
Right here’s the essential factor: Magic isn’t arbitrary. In each mythic custom, it has construction, self-discipline, and value. The magician’s energy depends upon understanding the correct phrases, pronounced in the correct method, with the correct intent.
The identical is true for AI techniques. The effectiveness of our magic phrases depends upon context, grounding, and suggestions loops that give the mannequin dependable details about the world.
That’s why I discover the rising ecosystem of AI functions so fascinating. It’s about offering the correct context to the mannequin. It’s about defining vocabularies, workflows, and roles that expose and make sense of the mannequin’s skills. It’s about turning implicit cultural information into specific techniques of interplay.
We’re solely firstly. However simply as early programmers discovered to construct structured software program with out spelling out precise machine directions, at present’s AI practitioners are studying to construct structured reasoning techniques out of fuzzy language patterns.
Magic phrases aren’t only a poetic picture. They’re the syntax of a brand new type of computing. As individuals grow to be extra snug with LLMs, they are going to move across the magic phrases they’ve discovered as energy consumer tips. In the meantime, builders will wrap extra superior capabilities round present magic phrases and maybe even train the fashions new ones that haven’t but had the time to accrete ample which means via huge utilization within the coaching set. Every software might be constructed round a shared vocabulary that encodes its area information. Again in 2022, Mike Loukides known as these techniques “formal casual languages.” That’s, they’re spoken in human language, however do higher whenever you apply a little bit of rigor.
And at the very least for the foreseeable future, builders will write “shims” between the magic phrases that management the LLMs and the extra conventional programming instruments and strategies that interface with present techniques, a lot as Claire did with ChatPRD. However finally we’ll see true AI to AI communication.
Magic phrases and the spells constructed round them are solely the start. As soon as individuals begin utilizing them in frequent, they grow to be protocols. They outline how people and AI techniques cooperate, and the way AI techniques cooperate with one another.
We will already see this occurring. Frameworks like LangChain or the Mannequin Context Protocol (MCP) formalize how context and instruments are shared. Groups construct agentic workflows that depend upon a typical vocabulary of intent. What’s an MCP server, in any case, however a mapping of a fuzzy perform name right into a set of predictable instruments and companies obtainable at a given endpoint?
In different phrases, what was as soon as a set of magic spells is turning into infrastructure. When sufficient individuals use the identical magic phrases, they cease being magic and begin being requirements—the constructing blocks for the subsequent era of software program.
We will already see this development with MCP. There are three distinct sorts of MCP servers. Some, like Playwright MCP, are designed to make it simpler for AIs to interface with functions initially designed for interactive human use. Others, just like the GitHub MCP Server, are designed to make it simpler for AIs to interface with present APIs, that’s, with interfaces initially designed to be known as by conventional packages. However some are designed as a frontend for a real AI-to-AI dialog. Different protocols, like A2A, are already optimized for this third use case.
However in every case, an MCP server is known as a dictionary (or in magic phrases, a spellbook) that explains the magic phrases that it understands and the right way to invoke them. As Jesse Vincent put it to me after studying a draft of this piece:
The half that feels essentially the most like magic spells is the half that almost all MCP authors do extremely poorly. Every software has a “description” subject that tells the LLM how you employ the software. That description subject is learn and internalized by the LLM and adjustments the way it behaves. Anthropic are significantly good at software descriptions and most all people else, in my expertise, is…much less good.
In some ways, publishing the prompts, software descriptions, context, and expertise that add performance to LLMs could also be a extra essential frontier of open supply AI than open weights. It’s essential that we deal with our enhancements to magic phrases not as proprietary secrets and techniques however as shared cultural artifacts. The extra open and participatory our vocabularies are, the extra inclusive and artistic the ensuing ecosystem might be.
Footnotes
- Whereas usually related at present with stage magic and cartoons, this magic phrase was apparently used from Roman instances as a therapeutic spell. One proposed etymology means that it comes from the Aramaic for “I create as I converse.”
