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Showing posts with label ChatGPT. Show all posts
Showing posts with label ChatGPT. Show all posts

Thursday, December 11, 2025

"Learnings" explained by ChatGPT, Claude, and Gemini

 I'm not at all a fan of the modern use of the word "learnings" in place of what could be called lessons or takeaways. I wondered what led to seeing this all-too-often in business communication. I  decided to see what I can glean about it from generative AI. 

ChatGPT

I started with ChatGPT and got the following response: 

📜 1. Historical origin of “learnings”

  • Old English already had leornung (“learning, knowledge obtained by study”).

  • “Learnings” appears intermittently in Middle English and Early Modern English, but mostly in the sense of knowledge or scholarship, not “takeaways.”

So the plural form is historically attested, but the modern meaning is new.


📈 2. When did “learnings” (meaning “takeaways”) take off?

Linguists and corpus researchers note that:

  • The usage begins to appear in the 1970s–80s in fields like education, psychology, organizational development, and management consulting.

  • It becomes much more widespread after the 1990s, especially in:

    • Corporate training

    • Agile/software development

    • Post-mortem analyses (“What were the key learnings?”)

By the early 2000s, it was common in business English; by the 2010s, it had firmly entered corporate jargon.


💬 3. Why was this term coined (or revived)?

Several reasons:

1. Jargon need in organizational development

Fields like management consulting, OD, and “lessons learned” methodology wanted a compact noun for:

“knowledge gained from experience, not just from instruction.”

“Lesson” felt too teacher-student oriented; “takeaway” too informal.

2. Influence of corporate and academic training culture

Training programs often talk about:

  • learnings,

  • key learnings,

  • actionable learnings.

The plural makes it feel like a measurable, list-friendly deliverable.

3. Analogy with words like “findings”

Consulting and research language uses many “-ings” nouns:

  • findings

  • earnings

  • savings

  • outcomes (a parallel)

“Learnings” fit the pattern of a concrete output after an event or analysis.

4. Global business English spread

Because English is used by many non-native speakers in international companies, simplified or regularized forms often spread.
“Learnings” works grammatically for learners who think:

verb → noun with “-ing” → plural is okay.


🚫 4. Why do some people dislike it?

  • For many native speakers, “learnings” sounds ungrammatical or like jargon.

  • They prefer:

    • lessons

    • takeaways

    • insights

Style guides (The Economist, AP, etc.) often recommend avoiding “learnings” unless quoting business jargon.

Claude's take

I then put the same question to Claude and got this response written out in paragraph form rather than bullet format with two citations, albeit from the same source. Also note that it does not throw in emojis like the other two do:

Based on my search, "learnings" has an interesting history. While the word itself dates back to the 14th century and was commonly used through the 18th century (Shakespeare even used it in Cymbeline), it surged in popularity during the 1950s in business jargon and educational contexts CSMonitor.com.

The term wasn't really "coined" in the modern sense—it was actually revived. From the 1400s through the 1700s, "learnings" meant "lessons" or "instructions" and was perfectly acceptable. However, it fell out of common use in the 19th and 20th centuries.

When it resurged in the 1950s, it took on a slightly different meaning in corporate and academic settings, essentially as a synonym for "findings," "conclusions," "results," or "takeaways." This revival happened as business jargon and corporate speak were developing their own vocabulary.

Today, learnings is widely viewed as pretentious and useless business jargon CSMonitor.com, appearing on countless lists of annoying corporate terminology. Despite this criticism, it has become firmly established in business, academic, and scientific contexts. The irony is that people generally have no problem with "teachings" (what is taught), but "learnings" (what is learned) somehow grates on many ears.

So it wasn't so much coined as it was resurrected from older English and repurposed for modern business speak—which is perhaps why it feels both familiar and oddly wrong to many people.

Google Gemini

To round out the experiment, I also posed the question to Google Gemini, which is closer to ChatGPT in style of presentation. however, it fails to grasp how much some of us hate the term. This is its response:

The word "learnings," particularly as a plural noun replacing terms like "lessons" or "takeaways," saw a significant increase in use as a corporate and educational buzzword starting around the year 2000.

However, it's important to note that the word itself is not new.

🗓️ Timeline of Usage

  • Middle/Early Modern English (14th - 17th Century): The noun "learning" meaning "a thing learned" (a countable sense) and its plural, "learnings," were in occasional use. Shakespeare, for example, used the term.

  • 1950s: The term saw an increase in use within academic and educational circles (often referred to as "edu-speak").

  • Circa 2000: It became a widespread buzzword in business-speak (corporate jargon), commonly appearing in phrases like "key learnings" or "apply these learnings." This is when it really started replacing "lessons learned" or "takeaways" in project management and professional contexts.


🤔 Why Was the Term Coined/Revived?

While "learnings" is often considered unnecessary jargon by language purists, its resurgence and adoption in business contexts appear to stem from a perceived need for a different nuance than existing words:

  • To Distinguish from "Lessons": The word "lessons" can carry connotations of being taught (as in a classroom lesson) or of something learned from a failure (as in "we learned our lesson"). "Learnings" is sometimes used to refer to insights or knowledge gained through experience or a process, often in a less painful or formal way.

  • To Merge Concepts: In corporate and project environments, "learnings" acts as a shorthand to combine the idea of "things we've learned as a team" and "action items" or "next steps." It is intended to imply a list of actionable insights or points of wisdom distilled from an experience.

  • Corporate Trend: It is part of a broader trend of turning verbs into nouns in corporate language ("What's the ask?" or "What's the solve?"). The plural "learnings" parallels other accepted plural nouns derived from verbal actions, such as findings and teachings.

Essentially, its modern rise is largely attributed to it becoming a recognizable piece of corporate jargon that differentiates the knowledge gained from the traditional, sometimes rigid, sense of a "lesson."

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The information from all three is consistent, so we don't have the problem of AI hallucinations here. However, Gemini seems to ignore the fact that many people hate the use of this jargon, considering it pretentious, as Claude points out. It also omits that it's not recommended for use in publications, as per ChatGPT's citation. Perhaps that's a reflection of Google's own corporate culture and form of communication.

Related: https://writewaypro.blogspot.com/2024/06/a-new-generative-ai-comparison.html


Tuesday, July 23, 2024

Aim higher than SEO for your marketing content


You know, Jane Austen could have opened "Pride and Prejudice" with the standard line, "Once upon a time there was a family with five girls and no sons to inherit the estate that they depended on for their support." She didn't.

Pride and Prejudice tote with the opening line of the novel
https://www.zazzle.com/pride_and_prejudice_tote_bag-149363338488539996


Instead of sticking with the safe formulation, she crafted one of the most memorable openers for a novel that also gives the readers a taste of her wit and sense of irony. That opening line is Austen's brand in a nutshell.


This is what businesses should be striving for in their opening lines on their sites and their reports. Generative AI will not deliver that because it will work off pre-existing models. Simply tweaking that output will still not result in something truly fresh, though it may be just good enough to not incur the generative AI penalty Google has promised to deliver for those who aspire to achieve high SEO results.


Achieving SEO goals is not the same as making a memorable impression on your target audience when they click through to your site or blog.


What impresses Google is not necessarily going to move your target market to establish a relationship with your brand. The content that does can only be produced by a combination of analytics and human creativity.


You can't just be content with optimizing for search engines by following SEO guidelines when you need RO -- responsiveness optimization -- that requires blazing your own brand path.


That's what Write Way branding and marketing is all about. Learn more about my business offerings here.


Related

What B2B content marketers get wrong
Add a pinch of salt to creative claims for AI
Most Memorable Brand Slogans
What Edison Can Teach Us About SEO
Pride, Prejudice and Persuasion: Obstacles to Happiness in Jane Austen's Novels


You can also follow Ariella Brown.  

Friday, June 28, 2024

An Apology to Generative AI

ChatGPT spelled out in Scrabble tiles

By Ariella Brown


I'm not a generative AI fangirl. If anything, I'd consider myself more of a skeptic because people tend to not just use it as a tool to improve their writing but as a tool to replace the work of research, composition, and revision that is essential to good writing.

It is generally embraced by people who consider online research to be too much work and who believe that anything that comes out of a machine that will charge them no more than $20 a month for writing to be too good a deal to pass up. 

For those of us who actually read, the output of ChatGPT and similar LLMs is not exactly something to write home about. Unless you know how to prompt it and train it to write in a truly readable style, it will default to the worst of wordy, opaque corporate style text. 

But this isn't the fault of the technology. It's the fault of the mediocre content that dominates the internet that trained it. Below is one example that I pulled off  the "About" section of a real LinkedIn profile (first name Kerri maintained in the screenshot that proves this is real and not something I made up):  LinkedIn screenshot

As a strategic thinker, problem-solver, and mediator, I thrive in managing multiple, sometimes differing inputs to achieve optimal messaging and positioning. My proactive nature drives me to partner with leaders across marketing teams and internal business units, aligning efforts, connecting dots, and adding context to enable flawless execution of communication strategies and tactics.


In fast-paced, fluid environments, I excel in effectively prioritizing tasks and ensuring they are completed efficiently. I have a proven track record of setting and meeting strict deadlines and budgets, leveraging my ability to navigate dynamic landscapes seamlessly.

Driven by natural curiosity, I am constantly seeking to understand and implement the latest trends, technologies, and tactics essential for driving B2B sales opportunities. My keen interest in exploring new channels for messaging and content distribution fuels my passion for innovation and continuous improvement to not just meet but exceed expectations.

Let’s connect to explore how we can drive success together.

You know what sounds exactly like this? Cover letters you ask ChatGPT to compose for you. 

I've tried those out a few times and never been happy with the results because they always sounds like the text above. Trying to tell it to sound less stiff doesn't make it sound any less canned, and forget about getting it to copy my own writing style.

It's possible that Kerri used ChatGPT to create her "About" section. Given that she's been in the marketing biz for some time, though, I'd think she had to have had something filled out for years before ChatGPT was available, and it likely sounded very much like this even if she did let some LLM or something like Grammarly tweak it for her.  

People like Kerri, who ignore all writing advice from the masters like Orwell, White (watch for a upcoming  blog about him), and others made this the public face of corporate communication who are to blame for the bombastic and soulless style that LLMs replicate at scale. 


That's the reason for this apology too ChatGPT for mocking its output. You're not the one at fault. You had no way of knowing better. Humans do, and they should have provided you with better models for writing. 

Note on the title: I thought of giving this post the title "Apology" intended in the classical sense of a defense or justification for something others take as wrong with the hint of an apology to AI. Knowing that that wouldn't be clear to some readers, I opted to make this just a straight apology instead. 

Related:

A new generative AI comparison




Sunday, June 23, 2024

A new generative AI comparison






Photo by Andrew Neel: https://www.pexels.com/photo/monitor-screen-showing-chatgpt-landing-page-15863066/



In the past, I've compared Chat GPT to Google Bard (now Gemini). For today's exercise, I put the same query to Claude, ChatGPT, Gemini, and Copilot. I put in the name of a real person and identified the location for that individual in Queens, NY.  None could give me the information I sough. 
What's interesting, though, is noting the differences in how they contextualized their responses. Out of the four, Claude shows the greatest self-awareness, and I'd say that Copilot shows the least.  

Claude's response

As this appears to be asking about a relatively obscure individual, I want to remind you that while I try to be accurate, I may hallucinate or generate incorrect information when asked about very specific people who are not widely known public figures. If you're looking for factual information about this person, I'd recommend checking other reliable sources.

I award Claude points for warning me about the possibility of hallucinations occurring when generative AI attempts to answer questions in the absence of data. See 

ChatGPT's response

I don't have specific information about an individual named ____from Queens, NY. It's possible that she is a private individual or someone not widely known beyond her personal circles. If she is known for something specific like public contributions, achievements, or notable activities, that information might be available through local news sources or community records.

ChatGPT's response failed to warn about hallucination, though it's interesting that it inferred the person in question was a she (based on the first name, I suppose), a gender identification that Claude managed to avoid.

Google Gemini's response

Gemini just bowed out, practically chiding me for giving it this query that it could not answer:
 
I do not have enough information about that person to help with your request. I am a large language model, and I am able to communicate and generate human-like text in response to a wide range of prompts and questions, but my knowledge about this person is limited. Is there anything else I can do to help you with this request?


Copilot's response

Copilot went in a completely different direction. I wouldn't call it a hallucination, but it is still inaccurate. It wanted to find a match, so in one case it named a business with the last name appearing twice as a partnership, though it admitted that was Brooklyn rather than Queens. Its second suggestion was a male doctor in Queens with a similar last name, though it is spelled differently. Honestly, I find it hard to believe that these are the only two results for the last name in all of NYC. I mean once you're expanding the parameters, there really should be a lot more than two possible results. 


RelatedAn A/B test of generative AI
Bard brings in the clowns


You can also follow Ariella Brown.  

Wednesday, March 6, 2024

The 6 step plan that fails

Photo by Aleksejs Bergmanis: https://www.pexels.com/photo/aerial-photography-of-concrete-bridge-681347/

By Ariella Brown

I should have known better, but I still  fell for it. 

I put in my information in order to ungate and  download the tantalizingly titled "How to build pipeline with content in 6 steps" from a company I won't name here. Disappointment doesn't begin to express my feeling at this one-pager that only someone who has never created business content wouldn't know.

The first step is: "Do some research" in order to know you customers.  Obviously, that is your starting point. But it doesn't give you any advice on how to go about this. That's what many businesses who fail to understand their customers really need help with. Surveys are ignored, and few take the time for really in-depth talks because all conversations turn to upsells and not to fostering understanding.

Step 3 is another obvious step for any content creator: "Tell a story." 
That was to be the bridge to step 4: using data and the claim that first-party data is the best (definitely debatable).

But the real goal of the whole piece was to declare in step 5 that you need the right tool -- the one the company that put this out offers -- to track engagement. Step 6 is to track engagement (no doubt, with this tool).


The dichotomy that's wrong

What struck me more than the blatant selling in this presented-as-helpful-guide  was the assumption of step 2, which focuses on a division of content that must appeal to people who love categories but that is, ultimately, counterproductive.

It says: "Determine if your content is tactical or 'experience-driven'.” It then goes one to explain that "collateral related to the business image like presentation decks, press releases, and thought leadership" all goes into the "tactical" bucket.

That is presented as distinct from "collateral related to demand gen activities, supported by personas, nurture content, event material, and industry-specific content" go into the "experience" bucket. The chef's kiss here is that the writer (I picture a college student intern using Chat GPT) adds in this note: "(hint: this is the one you want to focus on for demand gen)."

Now, if were to uphold this division of content type, something I don't advocate at all, I would definitely put thought leadership into the experience/demand gen bucket. That's where it belongs, no question about it. 

On the other hand, there is a very important form of content for the tactical bucket that is not named -- case studies or success stories.

Ultimately, though, the division seems to be about the more direct sales enablement materials that would be considered tactical vs. the brand and relationship-building content that is more often associated with demand gen. The delusion of this division is that the former works for immediate conversions-- at least to the point of an MQL while the latter is the stuff you put out to get the person primed for the tactical stuff.

But in reality, your target customer won't be pushed into a linear funnel, neatly progressing from your ToFu to your MoFu to your BoFu content and take the action specified as soon as they hit the tactical content. The buyer's journey is a lot more complex and recursive than that, and recognizing this reality should be part of your first step in building your pipeline.


 Related:


You can also follow Ariella Brown.  


Thursday, June 8, 2023

Should you market like Apple or OpenAI?



by Ariella Brown


When it comes to winning through marketing, there are two divergent strategies that can deliver spectacular results. We’ve seen them at work in recent months with the launch of new offerings that have generated massive hype.

Aim high or low 

One marketing approach is based on mass distribution to get people to sample your offering for free while adding to the hype about it. The other is based on loyalty to a strong brand that has won over fans willing to pay a premium price.  

Which one you choose depends on what kind of product you are offering and what your brand position is. As loyalty is only earned over time and through people’s positive experience with products, Apple’s marketing is not usually going to work for a new kid on the block. 

ChatGPT takes the low road to success

Understanding that, OpenAI took the tactic of mass distribution on a scale we have not seen before. It launched ChatGPT on November 30, 2022 and attracted over a million users in the first five days.  

In just  two months, it hit 100 million monthly active users, which made it “the fastest-growing consumer application in history,”  Reuters reported.  It now boasts of 1.8 billion visits a month, and many of those visitors are happy to pay the  $20 a month subscription for ChatGPTplus, which was introduced in February. 

What made ChatGPT take off so rapidly was the build-up of hype that continued to grow as a result of people being able to gain access to generative AI on their own devices simply by registering and logging in.  Remove any barriers to entry – like cost or the need for specialized equipment — and you get to enjoy rates of PLG (product-led growth).

Apple takes the high road

In contrast to OpenAI, Apple already has a well-established customer base eager to experience its new offerings. Accordingly, it doesn’t have to offer free access and can seriously expect people to pay $3499 for the Apple Vision Pro that is to become available for sale only in 2024. 

Why unveil something a half a year before you can even preorder it? To heighten the anticipation and the satisfaction the early adopters will feel when they are among the first to obtain the latest offering from a brand they love.


Even at this stage, they are all reading the tweets, viewing the videos, and asking questions that show a high level of interest. That level of engagement combined with the reviews from all the tech journalists who got to play with the headset create a type of hype that is more rarified than that surrounding ChatGPT but just as impactful.


Would you buy it? 

Apple can price its headset that the average consumer can’t afford because it has millions of fans already who know and love its products. Within those millions are tens of thousands who would not consider the price tag too high for the bragging rights that come with being among the first to have this new offering.

Sure, there will be imitators putting out cheaper versions of the headset. But that’s always been the case for Apple devices. True fans insist that you get what you pay for and you shouldn’t settle for second-best.

On the other hand, OpenAI had the difficult job of rousing interest in something intangible that couldn't be photographed or shown to advantage on video. You could have accounts of individual user experiences, but those don't generally generate the response of "Want!" the way videos do.

What do you do when you’re offering something people haven’t had before from a brand that has yet to establish its reputation? You offer free samples, and that’s just what OpenAI did – very successfully.  Once it had enough people hooked and even boasting about making it integral part of their businesses, it rolled out the premium version that most people could afford to pay.

Which are you?

"Know thyself"  is the basis of determining your course of action in life and in business. If you’ve established yourself as a premium brand that can trade on exclusivity, you can offer high end products to your fan base.  But if you’re an unknown quantity, you have to win over the masses to at least give your offering a try to build up a loyal following. 

What’s the tell? How many followers identify themselves as such is one indicator. Notice that even in its current heyday, OpenAI’s 2.3 million Twitter follower are dwarfed by Apple’s CEO’s 14.1 million. (No doubt, Steve Jobs’ numbers would be even higher if he were still alive today).


Most businesses will never attain Apple’s superstar status, but they can still follow the high road of marketing after establishing their brand as a leader in the market. And for those whose offering is not suited for premium pricing, OpenAI’s incredible rate of adoption proves that it is also possible to go from zero to millions in just a few months.

So long as you know what you're about and who makes up your target market, you can adopt the right strategy and follow the high, low, or middle marketing road to success.  


For help determining with marketing path to take and what type of content can help you get there visit WriteWayPro and  book a free consultation call.

Related: https://writewaypro.blogspot.com/2023/05/did-open-ai-open-pandoras-box.html


Thursday, May 18, 2023

Did Open AI Open Pandora's Box?


Pandora opening the box that releases  harm into the world. Image at: https://nypl.getarchive.net/media/pandora-opens-the-box-ca3915



OpenAI not only democratized access to AI but popularized it by inviting people to use it for free. Many of us have opened that box, but some of us have been dismayed at the results that speak as if they are objective truth without any accountability for sources of information or explanation for how ChatGPT arrives at its conclusion.

Relying on AI as an objective source of information ignores the fact that it reflects the bias embedded by its human programmers and can reinforce discriminatory effects. The consequences of that can range from biased beauty standards to reinforcing illegal discriminatory practices.  

Now that it just costs $20 a month or can even be available for free at off-peak times, everyone can -- and many are -- make use of ChatGPT instead of doing research in a variety of sources with documentation that offers at least some level of accountability that is essential for explainable AI. 

Read more here:  https://www.linkedin.com/pulse/did-open-ai-pandoras-box-write-way-pro/?trackingId=E3yor3MrHAi2B2HwIdqlVQ%3D%3D


 Related:


An A/B Test of Generative AI


AI' s Got Some Explaining to Do

AI's early attempts at screenwriting

The Pros and Cons of Generative AI

11 Quotes About AI 

AI Informs Personalization for Starbucks

AI Accessibility: The Next Spreadsheet Revolution for Modern Business? 

 


http://uncommoncontent.blogspot.com/2021/01/the-original-selection-of-11-ai-quotes.html