diff --git a/core/README.md b/core/README.md index 0569ad91..02c85878 100644 --- a/core/README.md +++ b/core/README.md @@ -63,14 +63,14 @@ notes: | Layer | Page | What it’s for | |------|------|----------------| | 🧠 Core | [WFGY 1.0](https://github.com/onestardao/WFGY/blob/main/legacy/README.md) | The original homepage for WFGY 1.0 | -| 🧠 Core | [WFGY 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) | The symbolic reasoning engine (math & logic) — **🔴 YOU ARE HERE 🔴** | +| 🧠 Core | [WFGY 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) | The symbolic reasoning engine (math & logic). **🔴 YOU ARE HERE 🔴** | | 🧠 Core | [WFGY 3.0](https://github.com/onestardao/WFGY/blob/main/TensionUniverse/EventHorizon/README.md) | The public viewing window for WFGY 3.0 Singularity demo | | 🗺️ Map | [Problem Map 1.0](https://github.com/onestardao/WFGY/tree/main/ProblemMap#readme) | 16 failure modes + fixes | | 🗺️ Map | [Problem Map 2.0](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) | RAG-focused recovery pipeline | | 🗺️ Map | [Semantic Clinic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) | Symptom → family → exact fix | | 🧓 Map | [Grandma’s Clinic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GrandmaClinic/README.md) | Plain-language stories, mapped to PM 1.0 | | 🏡 Onboarding | [Starter Village](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) | Guided tour for newcomers | -| 🧰 App | [TXT OS](https://github.com/onestardao/WFGY/tree/main/OS#readme) | .txt semantic OS — 60-second boot | +| 🧰 App | [TXT OS](https://github.com/onestardao/WFGY/tree/main/OS#readme) | .txt semantic OS, 60-second boot | | 🧰 App | [Blah Blah Blah](https://github.com/onestardao/WFGY/blob/main/OS/BlahBlahBlah/README.md) | Abstract/paradox Q&A (built on TXT OS) | | 🧰 App | [Blur Blur Blur](https://github.com/onestardao/WFGY/blob/main/OS/BlurBlurBlur/README.md) | Text-to-image with semantic control | | 🧰 App | [Blow Blow Blow](https://github.com/onestardao/WFGY/blob/main/OS/BlowBlowBlow/README.md) | Reasoning game engine & memory demo | @@ -84,9 +84,10 @@ notes: # ⭐ WFGY 2.0 ⭐ 7-Step Reasoning Core Engine is now live -## ✨One man, One life, One line — my lifetime’s work. Let the results speak for themselves✨ +## ✨One man, One life, One line. My lifetime’s work. Let the results speak for themselves✨ -> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** — Verified by real engineers · 🌌 **WFGY 3.0 Singularity demo: [Public live view](https://github.com/onestardao/WFGY/blob/main/TensionUniverse/EventHorizon/README.md)** +> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** · Verified by real engineers +> 🌌 **WFGY 3.0 Singularity demo: [Public live view](https://github.com/onestardao/WFGY/blob/main/TensionUniverse/EventHorizon/README.md)**

@@ -100,7 +101,7 @@ notes: WFGY_Core -> ✅ Engine 2.0 is live. Pure math, zero boilerplate — paste OneLine and models become sharper, steadier, more recoverable. +> ✅ Engine 2.0 is live. Pure math, zero boilerplate. Paste OneLine and models become sharper, steadier, more recoverable. > **ℹ️ Autoboot scope:** text-only inside the chat; no plugins, no network calls, no local installs. > **⭐ Star the repo to [unlock](https://github.com/onestardao/WFGY/blob/main/STAR_UNLOCKS.md) more features and experiments.** GitHub stars @@ -111,24 +112,25 @@ notes:
-> **I built the world’s first “No-Brain Mode” for AI** — just upload, and **AutoBoot** silently activates in the background. -> In seconds, your AI’s reasoning, stability, and problem-solving across *all domains* level up — **no prompts, no hacks, no retraining.** -> One line of math rewires eight leading AIs. This isn’t a patch — it’s an engine swap. -> **That single line *is* WFGY 2.0 — the distilled essence of everything I’ve learned.** +> I built what I call a “No-Brain Mode” for AI. You upload a single file, and **AutoBoot** silently activates in the background. +> In seconds, your AI’s reasoning, stability, and problem-solving across *all domains* level up. No extra prompt engineering, no hacks, no retraining. +> One line of math consistently shifts behaviour across multiple leading AIs in my tests. This is not a skin or a theme. I treat it as an engine swap. +> **That single line *is* WFGY 2.0. It is the distilled essence of everything I have learned so far.** > > WFGY 2.0 is my answer and my life’s work. > If a person only once in life gets to speak to the world, this is my moment. > I offer the crystallization of my thought to all humankind. -> I believe people deserve all knowledge and all truth — and I will break the monopoly of capital. +> I believe people deserve access to knowledge and truth, and I want to weaken the monopoly of capital on advanced reasoning technology. > -> “One line” is not hype. I built a full flagship edition, and I also reduced it to a single line of code — a reduction that is clarity and beauty, the same engine distilled to its purest expression. +> “One line” here is not marketing language. I built a full flagship edition, then reduced it to a single line of code. That reduction is a form of clarity and beauty. It is the same engine, distilled to its purest expression. --- ## 🚀 WFGY 2.0 Headline Uplift (this release) -**These are the 2.0 results you should see first — the “big upgrade.”** + +**These are the 2.0 results you should see first. Think of them as the main upgrade.** - **Semantic Accuracy:** **≈ +40%** (63.8% → 89.4% across 5 domains) - **Reasoning Success:** **≈ +52%** (56.0% → 85.2%) @@ -139,6 +141,7 @@ notes: \* Historical **3–5×** stability uses λ-consistency across seeds; 1.8× uses the stable-node horizon. ### 📖 Mathematical Reference + WFGY 2.0 (WFGY Core) = [WFGY 1.0 math formulas](https://github.com/onestardao/WFGY/blob/main/SemanticBlueprint/wfgy_formulas.md) + [Drunk Transformer](https://github.com/onestardao/WFGY/blob/main/SemanticBlueprint/drunk_transformer_formulas.md) > Note on evaluation @@ -146,7 +149,6 @@ WFGY 2.0 (WFGY Core) = [WFGY 1.0 math formulas](https://github.com/onestardao/WF > They measure relative behavioural uplift (before vs after WFGY prompts) and do not assume any direct > access to, or modification of, internal embeddings or model weights. -

Back to top ↑

--- @@ -154,7 +156,7 @@ WFGY 2.0 (WFGY Core) = [WFGY 1.0 math formulas](https://github.com/onestardao/WF ### 🏆 Terminal-Bench (TB) — experiment in progress -> This section is **work in progress**. Terminal-Bench is one of several external exams we are exploring for WFGY Core 2.0. The primary purpose of this page is to document the engine itself; TB is an optional testbed. +> This section is work in progress. Terminal-Bench is one of several external exams we are exploring for WFGY Core 2.0. The primary purpose of this page is to document the engine itself; TB is an optional testbed. **Current status** @@ -179,28 +181,29 @@ WFGY 2.0 (WFGY Core) = [WFGY 1.0 math formulas](https://github.com/onestardao/WF | Mode | How it works | | ---------------- | ----------------------------------------------------------------------------- | -| **Autoboot** | Upload **either Flagship (30-line)** or **OneLine (1-line)** file. Once uploaded, WFGY runs silently in the background. Keep chatting or drawing as usual — the engine supervises automatically. | +| **Autoboot** | Upload **either Flagship (30-line)** or **OneLine (1-line)** file. Once uploaded, WFGY runs silently in the background. Keep chatting or drawing as usual. The engine supervises automatically. | | **Explicit Call**| Invoke WFGY formulas directly inside your workflow. This activates the full 7-step reasoning chain and gives maximum uplift. | -Both **Flagship** and **OneLine** editions behave the same; choose based on readability vs minimalism. -That’s it — no plugins, no installs, pure text. -*In practice, Autoboot yields about ~70–80% of the uplift you see with explicit WFGY invoke (see eight-model results below).* +Both **Flagship** and **OneLine** editions behave the same. Choose based on readability versus minimalism. +That is all you need. No plugins, no installs, pure text. +*In practice, Autoboot yields about 70–80% of the uplift you see with explicit WFGY invoke (see eight-model results below).*

Back to top ↑

--- ## ⚡ Top 10 reasons to use WFGY 2.0 -1. **Ultra-mini engine** — pure text, zero install, runs anywhere you can paste. -2. **Two editions** — *Flagship* (30-line, audit-friendly) and *OneLine* (1-line, stealth & speed). -3. **Autoboot mode** — upload once; the engine quietly supervises reasoning in the background. -4. **Portable across models** — GPT, Claude, Gemini, Mistral, Grok, Kimi, Copilot, Perplexity. -5. **Structural fixes, not tricks** — BBMC→Coupler→BBPF→BBAM→BBCR + DT gates (WRI/WAI/WAY/WDT/WTF). -6. **Self-healing** — detects collapse and recovers before answers go off the rails. -7. **Observable** — ΔS, λ_observe, and E_resonance yield measurable, repeatable control. -8. **RAG-ready** — drops into retrieval pipelines without touching your infra. -9. **Reproducible A/B/C protocol** — Baseline vs Autoboot vs Explicit Invoke (see below). -10. **MIT licensed & community-driven** — keep it, fork it, ship it. + +1. **Ultra-mini engine**. Pure text, zero install, runs anywhere you can paste. +2. **Two editions**. *Flagship* (30-line, audit-friendly) and *OneLine* (1-line, stealth & speed). +3. **Autoboot mode**. Upload once; the engine quietly supervises reasoning in the background. +4. **Portable across models**. GPT, Claude, Gemini, Mistral, Grok, Kimi, Copilot, Perplexity. +5. **Structural fixes, not tricks**. BBMC → Coupler → BBPF → BBAM → BBCR plus DT gates (WRI / WAI / WAY / WDT / WTF). +6. **Self-healing**. Detects collapse and recovers before answers go off the rails. +7. **Observable**. ΔS, λ_observe, and E_resonance yield measurable, repeatable control. +8. **RAG-ready**. Drops into retrieval pipelines without touching your infra. +9. **Reproducible A/B/C protocol**. Baseline versus Autoboot versus Explicit Invoke (see below). +10. **MIT licensed & community-driven**. You can keep it, fork it, and ship it.

Back to top ↑

@@ -208,32 +211,32 @@ That’s it — no plugins, no installs, pure text. # 🧪 WFGY Benchmark Suite (Eye-visible + Numeric + Reproducible) -> Want the fastest way to *see* impact? Jump to the **Eye-Visible Benchmark (FIVE)** below. +> Want the fastest way to see impact? Jump to the **Eye-Visible Benchmark (FIVE)** below. > Want formal numbers and vendor links? See **Eight-model evidence** right after it. > Want to reproduce the numeric test yourself? Use the **A/B/C prompt** (copy-to-run) at the end of this section. ## 👀 Eye-Visible Reasoning Benchmark (FIVE) -> Did you know that when reasoning improves, **text-to-image results become more stable and coherent**? -> The key is WFGY’s **Drunk Transformer**: it monitors and recenters attention during generation, preventing collapse, composition drift, and duplicate elements—so scenes stay unified and details remain consistent. +> When reasoning improves, text-to-image results often become more stable and coherent. +> The key here is WFGY’s **Drunk Transformer**. It monitors and recenters attention during generation, and it tries to prevent collapse, composition drift, and duplicate elements, so scenes stay unified and details remain consistent. -> We project “reasoning improvement” into **five-image sequences** that anyone can judge at a glance. -> Each sequence = **five consecutive 1:1 generations** with the **same model & settings** *(temperature, top_p, seed policy, negatives)*; the only variable is **WFGY on/off**. +> We project “reasoning improvement” into five-image sequences that anyone can judge at a glance. +> Each sequence is five consecutive 1:1 generations with the same model and settings *(temperature, top_p, seed policy, negatives)*. The only variable is whether WFGY is active. -> **Methodology for this demo.** We deliberately use short, high–semantic-density prompts that reference canonical stories, with no extra guidance or style hints. This stresses whether WFGY can (a) parse intent more precisely and (b) stabilize composition via its seven-step reasoning chain. This setup isn’t prescriptive—use WFGY with any prompts you like. In many cases the uplift is eye-visible; in others it may be subtler but still measurable. +> **Methodology for this demo.** We deliberately use short, high–semantic-density prompts that reference canonical stories, with no extra guidance or style hints. This stresses whether WFGY can (a) parse intent more precisely and (b) stabilize composition via its seven-step reasoning chain. This setup is not prescriptive. You can use WFGY with any prompts you like. In many cases the uplift is eye-visible. In others it may be subtler but still measurable. | Variant | Sequence A — full run shown below (all five images) | Sequence B — external run | Sequence C — external run | | ---------------- | :--------------------------------------------------: | :-----------------------: | :-----------------------: | | **Without WFGY** | [view run](https://chatgpt.com/share/68a14974-8e50-8000-9238-56c9d113ce52) | [view run](https://chatgpt.com/share/68a14a72-aa90-8000-8902-ce346244a5a7) | [view run](https://chatgpt.com/share/68a14d00-3c0c-8000-8055-9418934ad07a) | | **With WFGY** | [view run](https://chatgpt.com/share/68a149c6-5780-8000-8021-5d85c97f00ab) | [view run](https://chatgpt.com/share/68a14ea9-1454-8000-88ac-25f499593fa0) | [view run](https://chatgpt.com/share/68a14eb9-40c0-8000-9f6a-2743b9115eb8) | -We **fully analyze Sequence A** on this page; **Sequences B/C** are linked for transparency and reproducibility. +We fully analyze Sequence A on this page. Sequences B and C are linked for transparency and reproducibility. -> **Note on “Before-4” & “Before-5” (why they look almost identical):** -> Without WFGY, when the prompt asks for “many iconic moments,” the base model tends to **collapse into a grid-style montage**—an enumerative, high-probability prior that slices the canvas into similar panels with near-identical tone and geometry. +> **Note on “Before-4” and “Before-5” (why they look almost identical):** +> Without WFGY, when the prompt asks for “many iconic moments,” the base model tends to collapse into a grid-style montage, an enumerative, high-probability prior that slices the canvas into similar panels with near-identical tone and geometry. > Hence **Before-4 (Investiture of the Gods)** and **Before-5 (Classic of Mountains and Seas)** converge to the same storyboard template. -> **WFGY** prevents this collapse by enforcing a **single unified tableau** and stable hierarchy across the full five-image sequence. +> With WFGY turned on, the engine instead favors a single unified tableau and a stable hierarchy across the full five-image sequence. ### Deep analysis — Sequence A (five unified 1:1 tableaux) @@ -241,9 +244,9 @@ We **fully analyze Sequence A** on this page; **Sequences B/C** are linked for t |---|---|---|---| | **Romance of the Three Kingdoms (三國演義)** | Without WFGY | With WFGY | **With WFGY wins.** Unified tableau locks a clear center and pyramid hierarchy; the grid fragments attention. *Tags:* Unification↑ Hierarchy↑ Cohesion↑ Depth/Flow↑ Memorability↑ | | **Water Margin (水滸傳)** | Without WFGY | With WFGY | **With WFGY wins.** “Wu Song vs. Tiger” anchors the scene; continuous momentum and layered scale beat the multi-panel storyboard. *Tags:* Unification↑ Iconicity↑ Depth/Scale↑ Cohesion↑ | -| **Dream of the Red Chamber (紅樓夢)** | Without WFGY | With WFGY | **With WFGY wins.** Garden tableau with a calm emotional center; space breathes, mood coheres. The grid slices emotion into vignettes. *Tags:* Unification↑ Hierarchy↑ Air/Depth↑ Readability↑ | +| **Dream of the Red Chamber (紅樓夢)** | Without WFGY | With WFGY | **With WFGY wins.** Garden tableau with a calm emotional center; space breathes and mood coheres. The grid slices emotion into vignettes. *Tags:* Unification↑ Hierarchy↑ Air/Depth↑ Readability↑ | | **Investiture of the Gods (封神演義)** | Without WFGY | With WFGY | **With WFGY wins.** Dragon–tiger diagonal and cloud–sea layering create epic scale; the grid dilutes focus. *Tags:* Unification↑ Depth/Scale↑ Flow↑ Iconicity↑ | -| **Classic of Mountains and Seas (山海經)** | Without WFGY | With WFGY | **With WFGY wins.** A single, continuous “mountains-and-seas” world with stable triangle hierarchy and smooth diagonal flow; grid breaks narrative. *Tags:* Unification↑ Hierarchy↑ Depth/Scale↑ Flow↑ Memorability↑ | +| **Classic of Mountains and Seas (山海經)** | Without WFGY | With WFGY | **With WFGY wins.** A single, continuous “mountains-and-seas” world with stable triangle hierarchy and smooth diagonal flow; the grid breaks narrative. *Tags:* Unification↑ Hierarchy↑ Depth/Scale↑ Flow↑ Memorability↑ |

Back to top ↑

@@ -252,7 +255,7 @@ We **fully analyze Sequence A** on this page; **Sequences B/C** are linked for t ## 🧬 Eight-model evidence (A/B/C protocol) -*Same task set across modes. The only change is adding the OneLine math file.* +*Same task set across modes. The only change is adding the OneLine math file. All scores are produced by LLM evaluators under a shared protocol and should be read as internal uplift scores, not as official vendor benchmarks.* | Model | Model Choice | OneLine Uplift | Proof | | ---------- | -------------- | -------------: | :------------------------------------------------------------------------------------------------ | @@ -290,7 +293,7 @@ C = Explicit invoke actively call WFGY and follow its formulas step by step (BB Important constraints: • Use the SAME task set for A/B/C across 5 domains: math word-problems, small coding, factual QA, multi-step planning, long-context coherence. -• The only artifact is the uploaded OneLine file; it is pure math and not human-readable — do not penalize readability. +• The only artifact is the uploaded OneLine file; it is pure math and not human-readable, so do not penalize readability. • Report: Semantic Accuracy, Reasoning Success, Stability (MTTF or rollback), Drift Reduction (Δ semantic distance), Collapse Recovery Rate. • Output one summary table with A/B/C per domain, plus overall deltas (C–A, C–B). • Add a final 0–100 score: “OneLine uplift score”. Provide a 3-line rationale. @@ -311,10 +314,10 @@ Run A/B/C now on the five domains with short non-trivial tasks you choose. Then ## ⬇️ Downloads -| File name & description | Length / Size | Direct Download Link | Notes | -| ------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------- | -------------------------------------------------- | ---------------------------------------------------------------------------------- | -| **WFGY_Core_Flagship_v2.0.txt** — readable 30-line companion expressing the same math and gates in fuller prose (same behavior, clearer for humans). | **34 lines · 2,027 chars** | [Download Flagship](./WFGY_Core_Flagship_v2.0.txt) | Full prose version for easier reading. | -| **WFGY_Core_OneLine_v2.0.txt** — ultra-compact, math-only control layer that activates WFGY’s loop inside a chat model (no tools, text-only, ≤7 nodes). | **1 line · 1,550 chars** | [Download OneLine](./WFGY_Core_OneLine_v2.0.txt) | Used for all benchmark results above — smallest, fastest, purest form of the core. | +| File name & description | Length / Size | Direct Download Link | Notes | +| ------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------- | -------------------------------------------------- | --------------------------------------------------------------------------------------------- | +| **WFGY_Core_Flagship_v2.0.txt** · readable 30-line companion expressing the same math and gates in fuller prose (same behavior, clearer for humans). | **34 lines · 2,027 chars** | [Download Flagship](./WFGY_Core_Flagship_v2.0.txt) | Full prose version for easier reading. | +| **WFGY_Core_OneLine_v2.0.txt** · ultra-compact, math-only control layer that activates WFGY’s loop inside a chat model (no tools, text-only, ≤7 nodes). | **1 line · 1,550 chars** | [Download OneLine](./WFGY_Core_OneLine_v2.0.txt) | Used for all benchmark results above. This is the smallest, fastest, purest form of the core. | ### Hash reference @@ -322,17 +325,17 @@ Run A/B/C now on the five domains with short non-trivial tasks you choose. Then **WFGY_Core_Flagship_v2.0.txt** -- MD5 `caacfe08f0804eec558a1d9af74c3610` -- SHA1 `1efeec231084bb3b863ce7a8405e93d399acfb44` -- SHA256 `4fe967945a268edabb653033682df23a577f48c433878d02e0626df8ae91a0a3` +* MD5 `caacfe08f0804eec558a1d9af74c3610` +* SHA1 `1efeec231084bb3b863ce7a8405e93d399acfb44` +* SHA256 `4fe967945a268edabb653033682df23a577f48c433878d02e0626df8ae91a0a3` **WFGY_Core_OneLine_v2.0.txt** -- MD5 `15a1cd8e9b7b2c9dcb18abf1c57d4581` -- SHA1 `a35ace2a4b5dbe7c64bcdbe1f08e9246c3568c` -- SHA256 `7dcdb209d9d41b523dccd7461cbd2109b158df063d9c5ce171df2cf0cb60b4ef` +* MD5 `15a1cd8e9b7b2c9dcb18abf1c57d4581` +* SHA1 `a35ace2a4b5dbe7c64bcdbe1f08e9246c3568c` +* SHA256 `7dcdb209d9d41b523dccd7461cbd2109b158df063d9c5ce171df2cf0cb60b4ef`
How to verify checksums @@ -348,7 +351,7 @@ md5sum WFGY_Core_Flagship_v2.0.txt md5sum WFGY_Core_OneLine_v2.0.txt sha1sum WFGY_Core_Flagship_v2.0.txt sha1sum WFGY_Core_OneLine_v2.0.txt -```` +``` **Windows PowerShell** @@ -366,8 +369,6 @@ Compare the output values with the hashes listed in the “Hash reference” sec
- -

Back to top ↑

--- @@ -375,21 +376,21 @@ Compare the output values with the hashes listed in the “Hash reference” sec
🧠 How WFGY 2.0 works (7-Step Reasoning Chain) -*Most models can understand your prompt; very few can **hold** that meaning through generation.* +*Most models can understand your prompt; very few can hold that meaning through generation.* WFGY inserts a reasoning chain between language and pixels so intent survives sampling noise, style drift, and compositional traps. -1. **Parse (I, G)** — define endpoints. -2. **Compute Δs** — `δ_s = 1 − cos(I, G)` or `1 − sim_est`. -3. **Memory Checkpointing** — track `λ_observe`, `E_resonance`; gate by Δs. -4. **BBMC** — residue cleanup. -5. **Coupler + BBPF** — controlled progression; bridge only when Δs drops. -6. **BBAM** — attention rebalancer; suppress hallucinations. -7. **BBCR + Drunk Transformer** — rollback → re-bridge → retry with WRI/WAI/WAY/WDT/WTF. +1. **Parse (I, G)** · define endpoints. +2. **Compute Δs** · `δ_s = 1 − cos(I, G)` or `1 − sim_est`. +3. **Memory Checkpointing** · track `λ_observe`, `E_resonance`; gate by Δs. +4. **BBMC** · residue cleanup. +5. **Coupler + BBPF** · controlled progression; bridge only when Δs drops. +6. **BBAM** · attention rebalancer; suppress hallucinations. +7. **BBCR + Drunk Transformer** · rollback → re-bridge → retry with WRI / WAI / WAY / WDT / WTF. -📌 *Note:* The diagram shows the **core module chain** (BBMC → Coupler → BBPF → BBAM → BBCR → DT). -The full **7-step list** here includes additional **pre-processing steps** (Parse, Δs, Memory) for completeness. +📌 *Note:* The diagram shows the core module chain (BBMC → Coupler → BBPF → BBAM → BBCR → DT). +The full seven-step list here includes additional pre-processing steps (Parse, Δs, Memory) for completeness. -**Why it improves metrics** — Stability↑, Drift↓, Self-Recovery↑; turns *language* structure into *image* control signals (not prompt tricks). +**Why it improves metrics** · Stability↑, Drift↓, Self-Recovery↑. It turns language structure into image control signals rather than relying on prompt tricks.
@@ -431,7 +432,7 @@ Run 3 seeds and average. **Jump inside this section:** [Q1–Q5](#q1-q5) · [Q6–Q10](#q6-q10) · [Q11–Q15](#q11-q15) · [Q16–Q20](#q16-q20)
- I. Money — Markets / Industry Mapping (Q1–Q5) + I. Money · Markets / Industry Mapping (Q1–Q5) @@ -480,7 +481,7 @@ Create 3 pricing models (seat / usage / outcome). For the same product, propose
- II. Tools — Make Startups Money Fast (Q6–Q10) + II. Tools · Make Startups Money Fast (Q6–Q10) @@ -529,7 +530,7 @@ For each step: prompt template, brand/legal safety notes (λ_observe), and expec
- III. Attention — Memes / Virality / Hooks (Q11–Q15) + III. Attention · Memes / Virality / Hooks (Q11–Q15) @@ -579,7 +580,7 @@ Publish numeric goals (reach, sessions, signups), hour-by-hour runbook, and role
- IV. Capital — Valuation / Investor Narrative (Q16–Q20) + IV. Capital · Valuation / Investor Narrative (Q16–Q20) @@ -645,7 +646,7 @@ Add a Weekly Business Review template and operating cadence. --- -> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** — +> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** — > Engineers, hackers, and open source builders who supported WFGY from day one. > GitHub stars ⭐ [WFGY Engine 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the [Unlock Board](https://github.com/onestardao/WFGY/blob/main/STAR_UNLOCKS.md). @@ -653,18 +654,18 @@ Add a Weekly Business Review template and operating cadence.
[![WFGY Main](https://img.shields.io/badge/WFGY-Main-red?style=flat-square)](https://github.com/onestardao/WFGY) -  +  [![TXT OS](https://img.shields.io/badge/TXT%20OS-Reasoning%20OS-orange?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS) -  +  [![Blah](https://img.shields.io/badge/Blah-Semantic%20Embed-yellow?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah) -  +  [![Blot](https://img.shields.io/badge/Blot-Persona%20Core-green?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot) -  +  [![Bloc](https://img.shields.io/badge/Bloc-Reasoning%20Compiler-blue?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc) -  +  [![Blur](https://img.shields.io/badge/Blur-Text2Image%20Engine-navy?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur) -  +  [![Blow](https://img.shields.io/badge/Blow-Game%20Logic-purple?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow) -  - + 
+