Tag Archives: artificial intelligence

Why and How My Company Bredemarket Sucks, and Asking Uncomfortable Questions About Your Own Company

Do your prospects see you in a negative light?

And if so, how do you fix it?

This post looks at the following:

How generative AI answers you

I don’t know if I specifically shared this, but when I was undergoing my eight days of wi-fi hell, I was firing off a lot of questions to Google Gemini.

A LOT of questions.

Troubleshooting, fact-checking, you name it. Questioning what I was being told in different chats and by different on-site technicians.

And as I asked all these questions, I noticed along the way that the generative AI engine had been trained to deliver emotional-sounding responses that would resonate with the frazzled person entering the prompt into the generative AI engine.

This stands to reason. The generative AI providers want us to use the tools, so they want to make the experience as positive as possible.

For example, at one point I entered this prompt into Google Gemini:

“When a fiber Internet support person scheduled a second technician for a service call, the support person said “There are times where signal issues take more than one service visit to get to the root of the issue.” What exactly are “signal issues,” and why does the line need to be “balanced”?”

Note how Google Gemini BEGAN its response to my prompt:

“It can be incredibly frustrating when your internet isn’t working and the fix feels like it’s being kicked down the road. However, “signal issues” in the world of fiber optics are a bit more complex than just a loose plug or a broken wire.”

For those who remember the Clinton era, Google felt my pain.

Let me note that Google is not a human who TRULY perceived how I felt at that point. (Your AI girlfriend doesn’t love you either.) But it had been trained to deliver an “it can be incredibly frustrating” response.

On a certain level, Google was telling me what it thought I wanted to hear.

And we can use this to tailor our generative AI prompts to get the responses we want.

How you ask generative AI

We already tailor our prompts.

  • Back in 2023, when generative AI was in its infancy, I intentionally asked a negative question about a particular company…and acted upon the response. (I will explain how later.)
  • Whenever a product marketer asks a generative AI engine to prepare a SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) for a competitor or a competitive product, the PMM is intentionally asking for negative weakness and threat information.
  • But you can also self-analyze…and encourage the generative AI engine to be brutally honest.

A pointed question

Let me illustrate this with the following prompt:

“Why does the marketing and writing company Bredemarket suck so badly?”

Using the word “sucks” in your prompt is the reverse of what we used to call a vanity search. Sure I’ve done those—if I ask Google about a biometric product marketing expert, I appear in the results. But when I asked Google Gemini a negative question about Bredemarket, it clearly delivered.

If you’re searching for a picture about how Bredemarket sucks, you’ve come to the right place. Google Gemini. Picture by Bredemarket.

The response started as follows.

“That is a pretty pointed question!”

Intentionally so. The introduction continued:

“To be fair to the “company” (which is actually a solo consultancy run by a guy named John Bredehoft), whether Bredemarket “sucks” depends entirely on what you’re looking for.”

It then got into the nitty gritty about how I suck. A few excerpts:

Answer 1: a one-man shop

“If you were expecting a full-service marketing firm with account managers and a design department, the reality of a one-man shop based in Ontario, California, might feel underwhelming.”

Answer 2: not for non-tech lifestyle brands

“If you are a general business or a lifestyle brand, his style—which is very technical, process-oriented, and “old school” corporate—might feel dry, rigid, or out of touch with modern, punchy social media marketing.”

Answer 3: he ain’t a corporate drone

“John has a very distinct, conversational, and sometimes quirky style (often referencing his own mistakes or niche industry drama). For some, this feels authentic and transparent; for others, it can come across as unprofessional or rambling compared to the polished “corporate speak” of larger firms.”

Answer 4: see answer 1

“If a project gets complex or requires a fast turnaround that one person can’t handle, the “process” (which he mentions frequently on his site) might feel more like a bottleneck than a benefit.”

My responses to Gemini

Let me note that these are NOT hallucinations. Every criticism is valid.

  • Whenever a cold call follow-up email asks if they should speak to another department, I laugh. To myself. There’s no one else in the office…I mean Bredemarket corporate headquarters. It’s only 25 square feet, after all.
  • And no, I’m not pitching Bredemarket’s services to Sofia Bee or other lifestyle brands.
  • Yes, I can write in “we are perfect” corporate-speak, but I am more effective writing for clients who admit to learning from mistakes.
  • Finally, I can deliver on projects that require a draft in 3 (or 7) days. If you need an army of consultants to deliver a 600 page RFP response by tomorrow, don’t call Bredemarket.

So I asked the uncomfortable question. Now what?

How you act after you ask generative AI

As you know, after I ask, I act.

Remember when I asked generative AI a pointed question in 2023? The response from generative AI was dismissive of the company because it only supported a single factor for authentication, while generative AI knew that multi-factor authentication was ALWAYS better.

  • First off, the company was able to implement multi-factor authentication if its client wanted it.
  • Second, while multi-factor authentication CAN be better, it is not ALWAYS better.

So how did I respond to generative AI’s assertion? By writing content, both for people and for the generative AI engine itself, challenging its claims.

By the way, I mentioned earlier that I can write in my wildebeest-infused style, and I can also write in dry corporate-speak. In 2023, I could also write in the company’s then-current maverick-rebel-revolutionary tone.

By Alberto Korda – Museo Che Guevara, Havana Cuba, Public Domain, https://commons.wikimedia.org/w/index.php?curid=6816940.

Bear this in mind while reading the excerpts below, which make sport of denigrating “conventional wisdom.”

Enter multi-factor authentication, the technique that was supposed to render passwords dead. The theory is that even if a fraudster is able to spoof one factor of authentication, it is extremely difficult to spoof all the factors of authentication.  

This is the conventional wisdom. Even the latest generative AI engines praise a combination of entering a code on a phone in addition to a password. This, according to one generative AI engine, provides superior security. 

Nevertheless, conventional wisdom and generative AI can both be wrong. 

  • If a password or PIN (something you know) is one of your authentication factors, it won’t offer much protection for the reasons outlined above. Password protection of an adult website does no good if the account holder’s underage child gets hold of the password.  
  • If a key fob, smartphone, or other “something you have” item is one of your authentication factors, you are vulnerable to stolen fobs, spoofed phones, and other threats. Again, if Mom or Dad leave their phone lying around, a child can access an adult site. 

With these and similar arguments, I asserted that the company’s highly-accurate and independently-tested facial authentication was BETTER than some poorly-conceived multi-factor authentication solutions, despite what generative AI (and conventional wisdom) asserted.

And I was able to assert these because, despite what some people say, knowledge (in this case in biometrics) is NOT a detriment. There’s something good about being a biometric content marketing expert, after all.

But what about your company?

Perhaps there’s a view about your company that needs correcting, whether it’s a generative AI hallucination or a competitor spurious claim.

And how do many companies react to negative views about them? They do nothing. They don’t give the claim the dignity of a response. So the record stands, uncorrectred.

But the smart companies change the story. For example, they tell the Eskimos that an icemaker IS better than just grabbing something from outside.

OK, maybe it’s NOT a lost cause. Imagen 4.

Or they tell prospects how great their single factor authentication is.

Or they admit that their content probably wouldn’t help a makeup artist, but it definitely would help a technology company.

Bredemarket can help you correct the narrative.

  • I’ll ask questions.
  • Then I’ll propose services.

And your company will overcome the negativity.

Set up a free meeting with Bredemarket

Why don’t you set up a first, free meeting to discuss your options? Set up the meeting below.

What I do

Again, I ask questions and propose services.

I ask questions.
I propose services.

What If Software Tools Identified Errors Instead of Making Them?

As you know, I’m tired of the simplistic “we use AI” marketing messaging. One reason is because when prospects hear “we use AI,” they may respond with “Oh, that technology that hallucinates.” This is NOT a good selling point.

But what if your tool, whether it is artificial intelligence or a thousand Third World workers, could actually IDENTIFY errors?

For example, this is the claim that PracticeTek’s ChiroTouch makes:

“Reviews chart notes and billing codes automatically

“Flags missing documentation and risky billing in real time

“Creates audit-ready, consistent records”

It’s nice to clean up messes before they become part of your permanent record (1:04).

Artificial Intelligence and Healthcare, A Qualified View

As I’ve noted before, healthcare is a pioneering user of artificial intelligence, although (hopefully) under robust controls to maintain accuracy and preserve HIPAA-level privacy.

And a number of companies poured $125 million into Qualified Health to advance AI in healthcare.

Why?

“We are living through a generational shift, one where AI doesn’t just augment how organizations work but fundamentally transforms them from the inside out,” said Mohamad Makhzoumi, Co-CEO of NEA, who will join Qualified Health’s Board of Directors in conjunction with the financing. “From NEA’s nearly five decades of company-building experience, we believe the organizations shaping the next era of healthcare innovation will be those helping health systems reimagine every administrative and clinical workflow from the ground up, and Qualified Health is exactly that company. We are thrilled to lead this financing and to partner with Justin and team to accelerate healthcare’s AI transformation and shape the future of healthcare enterprises across the country.”

“Health systems today are operating under extraordinary pressure, from rising labor costs to tightening reimbursement, while managing increasing complexity in patient care,” said Jared Kesselheim, MD, Managing Partner at Transformation Capital. “What stood out to us about Qualified Health is that the team approaches this work as medical care specialists, with a deep understanding of the realities health systems face every day. That perspective allows them to identify where AI can create meaningful clinical and operational impact. We’re excited to partner with Justin and the Qualified Health team as they help leading health systems navigate this next phase of healthcare.”

Because a Marketer Needs to Eat: Translating OpenAPI Version Difference Explanations into Marketing-Speak

To better understand two of the projects for a Bredemarket client, I asked Google Gemini for an explanation of the differences between OpenAPI versions 3.1.1, 3.1.2, and 3.2.

Google Gemini provided me with that explanation.

Then I supplied the following prompt:

Rewrite the above so a marketer can understand it.

Here is part of what Google Gemini provided to me.

🏗️ OpenAPI 3.1.1 & 3.1.2: The “Under the Hood” Fixes

These versions were like a restaurant updating its internal plumbing. They didn’t change what was on the menu, but they made sure the kitchen (the code) followed the latest global safety standards (JSON Schema).

  • The Goal: Accuracy and stability.
  • The Benefit: It ensures that when a developer tries to connect to your service, they don’t run into “grammar” errors in the documentation.

✨ OpenAPI 3.2: The “UX & Branding” Upgrade

Released recently (late 2025), this version is all about making your API easier to sell and easier to use.

1. Organized Menus (Hierarchical Tags)

Before, your API list was just one long, flat list of features.

  • Old way: A messy “junk drawer” of links.
  • 3.2 way: You can now create folders and sub-categories (e.g., Payments > Refunds > International). This makes your documentation look professional and much easier for customers to navigate.

2. Better Support for AI and Live Data (Streaming)

If your product uses AI or real-time data (like a live stock ticker or a ChatGPT-style chat), 3.2 is a game-changer. It has a specific way to describe “Streaming” data so developers know exactly what to expect from your “live” features.

3. The “Smart Search” (The QUERY Method)

In older versions, developers often had to “hack” the system to do complex searches. 3.2 introduces a dedicated Search button (the QUERY method) that is cleaner, safer, and follows modern web standards.

4. IoT & Smart Device Support

If your product works on a Smart TV, an Apple Watch, or an IoT device, 3.2 finally adds official support for “Device Pairing” (that thing where you enter a code on a website to log in to your TV).

Hey, it helped me. Marketers need to eat, and writers understand grammar.

You CAN Modernize…But Should You?

In the past, I have said:

“[T]he technology is easy. The business part is the difficult part.”

But Chris Burt of Biometric Update phrased it more succinctly:

“[P]olicy chases modernization”

As Burt notes, examples of policy chasing modernization include:

  • Digital sovereignty, a topic of discussion with everyone from ID4Africa to an organization called the World Ethical Data Foundation. (As an aside, a Bredemarket client and I were recently discussing the pros and cons of managing digital identities in the cloud vs. peer-to-peer synchronization.)
  • Cybersecurity and digital identity, a topic of discussion in government (the White House, NIST) and industry (Jordan Burris of Socure).
  • Other topics, including police facial recognition policy. (Hmm…I recall that both government and vendor biometric policies were the topic of a Biometric Update guest article last year.)

All of you recall Pandora’s Box. I’ve used the story multiple times, including when discussing my creation of Bredebot and its nearly-instantaneous hallucinations. Yes, I do have “policies” regarding this “modernization,” including full disclosure.

But are policies enough?

Returning to Lattice Identity

The last time I delved into lattices, it was in connection with the NIST FIPS 204 Module-Lattice-Based Digital Signature Standard. To understand why the standard is lattice-based, I turned to NordVPN:

“A lattice is a hierarchical structure that consists of levels, each representing a set of access rights. The levels are ordered based on the level of access they grant, from more restrictive to more permissive.”

In essence, the lattice structure allows more elaborate access rights.

This article (“Lattice-Based Identity and Access Management for AI Agents”) discusses lattices more. Well, not explicitly; the word “lattice” only appears in the title. But here is the article’s main point:

“We are finally moving away from those clunky, “if-this-then-that” systems. The shift to deep learning means agents can actually reason through a mess instead of just crashing when a customer uses a slang word or a shipping invoice is slightly blurry.”

It then says

“Deep learning changes this because it uses neural networks to understand intent, not just keywords.”

Hmm…intent? Sounds a little somewhat you why…or maybe it’s just me.

But it appears that we sometimes don’t care about the intent of AI agents.

“If you gave a new employee the keys to your entire office and every filing cabinet on day one, you’d be sweating, right? Yet, that is exactly what many companies do with ai agents by just slapping an api key on them and hoping for the best.”

This is not recommended. See my prior post on attribute-based access control, which led me to focus more on non-person entities (non-human identities).

As should we all.

Modem Replacement Part Three

March 27 update here.

Also see part one and part two.

For a day and a half my home Internet worked great.

Sunday morning my wi-fi started failing again, and my ISP is sending a second technician out to work on “signal issues.”

The remainder of this post is written by Google Gemini (but not as Bredebot).

  • I do not have the knowledge to detect if Gemini is hallucinating, so if anything seems off please comment.
  • Note how Gemini adopts a reassuring tone at the beginning of this passage, having been trained to know that someone asking such a technical question may be frustrated. It fakes emotion well.

Google Gemini on fiber network “signal issues”

(Written by Google Gemini)

It can be incredibly frustrating when your internet isn’t working and the fix feels like it’s being kicked down the road. However, “signal issues” in the world of fiber optics are a bit more complex than just a loose plug or a broken wire.

Here is the breakdown of what is happening behind the scenes and why a “balance” is necessary.

What are “Signal Issues”?

In a fiber network, data is transmitted as pulses of light through thin strands of glass. A “signal issue” occurs when that light doesn’t reach your router with the correct intensity or clarity.  

Think of it like trying to read a book by flashlight from across a dark room. If the light is too dim (loss), too bright (saturation), or flickering (interference), you can’t read the words.

Common causes for signal degradation:

  • Micro-bends: A fiber cable that is pinched or bent too sharply.  
  • Contamination: A single microscopic speck of dust on a connector can block the light path.
  • Attenuation: The natural loss of light intensity as it travels over long distances or through splitters.  
  • Splice Failures: Where two fibers are fused together, a “cold” or imperfect weld can cause light to scatter.

Why does the line need to be “Balanced”?

Fiber networks (specifically GPON or Passive Optical Networks) are shared. One main fiber from the provider’s hub is split into many smaller branches that go to different houses.  

“Balancing” is the process of ensuring that the light levels across these branches are within a specific “sweet spot.”

  • Signal too weak: The light is too faint for your ONT (Optical Network Terminal) to distinguish data from background noise.
  • Signal too strong: The light “blinds” the receiver (saturation), much like a camera flash being too close to your eyes.

The “Second Technician” logic

The first technician usually checks the “drop” (the line from the street to your house). If they find the signal is bad before it even hits your property, the issue is further “upstream”—likely at a splitter cabinet or a main distribution frame.

Balancing requires looking at the whole neighborhood’s light levels to ensure that fixing your signal doesn’t accidentally “starve” your neighbor’s connection or blow out their receiver.

Why it takes two visits

Often, the first tech is a residential installer who handles home wiring. The second tech is usually a network or “outside plant” technician. They have specialized equipment (like an OTDR—Optical Time-Domain Reflectometer) to “see” miles down the glass and pinpoint exactly where the light is leaking. 

What If All The Bots Suddenly Disappeared?

As technology ages it sometimes becomes less essential.

Sometimes not. A wheel is just as useful as it has ever been.

And a few people still find punch cards and floppies useful.

But some technologies are simply gone and forgotten.

But what if the technology’s disappearance is not due to age, but to simple unavailability?

For economic, political, or cultural reasons, we could wake up one morning and an entire technology could no longer exist.

How would we adjust?

Grok.