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DavidVaness/README.md

Hi, I'm David

I am an AI product and technology leader at Accenture Song, building privacy-conscious AI products and platforms at the intersection of enterprise strategy and hands-on engineering. I lead product and technology for an internal AI venture, serve as the platform's global representative, and remain hands-on in architecture and critical engineering decisions.

My background spans 16+ years across software engineering, entrepreneurship, consulting, and multidisciplinary product leadership. I specialise in turning emerging AI capabilities into production platforms, scalable delivery models, and useful customer experiences.

I also build local-first AI tools for sensitive, messy human information. They make capable models practical without making cloud upload the default.

Selected work

whospoke

Local, offline transcription and speaker identification for Apple Silicon. It combines multilingual speech recognition, speaker diarization, voice embeddings, and cross-file identity matching without uploading recordings to a hosted transcription service.

What it demonstrates: a resilient multi-model pipeline, local AI acceleration, privacy-aware product design, and usable outputs for real research, meetings, and media workflows.

Image Autonamer

Local AI image naming for macOS Downloads folders. It uses a vision-language model through Ollama to produce useful filenames while keeping image data on the device.

What it demonstrates: safe automation around an untrusted model, durable local state, macOS integration, and an intentionally simple product experience.

Current focus

  • Enterprise AI product and technology strategy
  • Agentic workflows and production LLM systems
  • AI-powered content production
  • Multidisciplinary product and engineering organisations
  • Technical pre-sales and enterprise customer delivery
  • Local and privacy-conscious AI

Connect

LinkedIn

Pinned Loading

  1. image-autonamerimage-autonamerPublic

    A sandboxed macOS menu bar app that uses a local Ollama vision model to safely rename downloaded images.

    Swift 2

  2. whospokewhospokePublic

    Local, offline transcription and speaker diarization for Apple Silicon, with cross-file voice identification and resumable processing.

    Python

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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15
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 · 15
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Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor

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DavidVaness/README.md
Hi, I'm David
I am an AI product and technology leader at Accenture Song, building privacy-conscious AI products and platforms at the intersection of enterprise strategy and hands-on engineering.
I lead product and technology for an internal AI venture, serve as the platform's global representative, and remain hands-on in architecture and critical engineering decisions.
My background spans 16+ years across software engineering, entrepreneurship, consulting, and multidisciplinary product leadership.
I specialise in turning emerging AI capabilities into production platforms, scalable delivery models, and useful customer experiences.
I also build local-first AI tools for sensitive, messy human information.
They make capable models practical without making cloud upload the default.
Selected work
whospoke
Local, offline transcription and speaker identification for Apple Silicon.
It combines multilingual speech recognition, speaker diarization, voice embeddings, and cross-file identity matching without uploading recordings to a hosted transcription service.
What it demonstrates: a resilient multi-model pipeline, local AI acceleration, privacy-aware product design, and usable outputs for real research, meetings, and media workflows.
Image Autonamer
Local AI image naming for macOS Downloads folders.
It uses a vision-language model through Ollama to produce useful filenames while keeping image data on the device.
What it demonstrates: safe automation around an untrusted model, durable local state, macOS integration, and an intentionally simple product experience.
Current focus
  • Enterprise AI product and technology strategy
  • Agentic workflows and production LLM systems
  • AI-powered content production
  • Multidisciplinary product and engineering organisations
  • Technical pre-sales and enterprise customer delivery
  • Local and privacy-conscious AI
Connect
LinkedIn

Pinned
Loading
  1. image-autonamerimage-autonamerPublic
    
A sandboxed macOS menu bar app that uses a local Ollama vision model to safely rename downloaded images.

    Swift
2

  2. whospokewhospokePublic
    
Local, offline transcription and speaker diarization for Apple Silicon, with cross-file voice identification and resumable processing.

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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15
followers
 · 15
following

Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor

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DavidVaness/README.md
Hi, I'm David
I am an AI product and technology leader at Accenture Song, building privacy-conscious AI products and platforms at the intersection of enterprise strategy and hands-on engineering.
I lead product and technology for an internal AI venture, serve as the platform's global representative, and remain hands-on in architecture and critical engineering decisions.
My background spans 16+ years across software engineering, entrepreneurship, consulting, and multidisciplinary product leadership.
I specialise in turning emerging AI capabilities into production platforms, scalable delivery models, and useful customer experiences.
I also build local-first AI tools for sensitive, messy human information.
They make capable models practical without making cloud upload the default.
Selected work
whospoke
Local, offline transcription and speaker identification for Apple Silicon.
It combines multilingual speech recognition, speaker diarization, voice embeddings, and cross-file identity matching without uploading recordings to a hosted transcription service.
What it demonstrates: a resilient multi-model pipeline, local AI acceleration, privacy-aware product design, and usable outputs for real research, meetings, and media workflows.
Image Autonamer
Local AI image naming for macOS Downloads folders.
It uses a vision-language model through Ollama to produce useful filenames while keeping image data on the device.
What it demonstrates: safe automation around an untrusted model, durable local state, macOS integration, and an intentionally simple product experience.
Current focus
  • Enterprise AI product and technology strategy
  • Agentic workflows and production LLM systems
  • AI-powered content production
  • Multidisciplinary product and engineering organisations
  • Technical pre-sales and enterprise customer delivery
  • Local and privacy-conscious AI
Connect
LinkedIn

Pinned
Loading
  1. image-autonamerimage-autonamerPublic
    
A sandboxed macOS menu bar app that uses a local Ollama vision model to safely rename downloaded images.

    Swift
2

  2. whospokewhospokePublic
    
Local, offline transcription and speaker diarization for Apple Silicon, with cross-file voice identification and resumable processing.

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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View DavidVaness's full-sized avatar
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🌮
15
followers
 · 15
following

Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor

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DavidVaness/README.md
Hi, I'm David
I am an AI product and technology leader at Accenture Song, building privacy-conscious AI products and platforms at the intersection of enterprise strategy and hands-on engineering.
I lead product and technology for an internal AI venture, serve as the platform's global representative, and remain hands-on in architecture and critical engineering decisions.
My background spans 16+ years across software engineering, entrepreneurship, consulting, and multidisciplinary product leadership.
I specialise in turning emerging AI capabilities into production platforms, scalable delivery models, and useful customer experiences.
I also build local-first AI tools for sensitive, messy human information.
They make capable models practical without making cloud upload the default.
Selected work
whospoke
Local, offline transcription and speaker identification for Apple Silicon.
It combines multilingual speech recognition, speaker diarization, voice embeddings, and cross-file identity matching without uploading recordings to a hosted transcription service.
What it demonstrates: a resilient multi-model pipeline, local AI acceleration, privacy-aware product design, and usable outputs for real research, meetings, and media workflows.
Image Autonamer
Local AI image naming for macOS Downloads folders.
It uses a vision-language model through Ollama to produce useful filenames while keeping image data on the device.
What it demonstrates: safe automation around an untrusted model, durable local state, macOS integration, and an intentionally simple product experience.
Current focus
  • Enterprise AI product and technology strategy
  • Agentic workflows and production LLM systems
  • AI-powered content production
  • Multidisciplinary product and engineering organisations
  • Technical pre-sales and enterprise customer delivery
  • Local and privacy-conscious AI
Connect
LinkedIn

Pinned
Loading
  1. image-autonamerimage-autonamerPublic
    
A sandboxed macOS menu bar app that uses a local Ollama vision model to safely rename downloaded images.

    Swift
2

  2. whospokewhospokePublic
    
Local, offline transcription and speaker diarization for Apple Silicon, with cross-file voice identification and resumable processing.

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
View DavidVaness's full-sized avatar
🌮
🌮
15
followers
 · 15
following

Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor

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DavidVaness/README.md
Hi, I'm David
I am an AI product and technology leader at Accenture Song, building privacy-conscious AI products and platforms at the intersection of enterprise strategy and hands-on engineering.
I lead product and technology for an internal AI venture, serve as the platform's global representative, and remain hands-on in architecture and critical engineering decisions.
My background spans 16+ years across software engineering, entrepreneurship, consulting, and multidisciplinary product leadership.
I specialise in turning emerging AI capabilities into production platforms, scalable delivery models, and useful customer experiences.
I also build local-first AI tools for sensitive, messy human information.
They make capable models practical without making cloud upload the default.
Selected work
whospoke
Local, offline transcription and speaker identification for Apple Silicon.
It combines multilingual speech recognition, speaker diarization, voice embeddings, and cross-file identity matching without uploading recordings to a hosted transcription service.
What it demonstrates: a resilient multi-model pipeline, local AI acceleration, privacy-aware product design, and usable outputs for real research, meetings, and media workflows.
Image Autonamer
Local AI image naming for macOS Downloads folders.
It uses a vision-language model through Ollama to produce useful filenames while keeping image data on the device.
What it demonstrates: safe automation around an untrusted model, durable local state, macOS integration, and an intentionally simple product experience.
Current focus
  • Enterprise AI product and technology strategy
  • Agentic workflows and production LLM systems
  • AI-powered content production
  • Multidisciplinary product and engineering organisations
  • Technical pre-sales and enterprise customer delivery
  • Local and privacy-conscious AI
Connect
LinkedIn

Pinned
Loading
  1. image-autonamerimage-autonamerPublic
    
A sandboxed macOS menu bar app that uses a local Ollama vision model to safely rename downloaded images.

    Swift
2

  2. whospokewhospokePublic
    
Local, offline transcription and speaker diarization for Apple Silicon, with cross-file voice identification and resumable processing.

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
View DavidVaness's full-sized avatar
🌮
🌮
15
followers
 · 15
following

Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor

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DavidVaness/README.md
Hi, I'm David
I am an AI product and technology leader at Accenture Song, building privacy-conscious AI products and platforms at the intersection of enterprise strategy and hands-on engineering.
I lead product and technology for an internal AI venture, serve as the platform's global representative, and remain hands-on in architecture and critical engineering decisions.
My background spans 16+ years across software engineering, entrepreneurship, consulting, and multidisciplinary product leadership.
I specialise in turning emerging AI capabilities into production platforms, scalable delivery models, and useful customer experiences.
I also build local-first AI tools for sensitive, messy human information.
They make capable models practical without making cloud upload the default.
Selected work
whospoke
Local, offline transcription and speaker identification for Apple Silicon.
It combines multilingual speech recognition, speaker diarization, voice embeddings, and cross-file identity matching without uploading recordings to a hosted transcription service.
What it demonstrates: a resilient multi-model pipeline, local AI acceleration, privacy-aware product design, and usable outputs for real research, meetings, and media workflows.
Image Autonamer
Local AI image naming for macOS Downloads folders.
It uses a vision-language model through Ollama to produce useful filenames while keeping image data on the device.
What it demonstrates: safe automation around an untrusted model, durable local state, macOS integration, and an intentionally simple product experience.
Current focus
  • Enterprise AI product and technology strategy
  • Agentic workflows and production LLM systems
  • AI-powered content production
  • Multidisciplinary product and engineering organisations
  • Technical pre-sales and enterprise customer delivery
  • Local and privacy-conscious AI
Connect
LinkedIn

Pinned
Loading
  1. image-autonamerimage-autonamerPublic
    
A sandboxed macOS menu bar app that uses a local Ollama vision model to safely rename downloaded images.

    Swift
2

  2. whospokewhospokePublic
    
Local, offline transcription and speaker diarization for Apple Silicon, with cross-file voice identification and resumable processing.

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
View DavidVaness's full-sized avatar
🌮
🌮
15
followers
 · 15
following

Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair Extraordinairex4Achievement: Pull Sharkx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor

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DavidVaness/README.md
Hi, I'm David
I am an AI product and technology leader at Accenture Song, building privacy-conscious AI products and platforms at the intersection of enterprise strategy and hands-on engineering.
I lead product and technology for an internal AI venture, serve as the platform's global representative, and remain hands-on in architecture and critical engineering decisions.
My background spans 16+ years across software engineering, entrepreneurship, consulting, and multidisciplinary product leadership.
I specialise in turning emerging AI capabilities into production platforms, scalable delivery models, and useful customer experiences.
I also build local-first AI tools for sensitive, messy human information.
They make capable models practical without making cloud upload the default.
Selected work
whospoke
Local, offline transcription and speaker identification for Apple Silicon.
It combines multilingual speech recognition, speaker diarization, voice embeddings, and cross-file identity matching without uploading recordings to a hosted transcription service.
What it demonstrates: a resilient multi-model pipeline, local AI acceleration, privacy-aware product design, and usable outputs for real research, meetings, and media workflows.
Image Autonamer
Local AI image naming for macOS Downloads folders.
It uses a vision-language model through Ollama to produce useful filenames while keeping image data on the device.
What it demonstrates: safe automation around an untrusted model, durable local state, macOS integration, and an intentionally simple product experience.
Current focus
  • Enterprise AI product and technology strategy
  • Agentic workflows and production LLM systems
  • AI-powered content production
  • Multidisciplinary product and engineering organisations
  • Technical pre-sales and enterprise customer delivery
  • Local and privacy-conscious AI
Connect
LinkedIn

Pinned
Loading
  1. image-autonamerimage-autonamerPublic
    
A sandboxed macOS menu bar app that uses a local Ollama vision model to safely rename downloaded images.

    Swift
2

  2. whospokewhospokePublic
    
Local, offline transcription and speaker diarization for Apple Silicon, with cross-file voice identification and resumable processing.

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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DavidVaness/README.md
Hi, I'm David
I am an AI product and technology leader at Accenture Song, building privacy-conscious AI products and platforms at the intersection of enterprise strategy and hands-on engineering.
I lead product and technology for an internal AI venture, serve as the platform's global representative, and remain hands-on in architecture and critical engineering decisions.
My background spans 16+ years across software engineering, entrepreneurship, consulting, and multidisciplinary product leadership.
I specialise in turning emerging AI capabilities into production platforms, scalable delivery models, and useful customer experiences.
I also build local-first AI tools for sensitive, messy human information.
They make capable models practical without making cloud upload the default.
Selected work
whospoke
Local, offline transcription and speaker identification for Apple Silicon.
It combines multilingual speech recognition, speaker diarization, voice embeddings, and cross-file identity matching without uploading recordings to a hosted transcription service.
What it demonstrates: a resilient multi-model pipeline, local AI acceleration, privacy-aware product design, and usable outputs for real research, meetings, and media workflows.
Image Autonamer
Local AI image naming for macOS Downloads folders.
It uses a vision-language model through Ollama to produce useful filenames while keeping image data on the device.
What it demonstrates: safe automation around an untrusted model, durable local state, macOS integration, and an intentionally simple product experience.
Current focus
  • Enterprise AI product and technology strategy
  • Agentic workflows and production LLM systems
  • AI-powered content production
  • Multidisciplinary product and engineering organisations
  • Technical pre-sales and enterprise customer delivery
  • Local and privacy-conscious AI
Connect
LinkedIn

Pinned
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  1. image-autonamerimage-autonamerPublic
    
A sandboxed macOS menu bar app that uses a local Ollama vision model to safely rename downloaded images.

    Swift
2

  2. whospokewhospokePublic
    
Local, offline transcription and speaker diarization for Apple Silicon, with cross-file voice identification and resumable processing.

    Python