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Achievement: YOLOAchievement: Pull Shark

Achievements

Achievement: YOLOAchievement: Pull Shark

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autumninthecloud/README.md

Hi there 👋

Senior Technical Product Manager | AI, Data & Industrial SaaS

I'm a product leader specializing in AI, data products, B2B SaaS, and industrial technology, with 15+ years of experience spanning product management, data science, engineering, and commercial strategy.

I currently lead product at an AI-driven industrial SaaS company, where I established the company's first product management function and lead product strategy for industrial automation, observability, and sustainability solutions.

My technical foundation comes from a Master of Information and Data Science (MIDS) from UC Berkeley, complemented by earlier experience in engineering and global product management across water, utilities, manufacturing, energy, and industrial technology.

Beyond Product & Technology

I'm particularly passionate about using technology to make communities and built environments safer.

My interest in safety comes from both my engineering background and my belief that technology should solve meaningful, real-world problems—not just optimize metrics. I've worked on projects focused on building-code accessibility, safety compliance, data-driven community decision-making, and public-interest technology.

One example is CodeQuery, an AI assistant designed to make building codes easier to understand and improve safety compliance. I also care deeply about using data and technology to help communities make better-informed decisions about the places where people live and work.

This intersection—AI + product + safety + social impact—is a particularly meaningful part of the work I want to continue building.

What I Build

-AI and machine-learning products -Data analytics and decision-support platforms -B2B SaaS products and platforms -Industrial IoT and automation solutions -Customer-facing AI applications -Safety and compliance technology -Products that translate technical capabilities into measurable business and social outcomes

Repository Table of Contents

MIDS Coursework

-W210: Capstone - Influence Maximization and Fairness in Social Networks at Scale

-W231: Behind the Data

-W241: Causal Field Experiments

-W207: Machine Learning

-W203: Statistics

-W200: Programming with Python

-W209: Data Visualization - Tableau

-Data Viz Final project: Tracking Food Prices Around the Globe

Personal Advocacy

I've been researching and developing a product that utilizes AI and ML to identify building safety issues sooner. The product is called CodeQuery - check it out!

-UC Berkeley Calhacks AI/LLM hackathon - June 2023 - CodeQuery.AI

-CodeQuery.AI Devpost Project Page

Pinned Loading

  1. housing-agent-evalhousing-agent-evalPublic

    A Claude Code playground for evaluating agent architectures on housing safety analytics: single vs multi-agent pipelines, failure-mode analysis (MAST), and a lightweight governance audit mapped to …

    Python

  2. mike-khor/BobBuilderGPTmike-khor/BobBuilderGPTPublic

    For CalHacks Hackathon 2023, team members: Mike Khor, Autumn Rains, Eric Dansforth, Meera Vinod

    Jupyter Notebook 2 1

  3. AIBillBriefAIBillBriefPublic

    Python

  4. IM_w_fairnessIM_w_fairnessPublic

    Our group capstone project site for UC Berkeley's MIDS W210/Capstone.

    JavaScript 6

  5. Machine_Learning_W207Machine_Learning_W207Public

    Final Project for MIDS w207 machine learning course.

    Jupyter Notebook

  6. Olive_Oil_Experiment_W241Olive_Oil_Experiment_W241Public

    A causal field experiment to understand if product preference can be influenced based on marketing messaging. Final Project for MIDS w241.

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
View autumninthecloud's full-sized avatar
5
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 · 7
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Achievements
Achievement: YOLOAchievement: Pull Shark
Achievements
Achievement: YOLOAchievement: Pull Shark

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autumninthecloud/README.md
Hi there 👋
Senior Technical Product Manager | AI, Data & Industrial SaaS
I'm a product leader specializing in AI, data products, B2B SaaS, and industrial technology, with 15+ years of experience spanning product management, data science, engineering, and commercial strategy.
I currently lead product at an AI-driven industrial SaaS company, where I established the company's first product management function and lead product strategy for industrial automation, observability, and sustainability solutions.
My technical foundation comes from a Master of Information and Data Science (MIDS) from UC Berkeley, complemented by earlier experience in engineering and global product management across water, utilities, manufacturing, energy, and industrial technology.
Beyond Product & Technology
I'm particularly passionate about using technology to make communities and built environments safer.
My interest in safety comes from both my engineering background and my belief that technology should solve meaningful, real-world problems—not just optimize metrics. I've worked on projects focused on building-code accessibility, safety compliance, data-driven community decision-making, and public-interest technology.
One example is CodeQuery, an AI assistant designed to make building codes easier to understand and improve safety compliance. I also care deeply about using data and technology to help communities make better-informed decisions about the places where people live and work.
This intersection—AI + product + safety + social impact—is a particularly meaningful part of the work I want to continue building.
What I Build
-AI and machine-learning products
-Data analytics and decision-support platforms
-B2B SaaS products and platforms
-Industrial IoT and automation solutions
-Customer-facing AI applications
-Safety and compliance technology
-Products that translate technical capabilities into measurable business and social outcomes
Repository Table of Contents
MIDS Coursework
-W210: Capstone - Influence Maximization and Fairness in Social Networks at Scale
-W231: Behind the Data 
-W241: Causal Field Experiments
-W207: Machine Learning
-W203: Statistics
-W200: Programming with Python
-W209: Data Visualization - Tableau
-Data Viz Final project: Tracking Food Prices Around the Globe
Personal Advocacy
I've been researching and developing a product that utilizes AI and ML to identify building safety issues sooner. The product is called CodeQuery - check it out!
-UC Berkeley Calhacks AI/LLM hackathon - June 2023 - CodeQuery.AI
-CodeQuery.AI Devpost Project Page

Pinned
Loading
  1. housing-agent-evalhousing-agent-evalPublic
    
A Claude Code playground for evaluating agent architectures on housing safety analytics: single vs multi-agent pipelines, failure-mode analysis (MAST), and a lightweight governance audit mapped to …

    Python
  2. mike-khor/BobBuilderGPTmike-khor/BobBuilderGPTPublic
    
For CalHacks Hackathon 2023, team members: Mike Khor, Autumn Rains, Eric Dansforth, Meera Vinod

    Jupyter Notebook
2

1

  3. AIBillBriefAIBillBriefPublic
    Python
  4. IM_w_fairnessIM_w_fairnessPublic
    
Our group capstone project site for UC Berkeley's MIDS W210/Capstone.

    JavaScript
6

  5. Machine_Learning_W207Machine_Learning_W207Public
    
Final Project for MIDS w207 machine learning course.

    Jupyter Notebook
  6. Olive_Oil_Experiment_W241Olive_Oil_Experiment_W241Public
    
A causal field experiment to understand if product preference can be influenced based on marketing messaging. Final Project for MIDS w241.


, '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('^' + ".*" + '

Skip to content
View autumninthecloud's full-sized avatar
5
followers
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Shark
Achievements
Achievement: YOLOAchievement: Pull Shark

Block or report autumninthecloud

Block user

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Learn more about blocking users.


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autumninthecloud/README.md
Hi there 👋
Senior Technical Product Manager | AI, Data & Industrial SaaS
I'm a product leader specializing in AI, data products, B2B SaaS, and industrial technology, with 15+ years of experience spanning product management, data science, engineering, and commercial strategy.
I currently lead product at an AI-driven industrial SaaS company, where I established the company's first product management function and lead product strategy for industrial automation, observability, and sustainability solutions.
My technical foundation comes from a Master of Information and Data Science (MIDS) from UC Berkeley, complemented by earlier experience in engineering and global product management across water, utilities, manufacturing, energy, and industrial technology.
Beyond Product & Technology
I'm particularly passionate about using technology to make communities and built environments safer.
My interest in safety comes from both my engineering background and my belief that technology should solve meaningful, real-world problems—not just optimize metrics. I've worked on projects focused on building-code accessibility, safety compliance, data-driven community decision-making, and public-interest technology.
One example is CodeQuery, an AI assistant designed to make building codes easier to understand and improve safety compliance. I also care deeply about using data and technology to help communities make better-informed decisions about the places where people live and work.
This intersection—AI + product + safety + social impact—is a particularly meaningful part of the work I want to continue building.
What I Build
-AI and machine-learning products
-Data analytics and decision-support platforms
-B2B SaaS products and platforms
-Industrial IoT and automation solutions
-Customer-facing AI applications
-Safety and compliance technology
-Products that translate technical capabilities into measurable business and social outcomes
Repository Table of Contents
MIDS Coursework
-W210: Capstone - Influence Maximization and Fairness in Social Networks at Scale
-W231: Behind the Data 
-W241: Causal Field Experiments
-W207: Machine Learning
-W203: Statistics
-W200: Programming with Python
-W209: Data Visualization - Tableau
-Data Viz Final project: Tracking Food Prices Around the Globe
Personal Advocacy
I've been researching and developing a product that utilizes AI and ML to identify building safety issues sooner. The product is called CodeQuery - check it out!
-UC Berkeley Calhacks AI/LLM hackathon - June 2023 - CodeQuery.AI
-CodeQuery.AI Devpost Project Page

Pinned
Loading
  1. housing-agent-evalhousing-agent-evalPublic
    
A Claude Code playground for evaluating agent architectures on housing safety analytics: single vs multi-agent pipelines, failure-mode analysis (MAST), and a lightweight governance audit mapped to …

    Python
  2. mike-khor/BobBuilderGPTmike-khor/BobBuilderGPTPublic
    
For CalHacks Hackathon 2023, team members: Mike Khor, Autumn Rains, Eric Dansforth, Meera Vinod

    Jupyter Notebook
2

1

  3. AIBillBriefAIBillBriefPublic
    Python
  4. IM_w_fairnessIM_w_fairnessPublic
    
Our group capstone project site for UC Berkeley's MIDS W210/Capstone.

    JavaScript
6

  5. Machine_Learning_W207Machine_Learning_W207Public
    
Final Project for MIDS w207 machine learning course.

    Jupyter Notebook
  6. Olive_Oil_Experiment_W241Olive_Oil_Experiment_W241Public
    
A causal field experiment to understand if product preference can be influenced based on marketing messaging. Final Project for MIDS w241.


, '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('^' + ".*" + '

Skip to content
View autumninthecloud's full-sized avatar
5
followers
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Shark
Achievements
Achievement: YOLOAchievement: Pull Shark

Block or report autumninthecloud

Block user

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autumninthecloud/README.md
Hi there 👋
Senior Technical Product Manager | AI, Data & Industrial SaaS
I'm a product leader specializing in AI, data products, B2B SaaS, and industrial technology, with 15+ years of experience spanning product management, data science, engineering, and commercial strategy.
I currently lead product at an AI-driven industrial SaaS company, where I established the company's first product management function and lead product strategy for industrial automation, observability, and sustainability solutions.
My technical foundation comes from a Master of Information and Data Science (MIDS) from UC Berkeley, complemented by earlier experience in engineering and global product management across water, utilities, manufacturing, energy, and industrial technology.
Beyond Product & Technology
I'm particularly passionate about using technology to make communities and built environments safer.
My interest in safety comes from both my engineering background and my belief that technology should solve meaningful, real-world problems—not just optimize metrics. I've worked on projects focused on building-code accessibility, safety compliance, data-driven community decision-making, and public-interest technology.
One example is CodeQuery, an AI assistant designed to make building codes easier to understand and improve safety compliance. I also care deeply about using data and technology to help communities make better-informed decisions about the places where people live and work.
This intersection—AI + product + safety + social impact—is a particularly meaningful part of the work I want to continue building.
What I Build
-AI and machine-learning products
-Data analytics and decision-support platforms
-B2B SaaS products and platforms
-Industrial IoT and automation solutions
-Customer-facing AI applications
-Safety and compliance technology
-Products that translate technical capabilities into measurable business and social outcomes
Repository Table of Contents
MIDS Coursework
-W210: Capstone - Influence Maximization and Fairness in Social Networks at Scale
-W231: Behind the Data 
-W241: Causal Field Experiments
-W207: Machine Learning
-W203: Statistics
-W200: Programming with Python
-W209: Data Visualization - Tableau
-Data Viz Final project: Tracking Food Prices Around the Globe
Personal Advocacy
I've been researching and developing a product that utilizes AI and ML to identify building safety issues sooner. The product is called CodeQuery - check it out!
-UC Berkeley Calhacks AI/LLM hackathon - June 2023 - CodeQuery.AI
-CodeQuery.AI Devpost Project Page

Pinned
Loading
  1. housing-agent-evalhousing-agent-evalPublic
    
A Claude Code playground for evaluating agent architectures on housing safety analytics: single vs multi-agent pipelines, failure-mode analysis (MAST), and a lightweight governance audit mapped to …

    Python
  2. mike-khor/BobBuilderGPTmike-khor/BobBuilderGPTPublic
    
For CalHacks Hackathon 2023, team members: Mike Khor, Autumn Rains, Eric Dansforth, Meera Vinod

    Jupyter Notebook
2

1

  3. AIBillBriefAIBillBriefPublic
    Python
  4. IM_w_fairnessIM_w_fairnessPublic
    
Our group capstone project site for UC Berkeley's MIDS W210/Capstone.

    JavaScript
6

  5. Machine_Learning_W207Machine_Learning_W207Public
    
Final Project for MIDS w207 machine learning course.

    Jupyter Notebook
  6. Olive_Oil_Experiment_W241Olive_Oil_Experiment_W241Public
    
A causal field experiment to understand if product preference can be influenced based on marketing messaging. Final Project for MIDS w241.


, '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 autumninthecloud's full-sized avatar
5
followers
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Shark
Achievements
Achievement: YOLOAchievement: Pull Shark

Block or report autumninthecloud

Block user

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autumninthecloud/README.md
Hi there 👋
Senior Technical Product Manager | AI, Data & Industrial SaaS
I'm a product leader specializing in AI, data products, B2B SaaS, and industrial technology, with 15+ years of experience spanning product management, data science, engineering, and commercial strategy.
I currently lead product at an AI-driven industrial SaaS company, where I established the company's first product management function and lead product strategy for industrial automation, observability, and sustainability solutions.
My technical foundation comes from a Master of Information and Data Science (MIDS) from UC Berkeley, complemented by earlier experience in engineering and global product management across water, utilities, manufacturing, energy, and industrial technology.
Beyond Product & Technology
I'm particularly passionate about using technology to make communities and built environments safer.
My interest in safety comes from both my engineering background and my belief that technology should solve meaningful, real-world problems—not just optimize metrics. I've worked on projects focused on building-code accessibility, safety compliance, data-driven community decision-making, and public-interest technology.
One example is CodeQuery, an AI assistant designed to make building codes easier to understand and improve safety compliance. I also care deeply about using data and technology to help communities make better-informed decisions about the places where people live and work.
This intersection—AI + product + safety + social impact—is a particularly meaningful part of the work I want to continue building.
What I Build
-AI and machine-learning products
-Data analytics and decision-support platforms
-B2B SaaS products and platforms
-Industrial IoT and automation solutions
-Customer-facing AI applications
-Safety and compliance technology
-Products that translate technical capabilities into measurable business and social outcomes
Repository Table of Contents
MIDS Coursework
-W210: Capstone - Influence Maximization and Fairness in Social Networks at Scale
-W231: Behind the Data 
-W241: Causal Field Experiments
-W207: Machine Learning
-W203: Statistics
-W200: Programming with Python
-W209: Data Visualization - Tableau
-Data Viz Final project: Tracking Food Prices Around the Globe
Personal Advocacy
I've been researching and developing a product that utilizes AI and ML to identify building safety issues sooner. The product is called CodeQuery - check it out!
-UC Berkeley Calhacks AI/LLM hackathon - June 2023 - CodeQuery.AI
-CodeQuery.AI Devpost Project Page

Pinned
Loading
  1. housing-agent-evalhousing-agent-evalPublic
    
A Claude Code playground for evaluating agent architectures on housing safety analytics: single vs multi-agent pipelines, failure-mode analysis (MAST), and a lightweight governance audit mapped to …

    Python
  2. mike-khor/BobBuilderGPTmike-khor/BobBuilderGPTPublic
    
For CalHacks Hackathon 2023, team members: Mike Khor, Autumn Rains, Eric Dansforth, Meera Vinod

    Jupyter Notebook
2

1

  3. AIBillBriefAIBillBriefPublic
    Python
  4. IM_w_fairnessIM_w_fairnessPublic
    
Our group capstone project site for UC Berkeley's MIDS W210/Capstone.

    JavaScript
6

  5. Machine_Learning_W207Machine_Learning_W207Public
    
Final Project for MIDS w207 machine learning course.

    Jupyter Notebook
  6. Olive_Oil_Experiment_W241Olive_Oil_Experiment_W241Public
    
A causal field experiment to understand if product preference can be influenced based on marketing messaging. Final Project for MIDS w241.


, '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 autumninthecloud's full-sized avatar
5
followers
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Shark
Achievements
Achievement: YOLOAchievement: Pull Shark

Block or report autumninthecloud

Block user

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Learn more about blocking users.


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Learn more about reporting abuse.

Report abuse
autumninthecloud/README.md
Hi there 👋
Senior Technical Product Manager | AI, Data & Industrial SaaS
I'm a product leader specializing in AI, data products, B2B SaaS, and industrial technology, with 15+ years of experience spanning product management, data science, engineering, and commercial strategy.
I currently lead product at an AI-driven industrial SaaS company, where I established the company's first product management function and lead product strategy for industrial automation, observability, and sustainability solutions.
My technical foundation comes from a Master of Information and Data Science (MIDS) from UC Berkeley, complemented by earlier experience in engineering and global product management across water, utilities, manufacturing, energy, and industrial technology.
Beyond Product & Technology
I'm particularly passionate about using technology to make communities and built environments safer.
My interest in safety comes from both my engineering background and my belief that technology should solve meaningful, real-world problems—not just optimize metrics. I've worked on projects focused on building-code accessibility, safety compliance, data-driven community decision-making, and public-interest technology.
One example is CodeQuery, an AI assistant designed to make building codes easier to understand and improve safety compliance. I also care deeply about using data and technology to help communities make better-informed decisions about the places where people live and work.
This intersection—AI + product + safety + social impact—is a particularly meaningful part of the work I want to continue building.
What I Build
-AI and machine-learning products
-Data analytics and decision-support platforms
-B2B SaaS products and platforms
-Industrial IoT and automation solutions
-Customer-facing AI applications
-Safety and compliance technology
-Products that translate technical capabilities into measurable business and social outcomes
Repository Table of Contents
MIDS Coursework
-W210: Capstone - Influence Maximization and Fairness in Social Networks at Scale
-W231: Behind the Data 
-W241: Causal Field Experiments
-W207: Machine Learning
-W203: Statistics
-W200: Programming with Python
-W209: Data Visualization - Tableau
-Data Viz Final project: Tracking Food Prices Around the Globe
Personal Advocacy
I've been researching and developing a product that utilizes AI and ML to identify building safety issues sooner. The product is called CodeQuery - check it out!
-UC Berkeley Calhacks AI/LLM hackathon - June 2023 - CodeQuery.AI
-CodeQuery.AI Devpost Project Page

Pinned
Loading
  1. housing-agent-evalhousing-agent-evalPublic
    
A Claude Code playground for evaluating agent architectures on housing safety analytics: single vs multi-agent pipelines, failure-mode analysis (MAST), and a lightweight governance audit mapped to …

    Python
  2. mike-khor/BobBuilderGPTmike-khor/BobBuilderGPTPublic
    
For CalHacks Hackathon 2023, team members: Mike Khor, Autumn Rains, Eric Dansforth, Meera Vinod

    Jupyter Notebook
2

1

  3. AIBillBriefAIBillBriefPublic
    Python
  4. IM_w_fairnessIM_w_fairnessPublic
    
Our group capstone project site for UC Berkeley's MIDS W210/Capstone.

    JavaScript
6

  5. Machine_Learning_W207Machine_Learning_W207Public
    
Final Project for MIDS w207 machine learning course.

    Jupyter Notebook
  6. Olive_Oil_Experiment_W241Olive_Oil_Experiment_W241Public
    
A causal field experiment to understand if product preference can be influenced based on marketing messaging. Final Project for MIDS w241.


, 'i');
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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('^' + ".*" + '

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Achievement: YOLOAchievement: Pull Shark
Achievements
Achievement: YOLOAchievement: Pull Shark

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autumninthecloud/README.md
Hi there 👋
Senior Technical Product Manager | AI, Data & Industrial SaaS
I'm a product leader specializing in AI, data products, B2B SaaS, and industrial technology, with 15+ years of experience spanning product management, data science, engineering, and commercial strategy.
I currently lead product at an AI-driven industrial SaaS company, where I established the company's first product management function and lead product strategy for industrial automation, observability, and sustainability solutions.
My technical foundation comes from a Master of Information and Data Science (MIDS) from UC Berkeley, complemented by earlier experience in engineering and global product management across water, utilities, manufacturing, energy, and industrial technology.
Beyond Product & Technology
I'm particularly passionate about using technology to make communities and built environments safer.
My interest in safety comes from both my engineering background and my belief that technology should solve meaningful, real-world problems—not just optimize metrics. I've worked on projects focused on building-code accessibility, safety compliance, data-driven community decision-making, and public-interest technology.
One example is CodeQuery, an AI assistant designed to make building codes easier to understand and improve safety compliance. I also care deeply about using data and technology to help communities make better-informed decisions about the places where people live and work.
This intersection—AI + product + safety + social impact—is a particularly meaningful part of the work I want to continue building.
What I Build
-AI and machine-learning products
-Data analytics and decision-support platforms
-B2B SaaS products and platforms
-Industrial IoT and automation solutions
-Customer-facing AI applications
-Safety and compliance technology
-Products that translate technical capabilities into measurable business and social outcomes
Repository Table of Contents
MIDS Coursework
-W210: Capstone - Influence Maximization and Fairness in Social Networks at Scale
-W231: Behind the Data 
-W241: Causal Field Experiments
-W207: Machine Learning
-W203: Statistics
-W200: Programming with Python
-W209: Data Visualization - Tableau
-Data Viz Final project: Tracking Food Prices Around the Globe
Personal Advocacy
I've been researching and developing a product that utilizes AI and ML to identify building safety issues sooner. The product is called CodeQuery - check it out!
-UC Berkeley Calhacks AI/LLM hackathon - June 2023 - CodeQuery.AI
-CodeQuery.AI Devpost Project Page

Pinned
Loading
  1. housing-agent-evalhousing-agent-evalPublic
    
A Claude Code playground for evaluating agent architectures on housing safety analytics: single vs multi-agent pipelines, failure-mode analysis (MAST), and a lightweight governance audit mapped to …

    Python
  2. mike-khor/BobBuilderGPTmike-khor/BobBuilderGPTPublic
    
For CalHacks Hackathon 2023, team members: Mike Khor, Autumn Rains, Eric Dansforth, Meera Vinod

    Jupyter Notebook
2

1

  3. AIBillBriefAIBillBriefPublic
    Python
  4. IM_w_fairnessIM_w_fairnessPublic
    
Our group capstone project site for UC Berkeley's MIDS W210/Capstone.

    JavaScript
6

  5. Machine_Learning_W207Machine_Learning_W207Public
    
Final Project for MIDS w207 machine learning course.

    Jupyter Notebook
  6. Olive_Oil_Experiment_W241Olive_Oil_Experiment_W241Public
    
A causal field experiment to understand if product preference can be influenced based on marketing messaging. Final Project for MIDS w241.


, '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); }
})();
})();

Skip to content
View autumninthecloud's full-sized avatar
5
followers
 · 7
following

Achievements
Achievement: YOLOAchievement: Pull Shark
Achievements
Achievement: YOLOAchievement: Pull Shark

Block or report autumninthecloud

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autumninthecloud/README.md
Hi there 👋
Senior Technical Product Manager | AI, Data & Industrial SaaS
I'm a product leader specializing in AI, data products, B2B SaaS, and industrial technology, with 15+ years of experience spanning product management, data science, engineering, and commercial strategy.
I currently lead product at an AI-driven industrial SaaS company, where I established the company's first product management function and lead product strategy for industrial automation, observability, and sustainability solutions.
My technical foundation comes from a Master of Information and Data Science (MIDS) from UC Berkeley, complemented by earlier experience in engineering and global product management across water, utilities, manufacturing, energy, and industrial technology.
Beyond Product & Technology
I'm particularly passionate about using technology to make communities and built environments safer.
My interest in safety comes from both my engineering background and my belief that technology should solve meaningful, real-world problems—not just optimize metrics. I've worked on projects focused on building-code accessibility, safety compliance, data-driven community decision-making, and public-interest technology.
One example is CodeQuery, an AI assistant designed to make building codes easier to understand and improve safety compliance. I also care deeply about using data and technology to help communities make better-informed decisions about the places where people live and work.
This intersection—AI + product + safety + social impact—is a particularly meaningful part of the work I want to continue building.
What I Build
-AI and machine-learning products
-Data analytics and decision-support platforms
-B2B SaaS products and platforms
-Industrial IoT and automation solutions
-Customer-facing AI applications
-Safety and compliance technology
-Products that translate technical capabilities into measurable business and social outcomes
Repository Table of Contents
MIDS Coursework
-W210: Capstone - Influence Maximization and Fairness in Social Networks at Scale
-W231: Behind the Data 
-W241: Causal Field Experiments
-W207: Machine Learning
-W203: Statistics
-W200: Programming with Python
-W209: Data Visualization - Tableau
-Data Viz Final project: Tracking Food Prices Around the Globe
Personal Advocacy
I've been researching and developing a product that utilizes AI and ML to identify building safety issues sooner. The product is called CodeQuery - check it out!
-UC Berkeley Calhacks AI/LLM hackathon - June 2023 - CodeQuery.AI
-CodeQuery.AI Devpost Project Page

Pinned
Loading
  1. housing-agent-evalhousing-agent-evalPublic
    
A Claude Code playground for evaluating agent architectures on housing safety analytics: single vs multi-agent pipelines, failure-mode analysis (MAST), and a lightweight governance audit mapped to …

    Python
  2. mike-khor/BobBuilderGPTmike-khor/BobBuilderGPTPublic
    
For CalHacks Hackathon 2023, team members: Mike Khor, Autumn Rains, Eric Dansforth, Meera Vinod

    Jupyter Notebook
2

1

  3. AIBillBriefAIBillBriefPublic
    Python
  4. IM_w_fairnessIM_w_fairnessPublic
    
Our group capstone project site for UC Berkeley's MIDS W210/Capstone.

    JavaScript
6

  5. Machine_Learning_W207Machine_Learning_W207Public
    
Final Project for MIDS w207 machine learning course.

    Jupyter Notebook
  6. Olive_Oil_Experiment_W241Olive_Oil_Experiment_W241Public
    
A causal field experiment to understand if product preference can be influenced based on marketing messaging. Final Project for MIDS w241.