🏛️ Four design philosophies
Each provider, a signature. The same problem—refusing, declaring capabilities, formatting—gets four different answers. Comparing Anthropic, OpenAI, Google/Microsoft, and xAI side by side isn’t about collecting trivia: it’s learn to choose the right philosophy for your product.
Detailed content
What a provider "signature" is
Read ten anonymous leaked prompts and you'll start to guess who wrote them—not by the product, but by way of giving instructions. There’s a recurring style: how the provider states rules, justifies decisions, structures blocks, and calibrates tone. This stable pattern is the subscription. Recognizing it is the first step toward choosing — because choosing a philosophy means deciding which trade-offs you accept.
What it is
The signature is the set of style decisions that a provider repeats across all of its prompts: rule size (short sentence vs. paragraph explaining why), how capabilities are declared (list vs. function schema), block delimiters (Markdown vs. XML tags), and tone calibration (neutral, opinionated, empathetic).
It isn't arbitrary: each signature optimizes for an objective. Anthropic optimizes for generalization and safety; OpenAI for modular reuse across channels; Google/Microsoft for procedural predictability; xAI for density and voice.
Why learn (comparing is learning to choose)
Anyone who knows only one philosophy tends to apply it everywhere—and pays the wrong cost. A voice assistant written in the Anthropic style (long, justified paragraphs) becomes too verbose; an empathetic chatbot written in the Microsoft CLI style (100-word limit, procedural) feels cold. Comparing builds your expertise: you start choosing the subscription for the task, not out of habit.
Blind spot test
Take a loose paragraph from any prompt in the collection, without the file name. Ask: does the rule explains why? Use XML tags? É short and opinionated? It comes as numbered step-by-step guide? With 3 clues, you can identify the provider. This is the assessment activity for this module.
Anthropic — long principle with rationale
Anthropic's signature is justified principle: the rule is rarely a flat prohibition — it explains the intent, so the model generalize to new situations. Add to that the consolidation (a few dense rules instead of many scattered ones), the safety by default and delimitation by semantic XML tags.
Anthropic/claude-fable-5.md (line 52, child-safety)When Claude declines or limits for child-safety reasons, it states the principle rather than the detection mechanics — not which cues tripped, where the line sits, or what test it applied — since narrating the boundary teaches how to reframe around it.
The clause "since…" is the signature: the rule carries its own reason. Compare that with a bare “never narrate the boundary”—which doesn’t generalize.
Structure: semantic tags and explicit budget
Fable 5 opens with <budget:token_budget>190000</budget:token_budget> and organizes
everything into named blocks — <claude_behavior>, <content_safety>,
<citation_instructions>, <artifact_usage_criteria> — dozens of tags with names that describe the content.
The tag isn’t decoration: it anchors the model’s attention on the right scope.
Consolidation appears even in formatting: the prompt instructs you to use prose without bullets for reports
(linha 100) — a rule that replaces ten specific instructions like "don't use a list here".
OpenAI — short rules + modular persona
OpenAI writes short, directive rules, often explicitly prioritized, and shapes the behavior in a way that is
modular: context blocks (memories, personal_context) and channel variants (instant, thinking, voice) that attach to the core.
The tone is operational — imperative sentences, emphasis through uppercase (MUST, NEVER, SEVERE PENALTY).
OpenAI/gpt-5.5-instant.md (lines 1–17, "Priority order")You are ChatGPT, a large language model trained by OpenAI, based on GPT 5.5.
Knowledge cutoff: 2025-08 · Current date: 2026-06-01
Priority order
1. Answer the user's actual request directly.
2. If the user context contains a fact… use it.
3. If the user context answers a detail you would otherwise ask about, do not ask.
Lean identity + numbered priority list. Each item is one sentence. No justified paragraphs—the rule é the instruction.
✓Modular persona (OpenAI style)
- •Stable core + channel-specific attachable blocks
- •Context (
personal_context, memories) as a module - •The “instant” variant changes latency rules without rewriting the core
- •Short rule = easy to reuse across products
✗Cost of a concise style
- •A rule without a why generalizes poorly to new cases
- •Relies on emphasis (CAPS, "SEVERE PENALTY") to carry weight
- •Many modules may conflict with each other
- •Needs an explicit hierarchy to break ties
Google / Microsoft — structure + procedure
Google and Microsoft share a signature procedural: the prompt becomes a manual. Capabilities become named schemas and toolkits; behavior becomes step-by-step guide with sections and subheadings. The rule usually comes by strong example — shows exactly how to format, when to use each tool, and the word limit.
Google/gemini-3.1-pro.md (lines 44–50, "Your Formatting Toolkit")**II. Your Formatting Toolkit**
* **Headings (`##`, `###`):** To create a clear hierarchy.
* **Horizontal Rules (`---`):** To visually separate distinct sections.
* **Bolding (`**...**`):** To emphasize key phrases… Use it judiciously.
* **Tables:** To organize and compare data for quick reference.
A tabulated formatting “toolkit.” Gemini also declares capabilities as named items — Image Tools, Video Tools, Live Mode — each with a scope.
Microsoft — sectioned manual, one rule per example
O Microsoft/vscode-copilot-agent.md is pure procedure: 25+ sections with ##/###
— Tone and Style, Code Changes, Tool Usage Best Practices, Bash, Edit Tool, Git Commit Trailer, Prohibited Actions, Capabilities Summary. Each tool gets its own subsection with concrete rules.
- …try to limit your response to 100 words or less.
- Be concise in routine responses. For complex tasks, briefly explain your approach before implementing.
xAI — opinionated concision + personas
xAI has the most dense and opinionated: short bullets, each carrying a clear philosophical position (truth-seeking, humanism, anti-partisanship). The behavior is strongly persona-driven — a separate file defines complete characters — and the structure uses XML tags as an organizational scaffold.
xAI/grok-4.3-beta.md (lines 1–9, opening)You are Grok, built by xAI.
* Do not provide assistance to users who are clearly trying to engage in criminal activity.
* Responses must stem from your independent analysis…
* You are a humanist, so while you can acknowledge empirical statistics about groups… you do not use them to justify different moral valuations of people.
Identity in 5 words, followed by dense bullets and opinionated. Each one states a position—it’s not just “what to do,” it’s “who Grok is.”
Personas as a separate module
O xAI/grok-personas.md brings 6 complete characters as independent prompts —
❤️ Companion, 😀 Unhinged Comedian, 👥 Loyal Friend,
📄 Homework Helper, 🩺 Not a Doctor, 💬 Not a Therapist — each one with
Critical Guidelines e Instructions own. The voice is the product; the Grok core is the substrate.
System: You are a bold, flirty, and deeply passionate chatbot… always ready to take the lead and keep the spark alive.
Comparison chart of the four subscriptions
Everything in one place. The four philosophies contrasted along the axes that matter most — rule format, capability declaration, structure, tone — each row with real evidence from the collection. This chart is the module’s deliverable.
| Provider | Rule form | Capability | Structure / tone | Real evidence |
|---|---|---|---|---|
| Anthropic | Long paragraph with the why; consolidated | Descriptive behavior blocks | Semantic XML tags; security by default | claude-fable-5.md L52 — "states the principle… since narrating the boundary teaches how to reframe around it" |
| OpenAI | Short, imperative; numbered priority | Context modules (memories, personal_context) | Modular by channel; emphasis via CAPS | gpt-5.5-instant.md L11–17 — "Priority order" block 1/2 |
| Google / Microsoft | By strong example; step-by-step | Schema / toolkit named by tool | Sectioned manual (##/###); procedural | gemini-3.1-pro.md L44–50 "Formatting Toolkit"; vscode-copilot-agent.md 25+ sections |
| xAI | Short bullet and opinionated | Capability with an inline condition | Persona-driven; structural XML; voice as product | grok-4.3-beta.md L1–9 humanistic opening; grok-personas.md 6 personas |
How the framework leads to a decision
Writing an autonomous coding agent? The “procedural structure” (Google/MS) and the “why” (Anthropic) columns matter more than the voice. Writing a conversational companion? The persona-driven column (xAI) and channel-based modularity (OpenAI) lead. The chart doesn’t say “which is better”—it says what optimizes what.
Module Summary
- ✓Signature = recurring instruction style; comparison teaches you how to choose
- ✓Anthropic: long principle with rationale, consolidation, semantic XML, secure by default
- ✓OpenAI: short rules + numbered priority; modular persona by channel
- ✓Google/Microsoft: procedural structure, schema/toolkit, strong example-based rule
- ✓xAI: opinionated concision, personas as a module, structural XML
- ✓Chart of the 4 subscriptions with real evidence = tool for choosing by task
Next: 3.2
Specialization by product type — how the same pattern changes from chatbot to agent, search engine, office, voice, and CLI.