AI Content in Web Search Results: Your Fault and Controlling Content Is Just Too Hard
August 4, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
I spotted a write up that surprised me. The BBC or BeeB published “Some People’s Chats with Claude AI Made Publicly Available Online.” Since I believe everything I read on the Internet, I will operate as if the Beeb is delivering actual factual information.
The article states:
Hundreds of user conversations with Anthropic’s popular artificial intelligence (AI) chatbot Claude were found to have been available to essentially anyone using Google or other web browsers. Links to the chats, some of which included personal and work information, would show up if a user of a search engine like Google used a site-specific search term. The searches showed Claude chats for which a user had decided to “share” a link had been saved by search engines like Google, leaving them accessible to the broader public.
Two members of big AI tech leadership find the idea of editorial responsibility unacceptably stupid. Thanks, MidJourney. Good enough.
Now who is to blame? Anthropic’s position about sharing is similar to OpenAI’s; that is, the user is responsible for any sharing. And what about the Google? The Beeb offers this statement from that estimable firm:
A spokesman for Google made clear to the BBC that the company does not control “what pages are made public on the web,” saying instead that action comes from websites. “We give site owners clear controls to decide whether pages can be crawled or indexed, and we always respect those directives.”
I love this approach to smart software and indexing, often without permission, content accessible via the Internet. The users are to blame. But for Google, it is abundantly clear that despite more than 100,000 full time equivalents, the firm is not able to control what pages are made public on the web. I include a site called Altenen in my lectures for LE and intel professionals. This is an interesting site, and you may want to check out the firm’s tutorials and for-fee information about credit and bank card theft. Google just can’t control what pages are made public on the web if the Beeb’s story is spot on. Oh, I locate the Altenen outfit via a Google search. I would not advise providing this site name to one’s teeny boppers.
I was disappointed that the Beeb did not point out that more than 80 percent of online queries flow to the Google. And in Denmark, the GOOG hits 99 percent of the search traffic. Content in Google becomes the content from a couple of billion people. Yep, no control.
Now I want to shift gears to a write up in Ars Technica. This report is “It’s Official: EU Will Force Google to Share Search Data and Open Up AI on Android.” I want to direct attention to the subtitle; to wit:
Google says these changes could endanger user privacy and security.
That’s clear. The EU will take steps for Google to share search data over which it has no control. Furthermore, if Google were to be required to share its data, the chief problem would be “user privacy and security.”
As a dinobaby, I am growing weary of the behaviors of the big tech outfits. The “it’s easier to say I am sorry than ask for permission” combined with the “move fast and break things” is for me a matter of concern. Others find the behavior beyond reproach. If there’s a problem, it’s my fault and yours. And whatever we do, we can’t control content.
Think about that for a moment.
Stephen E Arnold, August 4, 2026
Bad Agents Means Bad Management. Period.
July 23, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
Venture Beat, a quite unusual online publication, published “Enterprise AI Is Entering An Evaluation Gap: Agents Are Gaining Autonomy Faster Than Companies Can Verify Them. ” Is this a write up in the old Amazing Tales magazine or a serious analysis of people who are looking for a way to cut expenses, increase revenue, and land a big bonus payday? The answer: The article is a business and technical analysis prepared by a hard working professional with a track record of covering fast-changing subjects. Therefore, let’s take a look at the write up.
The good news is that software agents armed with “intelligence” haven’t become fully autonomous… yet. What is happening is that enterprise AI teams are giving their AI agents more freedom as their confidence in automated testing is collapsing. Is this one of those inconvenient paradoxes?
About 50% of enterprises have deployed an AI agent or LLM that passed internal evaluations, but they are still failing on the customer facing side. The logical thing to do would be to slow automation but 66% of respondents to a VB Pulse survey said they deployed some production without human oversight. Autonomy is coming sooner than humans are reviewing it. With layoffs and employees dropping out of “real” work, I am not sure that there are enough motivated, informed humans to review agentic software. In my experience, generating code really fast is a core semi-competency.
The article states:
“It also fits a broader thesis that will be explored at VB Transform 2026: enterprises ship agents first, while the control layers around identity, evaluation, cost, context and orchestration are arriving later. The next year will be a retrofit cycle, with buyers shifting budget toward the systems that make agentic deployments governable and dependable.”
Is an agent ready to be turned loose because it completes a task in one successful run? Sure it does. The goal of AI is to achieve repeatable results so that customers don’t experience any hiccups on their end. Every failure should be a regression test to make the AI agent better. Somehow American Airlines garbled by email and displayed an old phone number for me. I called the special number for AAdvantage members. I told the AI agent I needed to update my account. The system did not understand “update my account.” After five repeats telling me to state what I wanted to do, the smart software said, “If you want us to call you in 45 minutes, press one.” I did. In fact, I went through this drill several times. Did the smart software agent get someone to call me? Nope. I wrote a handwritten letter to the leadership of American Airlines, but I don’t think anyone will contact me. The agentic system worked at least once. Therefore, the system is perfect for paying customers.
I don’t think there are enough human hours to review every AI agent action, but:
“w-risk actions such as drafting internal summaries or categorizing documents can tolerate broader autonomy. Financial transactions, customer communications, code deployment, access-control changes and data deletion need stricter thresholds, repeated consistency tests, policy checks, rollback mechanisms and clear human escalation paths. The risk isn’t evenly distributed by company size, either. Larger enterprises — those with 2,500 or more employees — are moving toward zero-human deployment fastest, at 70% versus 64% for smaller companies, and they’re also shipping more agents that go on to fail a customer, at 54% versus 48%.”
I think this means that management must manage agents. The customer centric enterprise teams need to get their acts together and create an evaluation system so bad agents are not foisted on paying customers. Will that happen, Venture Beat?
Whitney Grace, July 23, 2026
BAIT Biting 101: Apple Chomps Sinks Its Teeth into OpenAI
July 14, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
These BAIT outfits are indeed remarkable. In my lingo, as you may recall, means “big AI tech.” In my lectures, I like to point out that these companies are becoming increasingly similar. They have realized that the convergence creates the idea opportunity for one big winner to emerge, a second place finisher with a shot at about 60 percent of the revenues of the winner, and the rest of the BAIT outfits fighting over remaining revenue. Therefore, folks, its cage match time.
“Apple Sues OpenAI Alleging Trade Secret Theft, Says Scheme Was at Every Level” reports:
Apple on Friday [July 10, 2026] sued OpenAI in federal court in Northern California, alleging trade secret theft, saying that the artificial intelligence lab took the iPhone maker’s intellectual property in order to develop its own consumer hardware.
How did this work? Did busy little software daemons prowl through Apple’s digital information? Did OpenAI’s smart software launch a thousand and one agents to suck down any content connected to the expanded term “Apple”? Did Sam AI-Man show up in the Apple parking lot, handing out offers to happy Applers?
Nope.
Apple alleged that OpenAI’s hardware chief, Tang Tan, who is a former Apple vice president, has directed Apple employees interviewing at OpenAI to share Apple secrets as part of the interviewing process. Tan is named as a defendant in the suit. “He has directed job candidates still working for Apple to bring ‘actual parts’ from Apple to their interviews for ‘show and tell’ sessions in which he and his team at OpenAI can elicit still more Apple confidential information,” Apple said in the filing. Apple alleged that OpenAI coached departing Apple employees in how to evade security processes when leaving the iPhone maker, and that Chang Liu, a former employee who joined OpenAI, stole an Apple laptop. Liu is named as a defendant in the suit.
Well, that’s subtle. a human thought up the ploy. Information flowed at the humanoid to humanoid level. Tips and tricks to sidestep “security” flew like a hungry turkey (yes, turkeys eat apples, but turkeys do not climb apple trees. Like job hoppers from Apple to OpenAI, the turkeys just go for easy pickings in my opinion).
Okay, I want to make sure I understand this. Apple found itself the defendant in some interesting knowledge transfer litigation. Examples, include the Masimio medical device matter, the VirnetX dispute, the University of Wisconsin (go badger Alumni Research Foundation), and some others. I am not lawyer, so my recollection may be off base. Please, keep in mind that I am a dinobaby and averse to doing legal research.
Assume that one of these instances of Apple taking another firm’s intellectual property is true. Do you find it interesting that Apple is greatly aggrieved that a fellow BAIT outfit is asking potential employees a question like this: “Okay, Sally, do you want some oat milk for your coffee? No, okay. Tell me what expertise you have and include a couple of simple examples?”
Yeah, HR and interviewers never ask this type of question. Let’s stick with the oat milk interrogatory. That’s much more useful in today’s go fast and break things world. Am I correct?
The CNBC story concludes:
Apple is seeking damages, injunctions, and an order to force OpenAI to stop using its trade secrets.
Okay, but I have one question: What’s a trade secret? I usually ask questions when I know the answer or I have a reasonable sense of the answer. Does that mean a person who answers my question has revealed a secret when I already know the answer or have a good idea of the answer?
“That’s not the point,” squawks a legal eagle. I agree. I don’t want to be baited by a BAIT. The unfolding legal drama will be interesting to watch. Snacking on apples in a court may not be permitted.
Stephen E Arnold, July 14, 2026
What Happens When AI Self Improves?
July 1, 2026
Give up? The answer is, “Whatever those with access to the AI system’s training sets, threshold settings, and software wrappers.”
Humans have driven AI’s development since the onset, but that might be about to change says Anthropic in the press release: “When AI Builds Itself: Our Progressive Toward Recursive Self-Improvement And Its Implications.”? When AI can autonomously drive towards improvement it is called “recursive self-improvement.? It could be closer on the horizon than expected.? When the 2026 benchmarks for Anthropic are measured against 2021-2025, engineers are delivering 8 times more code each quarter.? What does this mean? Buckle up. The article asserts:
“The technical trends discussed in this piece suggest that AI systems are going to become much more capable in coming years. These trends have huge implications. AI that can build itself would be a major development in the history of technology—one that could bring enormous good for the world in science, healthcare, and beyond. But full recursive self-improvement also might increase the risks of humans losing control over AI systems. If systems are capable of fully building their own successors, the ways we secure them, monitor them, and shape their behavior all grow much more important.”
Claude writes the majority of Anthropic’s code. In 2025, Claude ran code instead of suggest it for engineers to copy and paste.? ? The algorithm is also getting better at research. For example, on Claude Code sessions, when the the algorithm is asked to find mistakes, it can detect when engineers veered off course
If Claude is programming Anthropic, do humans have a role anymore?
“The evidence suggests that the human role is narrowing at each step in the AI development process. Once human- and AI-authored code quality reach parity, humans will stop writing code entirely, and shift to only reviewing it. But if they can’t review code as quickly as Claude can generate it, human review will become the bottleneck to AI development. Similarly, once Claude can run experiments, the question shifts towards ‘Which of these experiments is worth running?’ Put simply: the doing (i.e., writing the code, running the experiment, producing the result) now costs almost nothing in human time, even if it still has costs in compute. An area of human comparative advantage, for now, is research taste and judgment, including choosing which problems matter, which results to trust, and when an approach is a dead end.”
There are possible futures where this particular trend could stall, AI could see compounding efficiency gains, or the algorithms become entirely capable of full recessive self-improvement.
What are we going to do? The write up says:
“If it were possible to effectively slow the development of this technology to give ourselves more time to deal with its immense implications, we think that would likely be a good thing. But if a slowdown simply lets the least cautious actors catch up technologically, it could leave everyone less safe. Without a global coordination mechanism, companies and governments will have to make difficult decisions about safety while under competitive and geopolitical pressures.”
Don’t let the bad actors get ahead. They’ll take advantage of everyone if they do. We guess the only thing to do is push forward and hope for the best while wearing white hats…maybe gray.
Whitney Grace, July 1, 2026
AI Ai Aiiii! The Sound of Coffee Pain
June 16, 2026
The “AI failed” information continues to appear in my newsfeed. Most we ignore, but due to the ubiquity of an outfit called Starbucks (and the “bucks” word is germane to the business model for hot water sales) jumped into the output of a Thermoplan AG device. How did that dip into the warm bath of AI marketing work out?
That vendor of hot water is about to toss out the AI the firm. The State Of Brand explains the details in the article, “Starbucks Sold Its AI On A 99% Accuracy Number. Nine Months Later, 11,000 Stores Are Counting Milk By Hand.” Starbucks installed an AI tool called Automated Counting, designed by NomadGo, in September 2025. It was described as a way to relieve employees from mundane tasks:
“A “unique synthesis” of on-device computer vision, 3D spatial intelligence, and augmented reality. Wave a tablet at a shelf of milk jugs and syrups, and the count appears, validated in AR. Starbucks’ chief technology officer framed it as freeing partners from a time-intensive task so they could get back to making drinks and connecting with customers.”
It was removed in May 2026. The job for AI was “simple” like most work processes analyzed by “let’s increase margin” crazed MBAs and flexible bean counters. The system was supposed to count milk cartons. Eliminating manual counting would free up Excel projected hours. Presumably the time would be used for more productive activities like turning out more expensive hot water and writing in physician scrawl a customer’s name on a cup with a mermaid image.
How did that AI handle the simple job? Yeah, not very well. As anyone who has worked in a busy foody type of environement, when the rush arrives, life is pretty crazy. The system worked great in a store with a tidy, clean shelf, decent lighting, controlled SKUs. When caffeine semi withdrawl Type As crowd the counter, smart software did not work too well.
No modern “leadership” admits mistakes. Starbucks didn’t consider it a failure instead Automated Counting is labeled as more of a learning experience than anything. It’s a carefully crafted statement from Starbucks HQ to output what I call smarmy talk. Yeah, I interpreted the AI counting milk anecdote as another memorable moment for an outfit which sells hot water.
Does this AI moment prove anything? Yep:
- Real world actions are different from those demonstrated in a controlled setting.
- Modern leadership believes in Tooth Fairies, silver bullets, and the outputs of BAIT acolytes (BAIT is our lingo for big AI tech outfits).
- Probability is good for some things but not for other applications.
My view is that modern management is gullible and believes the the next big thing will wave a magic wand over some business problems. News flash: There is no tooth fairy.
Whitney Grace, June 16, 2026
Good Enough AI May Not Be Good Enough
June 4, 2026
Rest Of World explains something that we all knew: “The Agentic Divide: Why “Good Enough” AI Isn’t Enough To Survive The New Economy.” What this means is that many AI chatbots are being released and some are better than others. That is to be expected, but no one expected there to be chatbot inequality and its economic consequences.
Chatbots are expected to take on monotonous tasks thus freeing up employees for other work. A problem, however, is that most chatbots still fail at basic facts and Big Tech companies are still launching agents to handle more complex tasks. Here is what will happen:
“As AI agents become more integrated into the economy, companies and entities that deploy them will benefit disproportionately compared to those that cannot, Nick Srnicek, a senior lecturer in digital economy at King’s College London, told Rest of World. ‘We will see new inequalities of access, scale, quality and trust: divides between those who have agents and those who don’t; those who have good agents and those who have bad agents; those who have many agents and those who have few agents; and those who can trust their agents and those who cannot,’ he said.”
China and Singapore apparently introduced frameworks to regulate AI to focus on accountability and safety. Chinese local governments are boasting single-employee companies that rely on AI chatbots. India is even embracing AI to cut costs and scale quicker.
Better chatbots are already advancing companies, saving them money, and advancing in the markets. Another problem is that if governments and companies rely on chatbots, they can be canceled at anytime without notice. There are also security concerns:
Matthew Sharp, a research affiliate at the Oxford Martin AI Governance Initiative [said]:
‘The same infrastructure can become a surveillance layer if the data flows, defaults, and oversight are wrong,” Sharp said. “The safeguards around consent, purpose limitation, auditability, and political independence would need to be real, not merely architectural.’”
My fear is that “good enough” is the new standard of excellence. A race to dumbing down. Outstanding.
Whitney Grace, June 4, 2026
BAIT Does Not Attract the UK Fish
May 25, 2026
Is American big tech becoming a bit of a problem in the UK? Probably not, some of the BAIT folks would say. BAIT is my jargon for big AI tech. Perhaps “attitude” may be more of an issue? The do-what-we-tell-you approach may be unpalatable in some countries. After working in the UK on a number of projects over the years, in my experience saying “excuse me” when someone steps on your shoes indicates a different mental approach that stepping on a person’s toe and snarling excuse me at the individual whose 10 pound shoe shine has been besmirched.
Thanks, Midjourney. I did not know knees could speak. Good enough, of course.
I noted a BBC report a couple of weeks ago. The story “Millions’ Of Pounds Saved By Replacing Palantir Tech In Refugee System” suggests that the Palantir Technologies Tolkien infused intelware was not working for The Homes for Ukraine. That group replaced Palantir’s seeing stone with software designed by its own team. What began as a free service morphed into a US government procurement scale invoice.
Instead of paying the bill, the Ministry of Housing, Communities, and Local Government (MHCLG) said its new in-house system was equipped to handle high standards of security and was more flexible. The BBC pointed out that is was proud to have supported the project and helped to resettle 157,000 refugees displaced from the Russia “special operation.” The decision to step away from Palantir was celebrated:
“That message may be particularly welcome to those who have criticized Palantir and its contracts across UK public services – including with the NHS, the Ministry of Defense (MoD), the Financial Conduct Authority and 11 police forces. Some argue the firm’s success is because its tech is badly needed and works well. But others contend Palantir’s involvement with US immigration enforcement and Israel’s military, as well as the beliefs of its two most prominent founders, make it an unsuitable partner. There are also concerns the UK is relying too much on large US tech suppliers.”
On May 22, 20266, the Guardian online service published “Palantir Hits Back at Sadiq Khan after £50m Contract with Met Police Blocked.” The article reported:
Palantir has accused Sadiq Khan of “putting politics above public safety” after the London mayor blocked its £50m contract with the Metropolitan police in a move that has also led to tensions inside Labor over its involvement with the US tech company. Louis Mosley, who heads Palantir in the UK and Europe, accused Khan of politicizing procurement after he rejected a two-year deal for Scotland Yard to use AI to process intelligence in criminal investigations, as first revealed by the Guardian. Mosley said: “What Londoners value is not being mugged, not being raped by a serving police officer.”
According the the article, Palantir has been raising the hackles of some in the UK. Here’s how the Guardian presents Palantir’s sales suavity:
Last year, when the company’s chief executive, Alex Karp, was challenged that “Palantir kills Palestinians” in Gaza, he said: “Mostly terrorists, that’s true.” Khan’s stance puts him at odds with the UK government which has a £330m NHS England deal with Palantir and a £240m deal with the Ministry of Defense.
Instead of beating the anti-BAIT tambourine, the article presents this:
Ministers say they are aware of the need for less reliance on foreign AI companies as the technology becomes increasingly applied in the delivery of public services. Kyle said: “We need to have more British AI companies that can do those kinds of things, which is why I’ve taken equity stakes in British AI firms and British tech firms, so that we can scale them up much, much faster.”
I think this is part of the “pardon me” offered by the person who is looking at a ruined shoe shine. The polite phrase does not mean, “Hey, you baseball-cap wearing American, I am at fault.” Nope, the excuse me means that the rude oaf is a social menace. But it sounds nice, doesn’t it?
Stephen E Arnold, May 25, 2926
Synthetic Data from Synthetic People: What If One Asks about a Topic Not in the Training Data?
May 13, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
At lunch yesterday with another dinobaby, one of the topics we kicked around was, “Why are businesses struggling to use AI in a way that does not cause problems?” The individual with whom I dined has more grandchildren than I. He was concerned that the business processes were speeding up. His grandchildren accept mobile devices, video content, and the velocity of their lives as “normal.”
“What does this mean for them? What does this mean for business going forward?” he asked.
I said, “Speed is an issue.” He looked at me glumly. I looked at him glumly.
I thought about this quite successful individual’s dual concerns: Business and grandchildren when I read “Market Research Is Too Slow for the AI Era, So Brox Built 60,000 Identical Digital Twins of Real people You Can Survey Instantly, Repeatedly.” The write up states:
Brox, a predictive human intelligence startup, recently announced a strategic funding round following a year where they reported 10X revenue growth. Their proposition is as ambitious as it is technical: the creation of a “parallel universe” populated by 60,000 digital twins of real, living human beings and their entire demographic profiles and consumer preferences, allowing enterprises to run unlimited experiments in hours rather than months.
The article adds:
The company, currently a lean 14-person operation, is positioning itself as the antithesis of the “insane” research industry. By replacing statistical models with behavioral replicas, Brox aims to transform how the world’s largest banks and pharmaceutical giants anticipate human reactions to high-stakes global and market-shifting events, or narrow, targeted product releases and personnel news, and everything in between. The kinds of surveys and specific questions that Brox asks its digital twins are completely open-ended and can be customized to fit any conceivable business customer’s use cases and goals.
Now back to the AI “struggle” some businesses face while at the same time young children just flow with the artefacts available to them, their parents, and their schools.
Businesses struggle because, by definition, they usually operate on procedures and methods discovered over time. When time is zipping along at hyper speed, an existing business is at a disadvantage. AI requires change, and implementing AI without “understanding” its nuances can lead to caution. Caution means going slow. Too bad, however, because the AI augmented express is moving faster.
Thanks, OpenAI. At least you were working when I requested an image. MidJourney and Venice.ai were not working for me.
The “gap” creates the grandfather’s anxiety about businesses and his grandchildren. Will IBM’s new AI powered data base administrator really “work” better than the flawed, expensive human variety? That’s a tough question to answer. Will my lunch partner’s grandchildren have “real jobs”? Answering these questions correctly seems to be difficult.
The story about AI instant surveys and digital twins blends the business question with the grandchildren question. For a traditional research company, like the old IP Sharp-type of outfit, this Brox story sounds a klaxon. Like it or not, Brox is likely to be just one of many New World Order research firms. Obviously the outputs will be faster than old-fashioned survey methods. My hunch is that these NWO outfits will be cheaper at first and then once the competition has been decimated and the funding sources complain, the rates will go up. But the speed is the fentanyl. Instant, repeatable surveys: How does an old-school market research firm compete?
Consider the jobs question. Let’s assume that one of my lunch mate’s grandchildren wants to be a social science/market researcher. The old-fashioned method is a case study in a text book. The better method is the AI way. It is clear that the grandchild who gets hired or who starts her own AI-powered market research firm is going to embrace the speed and repeatable approach.
Now let’s go back to the question I was asked at lunch, “Why are businesses struggling to use AI in a way that does not cause problems?” The answer is that the speed with which AI moves leaves people at the train station watching the lights of the last car fade. Those who are on the train or in the AI flow are not disoriented. In fact, the use of AI and digital twins is normal, logical, and obvious. This is bad news for organizations using AI. Something like 85 percent of businesses have AI and are using it internally. Yet only five percent, if I remember correctly, are pushing it out to the paying customers. Anxiety forces a conservative approach. Conservatism means a slower pace. Ergo. The speedy are in a better position to gut the old-fashioned outfits.
What if the digital twin approach to research is wrong? The answer is, “Rerun the research and try again.” The result, in my opinion, is more of the “good enough” result or “close enough for horseshoes.” Speed blurs some details. Therefore, one has to adapt to a world in which “good enough” is “excellent”.
Is there a fix? Nope. AI is another destabilizer of what dinobabies like me perceive as the optimal way to run a business and assist grandchildren. Managing AI is going to be a needed skill for businesses and parents. Developing that expertise is going to be a process.
What happens if a survey on a topic not in the training data is surveyed? Yeah, think good enough. I think that’s why my friend and I just looked at one another over our salads … glumly.
Stephen E Arnold, May 13, 2026
Modern Life Now: Efficiency without Context
May 6, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
I don’t often read a book or an essay that says to me, “Think about this.” The author’s words might be a juiced LinkedIn post with truisms that will change the world. Most of the material I read and, on occasion, listen to as a podcast just drives an asphalt spray coating machine over a road I know quite well.
Then, there’s a good one.
I read “The West Forgot How to Make Things. Now It’s Forgetting How to Code.” The essay is chock full of interesting titbits of information. One example is a compound necessary for the production of US style nuclear weapons. I had heard about this mortar-and-pestle concoction from a reliable source, and that description was presented as an “Our Own Oddity”: No one kept track of the recipe.
The anecdote and quite a bit more turned up in “The West Forget…” essay. You might want to read it. I did. A couple of times, and I saved a PDF to my 2026 Research folder. Stuff has a tendency to be disappeared in the online world with remarkable velocity.
I want to highlight three comments from the essay and leave it to you to dig in and find the gems that resonate with your views of innovation, training, and skill development.
Here’s the first snippet. It is about the “efficiency” that flows from optimization. When one isolates a single factor and makes decision around that factor, what happens? Here’s the answer explained in terms related to the manufacture of an essential product:
…In 1993, the Pentagon told defense CEOs to consolidate or die. Fifty-one major defense contractors collapsed into five. Tactical missile suppliers went from thirteen to three. Shipbuilders from eight to two. The workforce fell from 3.2 million to 1.1 million. A 65% cut. The ammunition supply chain had single points of failure everywhere. One manufacturer for 155mm shell casings, sitting in Coachella, California, on the San Andreas Fault. One facility in Canada for propellant charges. Optimized for minimum cost with zero margin for surge. On paper, efficient. In practice, one bad day away from collapse.
I would suggest that the efficiency experts like Mr. McNamara of body count fame could prove that trimming would yield efficiency benefits: Low costs and more body count. Business school have for decades taught students how to examine processes, identify the inefficient bits (or the people bottlenecks), and remove them. In most cases the solution delivered some efficiency. The consultants got paid, and the MBAs took their bonuses and some started companies like Pets.com-type businesses.
Can you spot the flaw in the application of this type of efficient thinking? Take you time. From my experience, the big mistake is allowing the single factor to shape the thinking about a work process. Few ask, “What happens if we become too efficient and business circumstances change?” Why bother? The consultants will know what they are doing (ho ho ho), and we have the systems in place to deal with the unexpected. Yep, sure these outfits do.
Let’s look at my second snippet. This example applies to the very novel (for those who don’t know that smart software has been in oven for more than a half century) use of artificial intelligence. I quote:
RAND found that 10% of technical skills for submarine design need ten years of on-the-job experience to develop, sometimes following a PhD. Apprenticeships in defense trades take two to four years, with five to eight years to reach supervisory competence. Now map that onto software. A junior developer needs three to five years to become a competent mid-level engineer. Five to eight years to become senior. Ten or more to become a principal or architect. That timeline can’t be compressed by throwing money at it. It can’t be compressed by AI either. A METR randomized controlled trial found that experienced developers using AI coding tools actually took 19% longer on real-world open source tasks. Before starting, they predicted AI would make them 24% faster. The gap between prediction and reality was 43 percentage points. When researchers tried to run a follow-up, a significant share of developers refused to participate if it meant working without AI. They couldn’t imagine going back.
My take away from this example is that using technology to solve a problem may create other problems. Instead of coding faster, people are not sure what the AI-generated code does. Furthermore, when skilled coders used AI tools, the tool acted like a stuck disc brake. Coding more slowly was not the goal. But even worse, humans like convenience. The coders liked the AI tools even though the net effect was to bake in workforce resistance to doing the work the old-fashioned way. When organizations realize that smart software needs to be removed or used in a different way, people will quit. Efficiency and smart software seem to be teaming up to disadvantage an organization. Quite a surprise.
The third snippet reminded me of one of the Zoom lectures about smart software making employees smarter, better, faster, more empowered, etc. etc. I quote:
When juniors skip debugging and skip the formative mistakes, they don’t build the tacit expertise. And when my generation of engineers retires, that knowledge doesn’t transfer to the AI. It just disappears.
What’s happening in many organizations at this time is that thousands of people are being terminated. Someone thought that each individual was important to the organization. That’s the reason these people were hired. To cut costs and allow smart software to pick up the slack, the natural process of learning how an organization works, developing work processes that enable one’s colleagues, and allow the individual worker to absorb the language, content, and experience of a company operation will not take place.
I spoke with a young man who wanted to run restaurants. He asked me, “What do you suggest I do to become better at my job?” I was baffled. I told the young man that I had zero context for him and his skills. He persisted. The young man was earnest. I told him, “Watch the customers. If a customer is looking at another person’s lunch, go ask the fellow, “Would you like to try that dish? I won’t charge you.” The young man said, “I can’t give away free food.” I told him you were not giving away free food; you are communicating to that customer that you want to assist him. A kiosk ordering system does not encourage that type of manager customer interaction. People leave a store or restaurant and say, “I couldn’t find anyone to help me” or “These guys don’t know where anything is.”
Let me make several observations about this cited essay:
- The essay makes clear that the yip yap about knowledge management is just that… idle chatter. Once the knowledge dies, is deleted, or otherwise diminished, catching up and relearning may be impossible. Knowledge is inefficient. Efficiency is an enemy of knowledge.
- The production of products outside the United States has had catastrophic consequences on society, education, and innovation. Tim Apple proved again and again that without Chinese manufacturing expertise, the iPhone and other glitzy gizmos were impossible to fabricate in the US. Other companies have made the same “cash in” decision and their CEOs are going to jump ship. There is no easy fix to the situation efficiency yields when applied without contextual awareness.
- Every function I attend, I hear different comments about nothing works in the US. One person complains that the airplanes are late. Another grouses about turning up for a medical appointment and the clerk has not record of the visit. I went to pick up my horrible little car from the local garage. When I arrived, the manager asked, “Why are here now? It won’t be ready until tomorrow.” I pointed out that he had or his automated system had texted me that the car was ready for pick up. Look stupid, much, dude?
As a dinobaby, my span of authority and control experiences a shrinking radius every day. My hope is that someone reads this “The West Forgot…” essay and asks questions about assumed efficiency. Pretty soon, the smart software that hallucinates at an astounding rate, will not know how to process your input. Therefore, you are wasting its computational cycles by asking irrelevant questions.
The robot will allow people to find their future elsewhere. Lucky stiffs!
Stephen E Arnold, May 6, 2026
A New Spin on Start Up Doom: Nope, Not Good News
April 29, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
One of the “think thing” essays has been parked in my to-do file for about a month. Today (April 15, 2026) is the day. The write up is “Your Startup Is Probably Dead On Arrival.” With folks getting RIFed left, right, and sideways, the “start up now” chant is getting louder. The cited essay said:
… most startups older than two years old have an obsolete business plan – and a technical stack and team that’s likely out of date.
The essay tips its “think thing” hat toward smart software. The argument about Titanicism gets back on track with this statement:
The constraint used to be: Can we afford to build and ship this? Now the constraint is: Do we know what to test? And can we get in front of users fast enough to learn? Agile is no longer a serial process.
Thanks, Venice.ai. Good enough.
For me, this is “go fast, young man.” Apologies to Horace Greeley who wrote in 1865 something similar. The jargon for this concept is accelerationism.
The problem for the start up is that it must adopt smart software. The problem for the two year old start up is having to adapt to smart software. To start today, one must know the agentic boogie. To catch up, one must start over. Does this sound like good news for startups?
The source essay provides a list of tips. Here are three:
- You need a 2026 playbook
- The start up needs a “defensible moat”
- And I quote: “If you’re not losing sleep, you haven’t understood what’s happening.”
Okay, let me bring up a slightly different angle on this argument. Consider large companies. How do their new products work? If we look at Microsoft, it did the acceleration thing, burning tires in front of the disco. What’s happened? Microsoft is parking its AI hot rod and talking to experts about making the Copilot do more than get speeding tickets.
What about Amazon? The company is doing new things like killing functional Kindles and making chips and building data centers near a war zone and making life difficult for a customer to find a semi-decent product. It’s going fast and doing the equivalent of burning donuts in front of the disco.
And Google? It has gone slow. Like a turtle it has moved forward. Its pace of innovation, however, has allowed many flowers to bloom. Who can keep track of the new things Google is doing? But some Googley things are catching attention; for example, fiddling with YouTube ads and then insisting that those ads are not fiddled. Google also hides functionality in its smart software. At the same time, it chokes off innovation for the Android ecosystem. But the company sells ads. AI is a utility forcing Google to flounder in a quest for the good old days of traffic means clicks means a river of ad revenue.
These examples suggest that “startup thinking” at big companies does not do much better than regular startups; that is, the failure rate is baked in. A hit is a fluke, not a system and method like making commercial food like Nabisco chocolate chip cookies. (Watch a video on the process and then compare that method with the startup flounder, pivot, adapt thing.)
Several observations:
- Smart software is not able to get outputs right more than 75 to 85 percent of the time
- The agentic fantasy means that different smart software components are going to function correctly almost 99 percent of the time; otherwise, those retirement savings, yeah, gone due to a smart software problem buried deep in agentic Disneyland
- In the 2026 business environment, organizations are faced with problems not resolved by a Harvard Business School case study: War, civil issues, think thing marketing, etc.
Net net: Going fast is fun. What’s new? The speed factor. Humans, amp it up. Live fast. Die young.
Stephen E Arnold, April 29, 2026
-
- Subscribe to Beyond Search
Feature archive
News archive
-
