Showing posts with label ai. Show all posts
Showing posts with label ai. Show all posts

Saturday, March 7, 2026

The Great AI Arbitrage: making a killing before your client wises up

There is a silent heist happening in the billable hours of every major software agency. We’ve entered a Golden Hour - a brief, high-stakes arbitrage window where the cost of production has cratered, but the price tag remains frozen in 2022.

History is littered with these windows. They are defined by Knowledge Asymmetry: the gap between what a client thinks it takes to build a product and the time it actually takes, using a magical new tech.

We are living through the Agentic AI version of this playbook. In the time it takes a client to finish a discovery meeting on Teams, an agent has already drafted, tested, and hallucinated its way through the first 40% of the codebase. The agency is billing for the month; the machine finished before the coffee got cold.

Here are the most iconic historical parallels to the Great AI Arbitrage:

1. The Gutenberg Gap: The Scribe vs The Printing Press

In the 1450s, a hand-copied Bible took a scribe about a year to complete. The price reflected 12 months of high-level professional labor.

The Tech: Johannes Gutenberg’s movable type press.

The Arbitrage: Early printers were notorious for trying to make their books look exactly like hand-copied manuscripts. They used the same ligatures, the same layouts, and sometimes even had artists hand-illuminate the first letters of a printed page. They charged scribe prices for a product that was essentially mass-produced. 


2. The Master Gunsmith vs Interchangeable Parts

In the early 1800s, if a part of your rifle broke, a master gunsmith had to hand-forge a unique replacement. You paid for that master craftsmanship.

The Tech: The transition to interchangeable parts (mass production); machines began stamping out identical components.

The Arbitrage: Government contractors and factory owners keep billing for "fitting and filing" (the manual labor of a master gunsmith) long after the parts were being stamped out by low-skill laborers using jigs. 



3. The Master Machinist vs CNC Programming

The CNC (Computer Numerical Control) lathe transition of machine shops during the 1980s is the most direct ancestor to the Agentic AI shift in software development. It wasn't just a change in tools; it was a total transfer of power and a massive, hidden profit engine.


Here is the deeper breakdown of what happened:

The "De-skilling" of the Master Machinist

Before CNC, a master machinist was a craftsman with specific knowledge. They didn't just turn handles on the lathe; they had "the feel" for how metal reacted to heat and speed. This was deep, learned knowledge - it couldn't be easily written down or taught to someone else, and it gave those machinists immense leverage over shop owners.

  • The Tech: G-code and microprocessors made that deep knowledge redundant. The new machine could replay its tool-paths perfectly every time, regardless of whether the operator understood the physics of the cut.

  • The Arbitrage: Shop owners realized they could buy one $80,000 CNC lathe (the price of about 12 manual lathes in 1981) and hire a "button-pusher" CNC operator at 40% of the Master Machinist's wage to run it.

  • The AI Parallel: Today, an agency can use Claude Code to replace a team of senior developer SMEs on a complex legacy project with one AI "prompt-pusher" keeping a zombie legacy project on life support.

The "Ghost Labor" Billing Model

This is where the real money was made. In the 1980s, the market rate for precision machining was anchored to the labor of the machinist.

  • The Old Reality: If a complex aerospace part took 10 hours to hand-mill, the client was quoted for 10 hours of a senior machinist's time.

  • The CNC Reality: The machine could churn out that same valve in 45 minutes. Shop owners would literally hide the humming CNC machines out the back, and keep the master machinist hovering out the front for the clients to meet.

  • The Play: Shops didn't tell the clients. They continued to bill for the 10 hours.

  • The Result: Profit margins jumped from a standard 20% to a staggering 500% on certain parts, just by exploiting the client's ignorance of the new CNC speed increases.

The Knowledge Monopoly

Historian David Noble argued that CNC machines weren't better when they first came out - manual machinists were often faster for one-off parts. However, management pushed CNC primarily because it removed the knowledge monopoly from the workers.

  • With CNC, the knowledge moved from the shop floor to the office floor.

  • It allowed management to dictate the pace of work without the machinist ever needing to be consulted.

The End Game

The end of the CNC arbitrage window provides a brutal preview of what happens when a secret productivity leap becomes a baseline industry standard. When the knowledge asymmetry vanishes, the pricing floor doesn't just sag, it collapses.

Once CNC machines became affordable and CAD/CAM software became user-friendly, the secret weapon became a commodity. Job shops that once made a killing started undercutting each other just to keep the spindles turning. Prices for standard parts plummeted by 60-80% in a few years. The bespoke premium evaporated because precision was no longer a rare skill - it was a machine setting.

The ultimate price-killer was when the giants - the Boeings and Fords of the world - realized they didn't need the middleman anymore. As the tacit knowledge of the shop floor was codified into G-Code, the 'craft' became a 'file' ... and files are infinitely portable. Clients realized they could hire a CNC programmer/operator to run the same machines in-house for a fraction of the agency's markup.

External shops were forced to drop their prices to Cost + 10% just to prevent their clients from in-sourcing the work entirely. The only shops that kept their high margins were the ones that made a pivot.

  • The Pivot: If you were just "making parts", you were a commodity. If you were providing "Aerospace-Grade Quality Assurance and Material Traceability" you could still charge a premium. You stopped selling the shaping of metal and started selling the certainty of the result.

  • Master Machinists became Manufacturing Engineers. They traded their manual "feel" for process optimization. A shop might have 5 CNC machines, but they still needed someone who understood the physics of metallurgy to ensure those machines didn't destroy $50,000 worth of carbide tools in a single afternoon.

  • The AI Parallel: In 2027, writing code will be a commodity. The thing clients will pay for in the future is functional and architectural assurance... did you build the right thing, and build the thing right?

The Generalist Dev Pivot: Breadth Over Depth


Software developers focus will need to shift upwards, onto software architecture, business analysis and the AI tools themselves - using AI tools to drive more productivity for business.

With this shift comes the need for a breadth of knowledge rather than a depth of knowledge. Specialist developers who continue to focus narrowly on just one framework / platform will slowly lose their knowledge monopoly to a machine that never sleeps, doesn't take coffee breaks and doesn't charge for overtime. 






Thursday, February 26, 2026

The Zombie App Apocalypse

"Talk is cheap. Show me the code."
- Linus Torvalds, 2000

"Code is cheap. Show me the users."
- Me, 2026


The Death of the Dev Moat

In 2023, if you had a bullshit idea (like a social media app for cats), you still had to find $50,000 or 6 months of your own life to build a prototype. 

That cost acted as a bullshit filter.

In 2026, that filter is gone. Code has become cheap, and the bullshit has become infinite. If you can’t find a single user before you hit 'Generate' you haven't built a tool; you've just automated the process of adding to the internet's infinite landfill.

We’ve been here before. In 2000, millions of bullshit apps came out of Microsoft Access and VB6. For the first time, a department manager could drag-and-drop a few components, click a wizard, and 'build' a billing system. It felt like magic, but it mostly resulted in a million fragile .MDB files on desktops and a nightmare to maintain. Today, we aren't dragging buttons; we're vibe-coding entire repos. The tech changed, but the delusion remains: just because you can build it doesn't mean you should.

Zombie Apps

With tools like Claude Code or DeepSeek-V4, a non-technical founder can go from napkin sketch to a hosted, functional web app in a single afternoon. Due to this, we're in a supply-side explosion of Zombie Apps - AI generated apps with no users - beautiful, functional, and completely hollow. Because the cost to maintain a web app with a negligible userbase is less than a cup of coffee per month, they can stay online forever, creating a graveyard of functional software that no one ever logs into.

We'll end up with a long tail of these apps that never get used. Think of it as the YouTube-ification of software. 90% of all uploaded videos on YouTube never break 1000 views, and 25% get exactly zero views. A vibe coded SaaS is the same... a perfectly rendered concert performed in an empty stadium. 

Building an app may be almost free, but getting someone to care about it has never been more expensive. The truth is that with a SaaS, the code has never been the most important part, it's always been "product/market fit", and the ability to grow an active community of users who need your product. There is still a massive market for a focused SaaS that solves a real problem, but in 2026 shipping it isn't the victory - growing a real user base is.




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Saturday, February 14, 2026

The Trash-to-Cash pipeline: monetizing your garbage


Oshkosh and their AI driven garbage trucks

At CES 2026, Oshkosh Corporation took the stage not just as a vehicle manufacturer, but as a data powerhouse. Their flagship innovation for the "Neighborhood of the Future" is an AI-Powered Contamination Detection system integrated into their refuse and recycling fleets.

The stated goal is noble of course - "Landfill Diversion" - by using advanced cameras and on-the-edge AI processing, these trucks scan every piece of waste as it falls into the hopper. The system identifies contaminants (like a plastic bag in the paper bin or a greasy pizza box) and uses onboard GPS to map that issue back to your home address. The city then sends you a friendly, automated SMS educating you on your recycling sins. It’s efficient, it’s green, and it’s powered by the same tech used in autonomous combat vehicles.

Dystopian twist via a software upgrade

As every developer knows, hardware is just a shell for the software running on it. While the truck currently only looks for plastic bags, theoretically a software update could turn it into a collector of household product consumption data.

Imagine a local cash-strapped city council realizing that their recycling program is a cost center, but their waste data collection program is a cash goldmine. With one firmware push, the AI models are updated to recognize not just cardboard or plastic but specific brand logos, product SKUs, and consumption volumes. Your bin is no longer just a waste dump; it’s a physical record of your household's consumption patterns ... sitting on a public curb with zero legal expectation of privacy.

Monetizing the data

Once the AI is brand and product aware, it becomes a tool for monetization via these potential goldmines of garbage:

  • Retail Data: Why spend millions on broadcast ads when you can buy a report from the local council showing exactly which households are throwing out competitor brand's packaging? A cereal company could target "Kellogg's households" with high-precision mailouts, product samples, or localized digital ads.

  • Health Profiling: By detecting medicine bottles and food packaging, AI can build a neighborhood health profile. It'd be highly valuable to insurance actuaries and pharmaceutical giants, who would love to know the "wellness score" of a specific zip code.

  • Health Insurance: The AI detects an above-average volume of beer cans at your address. Does your health insurance premium go up next year?

  • The Green Tax: Left-leaning councils could move beyond flat waste fees to "Environmental Impact Taxes" based on the volume of non-sustainable brands or products detected in your garbage. Did you buy a pack of ribeye beef steaks this week, you carnivorous bastard? Then you'll need to pay $10 towards reversing the deforestation of the Amazon.

  • Fast Food Giants: Mapping market share hotspots by suburb... "We only have a 20% market share in this zip code; let’s put a new billboard up."


Your bin is the new privacy battleground

AI powered garbage truck technology means that the contents of your bin are eventually going to be opened up to the local council. 

The next time you hear a garbage truck cruising by at 6:00 AM, don't get annoyed by the noise; think about the sensors scanning your bad habits, one pizza box at a time... ;-)


References
The 2025 Deepnest Report: What Waste Data Revealed About Recyclability
Turning Trash into Transparency: Nawa's AI-Driven Vision for Global Recycling
Robotic Collection and AI-Powered Contamination Detection Spotlighted at CES 2026
Dallas to install AI cameras on garbage trucks



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Friday, February 6, 2026

United Airlines Chatbot Fail

AI Agents hooked up directly to the customer over SMS text messaging are a disaster waiting to happen. 

A chatbot bug had real world consequences for a United Airlines customer last week - their booking got cancelled by mistake.

The United Airlines AI Agent gets it wrong over text message

The chatbot presented two options:

A) Yes, cancel & get a refund
B) No, not ready to cancel


Pretty simple you'd think, but when the customer replied B, it completely lost the context of the command and went ahead with A, the opposite option.

So the lesson here is don't trust a chatbot to know what its doing at all, and for anything important, just use the company's app or website directly. If its a complex issue, call them up and talk to an actual employee... it will probably save your time in the end.


The simple text based interface was used for many years before windows & mouse interfaces became dominant during the 1990s. Unfortunately some AI agents aren't capable of getting a basic text interface like this correct yet.

An old school text based menu interface


References:
https://www.reddit.com/r/unitedairlines/comments/1qrrvfd/am_i_stupid_for_did_i_just_get_screwed_by_the_ai/
https://www.slalom.com/au/en/customer-stories/united-airlines-gen-ai
https://www.cio.com/article/3969476/united-airlines-ai-strategy-the-airline-that-makes-decisions-fastest-wins.html


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