How it works

Type human. Get genius.

Safyan sits between you and AI. You speak naturally. AI gets perfection. Three steps, two seconds, zero learning curve.

You type anything

Messy, vague, any language. Type the way you think. No formatting required.

input

Safyan translates

Diagnoses 7 mistakes. Applies mathematical cures. Restructures for your platform.

translate

AI gives its best

Optimized for ChatGPT, Claude, Gemini, or any platform the AI needs.

output

3 steps -- 2 seconds -- zero learning curve

Before & After

You typedhey make a cool website for my bakery with nice colors

Safyan translatedYou are a senior web developer. Build a responsive bakery website with warm earth tones (#8B6914, #F5E6C8), hero section with artisan bread photography, product grid with hover effects, online ordering CTA, and mobile-first layout. Semantic HTML5, modern CSS.

Words10 → 42

Specificity+320%

Without SafyanVague output

You typedje veux un logo moderne pour ma startup tech

Safyan translatedDesign a modern, minimalist logo for a technology startup. Style: geometric, clean lines, single accent color. Output: SVG-ready vector with 3 variations — icon-only, wordmark, combination mark. Include hex color palette and typography recommendation.

Words9 → 36

Specificity+300%

Without SafyanLost in translation

You typedfix my async code it keeps crashing idk why

Safyan translatedDebug an async/await issue causing crashes. Analyze for: unhandled promise rejections, missing try/catch, race conditions, improper error propagation. Provide corrected code with inline comments explaining each fix, plus a checklist of async pitfalls.

Words9 → 35

Specificity+289%

Without SafyanGeneric fix

↑ Safyan users get 3.2x more precise AI responses on average

The problem

The 7 Mistakes

Every human makes these mistakes when talking to AI. Safyan detects and cures all 7 — automatically, before your prompt reaches the model.

Every "hey," "could you maybe," and "please" injects uncertainty tokens. The AI hedges its response because you hedged your ask.

Human says "Hey could you maybe possibly help me write something?"

Safyan sends "Write a [specific deliverable] with [constraints]."

Cure: COMPRESS LOCK

"Make it look nice" is not a color, not a font, not a layout. The AI averages across ALL its concepts of "nice" — you get the mean, not the magic.

Human says "Make my website look nice and professional"

Safyan sends "Apply Inter font, 4px border-radius, #1a1a2e palette, 8px grid spacing."

Cure: LOCK GROUND

"Do whatever you think is best" = infinite options. The AI picks the safest, most generic, most forgettable answer. Constraints are information.

Human says "Write me a marketing email, do whatever you think"

Safyan sends "Write a 150-word email. Tone: urgent but warm. CTA: Book a demo. No jargon."

Cure: BOUND SHAPE

AI contains every expert and every novice. Without a role, it averages across all of them. You get a Wikipedia summary instead of a specialist's insight.

Human says "How do I save money on taxes?"

Safyan sends "As a senior tax attorney: list deductions for a $150K W-2 earner, filing single."

Cure: PRIME

One example is worth a hundred instructions. Without a reference, the AI guesses what quality looks like — and it guesses conservatively.

Human says "Write me a bio for my LinkedIn"

Safyan sends "Write a bio like: 'Built X from 0 to $5M ARR. Now doing Y.' — punchy, metric-driven."

Cure: CALIBRATE

"Compare X, also explain Y, and what about Z?" — attention splits across all of them. Quality drops on each sub-answer. Less is more.

Human says "Compare React and Vue and also explain SSR and what about Svelte?"

Safyan sends "Step 1: Compare React vs Vue on [criteria]. Step 2: Explain SSR trade-offs."

Cure: SPLIT SEQUENCE

Never told AI what NOT to do? It covers everything — including filler, disclaimers, and things you explicitly don't want. Tell it what to avoid.

Human says "Explain machine learning to me"

Safyan sends "Explain ML. No analogies. No 'simply put.' No history. Jump to how it works."

Cure: NEGATE

↓ Safyan detects and cures these mistakes before your prompt reaches the AI

The language

16 Primitives. 7 Modifiers.

Each primitive is a mathematical operation on the AI's output distribution. Click any primitive to see how it works.

Activates expert knowledge clusters in the model. Instead of averaging across all knowledge, PRIME focuses the AI on a specific domain — "senior tax attorney" not "helpful assistant."

PRIME("senior React architect")

Collapses ambiguity to one precise interpretation. When you say "nice," LOCK picks the one meaning that fits your context — no hedging, no "it depends."

LOCK("reduce effective tax rate")

Hard boundaries on the solution space. Constraints are information — the more you constrain, the more specific and useful the output becomes.

BOUND(language: JS, max: 50 lines, no dependencies)

Defines the output topology and structure. Instead of letting AI decide format, SHAPE tells it exactly how to organize the response — numbered steps, table, bullet points.

SHAPE(table: feature | pro | con)

Anchors claims to concrete evidence. Forces the AI to cite sources, use real numbers, and avoid speculation. Every claim gets backed by something verifiable.

GROUND(cite IRS publications, dollar amounts)

Zeros out known-bad output regions. Tells AI what NOT to include — no filler, no disclaimers, no restating the question. Elimination is as powerful as instruction.

NEGATE(no analogies, no "simply put")

Self-consistency audit. Forces the AI to check its own work before presenting it — verify each claim applies to the user's situation, catch contradictions.

VERIFY(each deduction applies to filing status)

Metacognitive step: what do they NEED vs what they SAID. "Help with taxes" means "maximize take-home pay legally." REFLECT reads the real intent.

REFLECT(said: "help with taxes" = need: maximize savings)

Causal step ordering. When the answer has dependencies — step A must happen before step B — SEQUENCE ensures the AI presents them in executable order.

SEQUENCE(identify → calculate → rank → plan)

Sets the quality bar via example. One reference output tells the AI more than a page of instructions. CALIBRATE gives a Bayesian prior on what "good" looks like.

CALIBRATE("HSA — save $1,200/yr — open by April 15")

Maximum signal per token. Strips all filler, hedging, and noise. Every sentence carries a fact, decision, or instruction. Zero wasted tokens.

COMPRESS(pure signal, no pleasantries)

Decomposes compound problems into focused sub-tasks. Each gets full attention instead of splitting it across many. Quality per task goes up.

SPLIT("optimize taxes" → income, deductions, credits)

Explores beyond the obvious. Pushes the AI past safe, conventional answers into novel territory — unconventional approaches, edge cases, creative solutions.

DIVERGE(beyond standard deductions: QBI, cost segregation)

Synthesizes multiple perspectives into one coherent view. Merges aggressive and conservative, theory and practice, pros and cons — into a balanced recommendation.

FUSE(aggressive + conservative = balanced plan)

Stress-tests before recommending. Forces the AI to attack its own answer — what could go wrong? What's the strongest counterargument? Only surviving ideas get through.

OPPOSE(what triggers an audit? what fails?)

Structure first, content second. Build the skeleton, then fill each section. Prevents the AI from going on tangents — every piece slots into the framework.

SCAFFOLD(outline → fill each section)

Modifiers

Temperature knobs — adjust the precision, depth, and style of any primitive.

::sharp

Temperature → 0. Maximum precision. No exploration, no hedging. The single best answer.

::open

Temperature → 1. Maximum exploration. Brainstorm, diverge, surprise me.

::dense

Minimize tokens per unit of information. Every word earns its place or gets cut.

::wide

Maximize coverage. Hit every edge case, every scenario, every possibility.

::now

Optimize for immediate action. Zero theory, zero background. What do I do right now?

::deep

Maximize reasoning depth. Show your work. Think step by step. No shortcuts.

::counter

Invert assumptions. Play devil's advocate. What if the opposite is true?

Translation modes

7 Modes

Each mode is a pre-tuned combination of cures and primitives, optimized for a specific type of task.

Fast, minimal optimization. Locks intent and adds constraints in under a second. For when speed matters more than depth.

LOCK BOUND SHAPE

The default. Cures the first 4 mistakes automatically — strips noise, locks intent, adds constraints, assigns expert role.

PRIME LOCK BOUND SHAPE

Maximum cure coverage. All 7 mistakes detected and addressed. Auto-selects up to 7 primitives based on the specific prompt.

All auto-detected max 7 primitives

Precision-optimized for programming tasks. Adds anti-patterns, specifies language constraints, and structures for executable output.

PRIME LOCK BOUND SHAPE NEGATE

High-temperature exploration. Diverges beyond the obvious while still locking to your core intent. For writing, brainstorming, and ideation.

PRIME LOCK SHAPE DIVERGE

Evidence-anchored and comprehensive. Grounds all claims, fuses multiple perspectives, and covers every angle of a topic.

LOCK BOUND GROUND FUSE SHAPE

Action-oriented with self-verification. Strips theory, adds expert context, verifies claims, and outputs deliverables you can use immediately.

PRIME LOCK BOUND SHAPE VERIFY