Software Engineers Know How to Build. Few Know How a Business Runs

By Nasly Duarte

The best technical people I meet can build almost anything. The gap is never the code.

The code was never the hard part. The business was.

Paul Graham wrote a line that should sit on every engineer's desk. Enterprise software companies are not technology companies. They are sales companies, and sales depends mostly on effort.

Read that again if you build for a living. The thing that wins is not the cleanest architecture. It is understanding the business the software serves.

Most builders never get that understanding. They receive a requirements document. They build against a description of the work, not the work itself. The gap between the two is where good software quietly fails.

The skill most software engineers are missing

Technical skill has a ceiling. The ceiling is business understanding.

You can write the system. The harder question is whether you know how the business actually runs. Where the money moves. Where the work breaks down. What the owner fears at two in the morning.

That knowledge does not come from a stack. It comes from being inside an operation and watching it work.

Cross-training is the highest-leverage move

The most valuable builder in business in the coming years is not the one with the deepest technical stack. It is the one who understands how a real business runs and can build for it.

That person does not discover the pain through customer interviews. They have lived it. They build the fix that removes the cause, because they watched the cause happen.

Cross-training on business operations is the highest-leverage skill a technical person can add right now. It is the skill that moves you out of the sales-company category Graham described. It puts you in the category of someone who builds what a business actually needs.

This is the work I do at Mindful Dollar. I help business owners design their own financial architecture through autonomous agents that work alongside their employees, not instead of them, to increase profit and productivity.

The Bottom Line

Building skill alone is not enough. The builders who win understand the business first.

I wrote the full thesis for my community. It covers how I treat a small business as a research environment, why full visibility beats documentation, and how an operator builds in a sprint what a corporation gates over years. I call it The Operator's Lab.

Read the full piece on Buy Me a Coffee. 

buymeacoffee.com/girlgoneverde/buildingbusinesstoolsasanengineer

Then go find the room where you can see the whole machine.

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Mindful Dollar | Nasly Duarte | Doing More With Less | mindfuldollar.blogspot.com

The Skill Nobody Teaches: Learning to Read Code

By Nasly Duarte

Readers of this blog know I am building an AI product in real time.

That product — Soulaccess, a phone-based access tech to enter churches during un — requires me to read, understand, and extend code I did not write. It requires me to direct AI coding agents and evaluate what they produce. And it requires me to teach these skills to a community of people who want to build alongside me.

Which is why this series exists.

Most churches sit empty 90 percent of the week. Meanwhile, the people who fund those churches experience grief, anxiety, and crisis at the hours when those buildings are locked. That's broken. !I'm building a Phone-based access app to sacred space, anytime https://soulaccessprototype.netlify.app

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The Overlooked Skill

Developers spend ten times more time reading code than writing it. That is not a statistic from a research paper. It is the lived reality of every developer working on a team, fixing a bug, reviewing a pull request, or building on an existing codebase.

School teaches writing. The real world demands reading.

The mismatch is significant. By the time you are hired into a technical role, you walk into a codebase you have never seen and are expected to produce output by Friday. The ability to orient yourself inside someone else's system — to find the entry point, trace the flow, understand the structure — separates productive builders from people who ask questions for two weeks before touching anything.

This matters more now, not less, because of AI coding tools. When you prompt an agent to build something, it produces code. That code might be correct. It might have subtle errors. It might follow patterns that conflict with the rest of your project. The only way to evaluate what an agent gives you is to be able to read it.

Reading code in the AI era is not about memorizing syntax. It is about the ability to open a project and understand its structure, trace one feature through an entire system, identify patterns that repeat, and notice what is well-designed versus what is a red flag.

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The Six Situations

Reading code happens in six recurring situations, each with a different objective.

The first-day read happens at a new job or when you inherit a project. You are not looking for details yet. You are asking: how is this structured and where do I start?

The bug read happens when you are assigned to fix code someone else wrote. You are asking: what was this supposed to do and where did it break?

The review read happens during a pull request or code review. You are asking: does this work, is it clean, and will it cause problems later?

The learning read happens when you open a well-built project to study it. You are asking: how did they solve this and can I use this pattern?

The library read happens when you want to understand a tool you are already using. You are asking: how does this actually work under the hood?

The inheritance read happens when someone leaves and their code stays. You are asking: what is this doing and why did they do it this way?

Each situation asks a different question but uses the same foundational skill. The ability to read unfamiliar code confidently and orient yourself inside a system you did not build.

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The Build-in-Public Context

I am teaching this skill because I am living it.

The Itemizing build — which I am documenting publicly for my community — requires me to read repositories I have never opened, understand patterns I have never implemented, and adapt them for a product I am building as I go. The agent workshop at Agentcamp gave me working code to read. Open-source libraries I am evaluating require me to assess quality before I commit to them. AI agents produce code that I need to understand before I push it to production.

Every principle in this series is one I applied this week, on a real product, in a real codebase.

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The Framework: The Bird's Eye View

The next post in this series introduces The Bird's Eye View — a three-step methodology for opening any codebase without panic. It is the first pass developers use before reading a single line of logic code. The file structure. The entry point. The config files that reveal a project's DNA in thirty seconds.

This is the methodology I applied when I opened the Itemizing repository for the first time. It is the methodology I am teaching in the summer curriculum. And it is the methodology that turns a 50,000-line codebase from overwhelming to navigable.

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The Bottom Line

Reading code is not a secondary skill. It is the primary skill of anyone building products, reviewing AI output, or working on any codebase that existed before they arrived. The faster you develop it, the faster every other technical skill follows.

Building this in public, one codebase at a time.

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Follow the full summer curriculum — including weekly code reading challenges, a live build log, and community events — at the Mindful Dollar BMAC community. The curriculum is live now and designed for people who want to build, not just read about building.

Join the Mindful Dollar BMAC Community →

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Read Next: The Bird's Eye View: How Developers Open Unfamiliar Code

Mindful Dollar | Nasly Duarte | Doing More With Less

Space Intelligence App

Space Intelligence 

You haven't heard from me in a few weeks. Here's why.

I've been building something called SoulAccess.

It's a phone-based platform that gives members secure access to sacred space outside of service hours. Faith centers maintain complete control. Members access the buildings their tithes already sustain, at the hours they actually need them.

The short version: most churches, mosques, and temples sit empty more than 90 percent of the week. Meanwhile people experience grief, anxiety, panic, and crisis at the hours when those buildings are locked. SoulAccess is the access layer that closes that gap.

I started building it on the National Day of Prayer  weeks ago. Since then:

The landing page is live at soulaccess.netlify.app. A high-fidelity clickable prototype lives on the same page. Scroll down to "Try it yourself." The prototype is fully bilingual. English and Spanish. Pilot conversations are underway with three pastors and the Mayor of Hialeah. A spot at the next GDG South Florida workshop is locked in to demo it with Misfit Labs. The whole thing is open source under CC BY 4.0 at github.com/nasly-ai/soulaccess.

You are the community that made it possible for me to spend this kind of time building. Before I share this anywhere else, I want to share it with you.

Three things you can do if you want to be part of this.

• One. Visit the site. Click through the prototype. Tell me what lands and what doesn't. Honest feedback from this group is worth more to me than the polished feedback I'll get anywhere else.

• Two. Forward this to someone. A pastor who has been on your mind. A friend who runs a community space. A developer who cares about this kind of work. The hardest part of building right now is reaching the right people. You can help just by sharing.
• Three. If you can, support this work financially. I don't draw a salary from any of this yet. Every coffee buys me another evening of building.

This is the work I'm most proud of doing. It's also the work that scares me the most. Both of those things being true at the same time tells me I'm in the right room.

Read the Full Post of my realization it was spatial not sapce intelligence. lol your live and you learn.  https://buymeacoffee.com/girlgoneverde/spacial-intelliegence 

Florida's First Applied AI Program Has a Responsibility to This Conversation

 

Miami Dade College launched Florida's first Associates & Bachelor of Science in Applied Artificial Intelligence.

That is not a small thing. It means MDC made a decision that AI literacy is not a luxury for a four-year university student. It is a right for the working adults, the career changers, the first-generation students who make up the MDC community.

I am one of those students.

I have spent over 20 years in operations accounting across construction, manufacturing, insurance restoration, and retail. I enrolled in the Applied AI program because I believe the people who understand both the operational side of business and the architecture of AI are the people who will determine whether this technology serves workers or replaces them.

What I am watching in this industry concerns me deeply.

Hyundai and Boston Dynamics are deploying humanoid robots in automotive manufacturing facilities trained on the labor of human workers. OpenAI published a 13-page policy paper this week proposing wealth funds and robot taxes to manage the economic fallout. Not one proposal in that paper addresses ownership of the AI training data generated by skilled physical labor.

The workers being displaced built the intelligence that is replacing them. They own none of it.

This is the defining workforce question of our time. And it is being answered right now, in real factories, without the workers at the table.

Florida's first Applied AI program sits in the middle of one of the most diverse working populations in the country. Miami is a manufacturing city. A logistics city. A garment city. A construction city. The workers in those industries are MDC's community.

The program has an opportunity to do something no other applied AI program in the country is doing. Train students not just to use AI tools but to understand and protect the labor rights of the people those tools are built on.

To Madeline Pumariega, President of Miami Dade College. To Manny Perez, Dean of Engineering Technology and Design. This series is part of a larger framework that I want to bring into that conversation formally.

To Pedro Santos and Mr. Knight at Entech. The panel discussion we shared was the beginning of this conversation. The framework has grown significantly since then and the Entech network represents exactly the kind of industry partner a pilot needs.

The capstone project for Florida's first Applied AI program should not just demonstrate what AI can build. It should demonstrate what AI must protect.

I help business owners design autonomous financial systems that work alongside their employees and strengthen the way their teams make decisions. My approach is grounded in years of seeing what happens when systems are built without people at the center.

Follow the blog at mindfuldollar.blogspot.com.

#MiamiDadeCollege #AppliedAI #LaborEquity #MiamiDynamics #ResponsibleAI #OperationsAccounting #NaslyDuarte

 The Mindful Dollar  ·  AI Explained Simply

"Skilled Labor Is Dead." I Disagree.

By Nasly Duarte | Mindful Dollar — Doing More With Less

I was sitting in a virtual live event this week when the speaker put up a pyramid. Tech at the top. Media and Data below it. Intellectual Property in the middle. And near the bottom, in red text: Skilled Labor. Component Labor at the base.

Then the speaker said it: "Skilled labor is dead."

The chat started moving. People nodding along. The room was full of builders and tech-forward thinkers ready to automate the future from behind a screen.

And I thought: that's not just wrong. It's incomplete in a way that could actually hurt people.

I've spent 20 years in accounting. I've lived the screen-only career. And what I've learned — through my body, not just my brain — is that the conversation about the future of work is missing something critical.

The Pyramid Gets It Backwards

The U.S. construction industry needs to attract 349,000 new workers in 2026 alone, according to Associated Builders and Contractors. Over the next decade, the industry will need 1.9 million workers just to keep up with growth and retirements. And 91% of construction firms report struggling to find qualified workers.

The retirement cliff is staggering: 41% of the construction workforce will retire by 2031. For every five Baby Boomers leaving the trades, only two younger workers are coming in behind them.

This isn't just construction. In manufacturing, 2.1 million jobs could go unfilled by 2030. And 77% of manufacturers report ongoing difficulty even finding workers.

Meanwhile — and this is the part that should make anyone in the tech space pay attention — white-collar layoffs have dominated headlines in 2025 and 2026, with technology, media, and finance companies cutting tens of thousands of positions. The skilled trades are experiencing the exact opposite. Demand is outstripping supply.

Every piece of AI technology we build still needs physical infrastructure. Servers need buildings. Buildings need electricians. Data centers need cooling systems. The cloud lives in a warehouse somewhere, and somebody had to pour that concrete, run that wiring, and connect those pipes.

When I hear "skilled labor is dead," I hear someone who has never had to call a plumber on a Sunday.

But that's not actually the argument I want to make. The real issue goes deeper.

What 20 Years at a Desk Taught Me That No Conference Will

Here's what nobody warned me about when I started my accounting career: sitting at a desk for hours and hours is a health hazard.

It doesn't matter if you work four-day weeks or seven-day weeks. It doesn't matter if AI cuts your workload to four hours a day. If you're sitting for long stretches, your body is paying a price. Slowly. Quietly. Until it isn't quiet anymore.

I lived it. Years of sedentary work did real damage to my body — damage I didn't see coming until it was already done. If you want the full story, follow my Think Like a Healer series, where I document what years of sedentary work actually does and what I'm doing to reverse it.

That experience gave me a perspective on the future of work that I don't hear anyone in the AI space talking about.

The Balance Problem

Tech work is a lot like accounting work. It takes enormous brain power. Hours of deep focus. Mental stamina. You're solving complex problems, holding abstract systems in your head, making decisions that ripple downstream.

But the human brain doesn't work in isolation from the body.

Even if we build the most incredible AI tools. Even if we automate every workflow. Even if we can run a business in four hours a day from a laptop — we still need to develop both our mind and body. Not as a nice-to-have. As a biological requirement.

Your brain chemistry needs physical output. Not just for fitness. For clarity. For regulation. For the kind of deep creative thinking that no amount of screen time produces on its own.

You can't optimize your way out of that with a better prompt.

I call this the Balance Problem, and I think it's the blind spot in every conversation about the future of AI and work.

The Interchange

Here's what I think is actually coming over the next five to ten years. I'm calling it The Interchange — the convergence of tech workers picking up trade skills and trade workers picking up tech skills. Not because the market forces them to. Because their bodies and brains require it.

The Claude builder who automates their entire content pipeline will pick up woodworking, or gardening, or welding — because they realize their sharpest thinking happens after they've used their hands.

The electrician who runs a crew of ten will start using AI to handle estimates, scheduling, and accounting — because they realize the administrative burden is what's actually burning them out.

This reminds me of the Netflix documentary The Biggest Little Farm, where John and Molly Chester buy a barren plot of land outside Los Angeles and spend eight years turning it into a thriving, biodiverse farm. The whole lesson of that film is that the ecosystem balances itself out — but only when you let both sides exist. The soil needs decomposition and growth. The land needs predators and prey. Nothing thrives in isolation.

AI — my hope — will balance us the same way. Not replace skilled labor. Balance us.

That's why I'm building Mindful Dollar at the intersection of both. I'm studying Applied AI and building software architecture — and I'm also listening to my body after two decades of desk work. "Doing More With Less" isn't just about efficiency. It's about building a life that doesn't break your body to feed your brain.

Where Do You Stand?

I wrote this post because I couldn't let "skilled labor is dead" sit unchallenged.

Are you a skilled trade and tech combo person? A developer who's picked up a physical craft? A contractor who's learning to automate? Are you interested in using AI not just to build faster, but to build a more balanced life?

Where do you see trade skills going — not just in Claude, but in the real world?

Drop a comment, send me a message, connect with me on LinkedIn. The best responses will show up in a follow-up post, because this conversation is bigger than one article.

We're building in public. Let's figure out what we're actually building toward.

Follow the Think Like a Healer series for more on what years of sedentary work does to your body — and how to reverse it.

Mindful Dollar | Nasly Duarte | Doing More With Less

#BuildInPublic #SkilledTrades #AI #TechAndTrades #MindfulDollar #DoingMoreWithLess #ThinkLikeAHealer #FutureOfWork #BalanceProblem

Sources

• Associated Builders and Contractors (ABC) — "Construction industry must attract 349,000 workers in 2026" — abc.org
• Associated General Contractors of America — 91% of firms struggle to find qualified workers
• National Association of Home Builders (NAHB) — 41% of construction workforce will retire by 2031; housing industry labor shortage carries $10.8 billion annual economic impact — nahb.org
• Deloitte & The Manufacturing Institute — 2.1 million manufacturing jobs could go unfilled by 2030; 77% of manufacturers report difficulty attracting workers — deloitte.com
• Academy of Craft Training — Construction will need 1.9 million workers over the next decade — academyofcrafttraining.org
• Skillwork — For every 5 Baby Boomer retirees, only 2 younger workers enter the trades — skillwork.com
• Metaintro — White-collar layoffs in tech/media/finance vs. trades demand outstripping supply, 2025–2026 — metaintro.com
• U.S. Chamber of Commerce — America Works Data Center, industry labor shortage data — uschamber.com
• The Biggest Little Farm (2018) — Directed by John Chester. Available on Netflix, Hulu, and Amazon Prime Video.

Is n8n Dead for Content Workflows?

The Mindful Dollar  ·  AI Explained Simply

Google Just Put an AI Content Engine Inside Your Spreadsheet. Is n8n Dead for Content Workflows?

By Nasly Duarte | Mindful Dollar — Doing More With Less

I need to start with a confession: I almost mass-deleted three n8n workflows this week.

I was organizing my LinkedIn content topics in Google Sheets — hashtags, hooks, post drafts, status columns — and then I saw it. A little purple cross icon appeared with a label I hadn't noticed before: "Drag to fill with Gemini."

I dragged it. And Gemini started filling my rows with content. Not random content. Content that matched my column headers and the patterns in my existing rows. It pulled from the web. It categorized. It wrote draft hooks based on the topics I'd already started.

I sat there staring at it like… wait. Did Google just eliminate half my automation stack?

I want to know if you had the same reaction — or if you think I'm overreacting. Keep reading and tell me at the end.

What Actually Changed (This Literally Just Happened)

Google rolled out a major Gemini update to Workspace on March 19, 2026. The Sheets update is the one that matters for builders like us who plan content in spreadsheets.

Here's what "Fill with Gemini" actually does:

• You set up column headers (Topic, Hook, Hashtags, Post Draft, Status)
• You fill in a few rows manually so Gemini can see the pattern
• You drag down and Gemini auto-populates the rest — pulling from the web, categorizing, even writing draft copy

It's not just autocomplete. It runs a separate web search for each row. It reads your column headers and figures out what data to pull. Google's VP of Product described it as Gemini being able to "figure out how to go find what you need" just by reading the structure you've built.

Available now for Google AI Ultra and Pro subscribers.

My Hot Take: Gemini Replaces the Brain. n8n Is Still the Body.

What Gemini in Sheets Does Well

Topic research and enrichment. If I have a column of broad topics — "Miami construction workforce," "AI in accounting," "contractor licensing Florida" — Gemini fills adjacent columns with trending angles, relevant statistics, and draft hooks. That used to require a separate n8n node hitting an AI API.

Pattern-based content generation. Write three posts in a specific format, drag down, and Gemini generates more in that same pattern. For batching a week's worth of content in one sitting, this is fast.

Zero setup cost. No webhook URLs, no OAuth tokens, no node configuration. It just works inside the sheet you already have open.

What Gemini in Sheets Cannot Do

It cannot publish. Gemini fills your spreadsheet. It does not post to LinkedIn. You still need either a scheduling tool or an automation platform to move content from sheet to platform.

It cannot run on a schedule. Gemini responds when you interact with it. There's no "run this every Monday at 6 AM" trigger. n8n's Schedule Trigger exists specifically for this.

It cannot handle approval workflows. If you want a human review step before publishing (and you should — more on this below), Gemini doesn't offer that. n8n can route a draft to Telegram or Slack for your sign-off before it goes live.

It doesn't close the loop. After a post publishes, n8n can mark the row as "Posted" and add the live URL back to your sheet. Gemini doesn't do post-publish tracking.

Here's Where I Want to Fight About It

I think most builders are overengineering the research step.

If you're paying for Google AI Pro anyway, why are you running a 10-node n8n workflow with Perplexity and OpenAI just to generate topic ideas and draft hooks? Gemini does this natively now, inside the sheet, with zero config.

But — and this is important — I also think anyone publishing AI-generated content straight to LinkedIn without human review is playing with fire.

Where do you land on this?

• Are you comfortable with fully automated post-to-publish pipelines?
• Or do you keep a "Ready" column and review every draft before it goes out?
• Has an AI-generated post ever embarrassed you? (Be honest.)

I keep a human-in-the-loop step because my voice is my brand. But I know builders who skip it entirely and post three times a day on autopilot. I want to hear what's actually working for you.

The Stack I'm Landing On (Tear It Apart)

Here's my current thinking. Tell me what you'd change:

Layer	Tool	Why
Topic research & draft generation	Gemini in Sheets	Faster, zero config, web-grounded
Human review & editing	Me, in the same Sheet	Edit Gemini's drafts, mark rows as "Ready"
Scheduled publishing	n8n	Reads "Ready" rows, posts to LinkedIn on a schedule
Status tracking	n8n	Updates row to "Posted," adds the live post URL

Gemini replaced the research and first-draft nodes in my n8n workflow. It did NOT replace the scheduling, publishing, and status-tracking nodes.

Gemini is the writer. n8n is the operations manager.

Less nodes. Less complexity. Same output. Maybe better output, because Gemini's web search is pulling fresher data than a cached AI prompt would.

The Bigger Pattern (This Isn't Just About Content)

This is something I keep seeing as AI tools mature, and I think it matters for every builder reading this:

The generation layer is getting commoditized. Every platform is adding AI content generation natively — Google Sheets, Notion, Canva, even email clients. The thing that still requires you to build something is the orchestration layer — getting the right content to the right place at the right time with the right approvals.

That's where n8n (or Zapier, or Make, or Claude Code) still earns its keep.

But here's my question for the group: how long until Google adds scheduling and auto-publish to Sheets too? If Gemini can already research, draft, and organize — publishing feels like it's next. And if that happens, does n8n lose its role in this workflow entirely?

I genuinely don't know the answer. I'm curious what you think.

What Should I Doing Next (And What I Want From You)

Should I simplify my n8n workflow this week. Remove the OpenAI research nodes and let Gemini handle topic enrichment directly in my content calendar sheet. My n8n setup will get leaner — it just reads, publishes, and updates.

Doing more with less. That's the whole point.

Next week, I'm building my full n8n workflow setup — screenshots, node configs, and the Google Sheet template. So you can use it or tell me what's wrong with it.

But before that, I want to hear from you. Seriously. Drop a comment, reply, DM me — whatever works:

1. What does your content automation stack look like right now? (Sheet + n8n? Notion + Zapier? Something else entirely?)
2. Have you tried "Fill with Gemini" yet? What was your first reaction?
3. Human review or full autopilot? And has skipping review ever burned you?
4. Hot take: will Google eventually add scheduling and publishing directly to Sheets? Or is that a bridge too far for a spreadsheet app?

The best answers are going in next week's post. I'll credit you and link your profile. Build in public means building together.

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Connect with me on LinkedIn — I'm documenting this entire workflow evolution .

Mindful Dollar | Nasly Duarte | Doing More With Less

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#BuildInPublic #n8n #GeminiAI #GoogleSheets #ContentAutomation #LinkedInStrategy #MindfulDollar #DoingMoreWithLess