Author: remap_content_admin

I love this mural; it roughly translates to “To. be born, Portugal, to die, the world”. It’s on Rua Sao Bento, in Lisbon – a fact which I found impossible to determine by using Google, Google Maps, Bing, or ChatGPT.

How do I know it’s on Rua Sao Bento then? I used a sort of virtual assistant, an “agent”, called BabyAGI. You can try it here: https://babyagi-ui.vercel.app/ with an API to an LLM like OpenAI’s.

Basically BabyAGI (questionable name) automates the combined and focused searching of the web in an iterative process, against a goal that you set for it.

In my case, the goal was, “find the street in Lisbon, Portugal in which the mural «Para nascer, Portugal: para morrer, o mundo.» is located”.

I also gave it a first step: find references to this mural online in English and in Portuguese. In concrete terms, that meant it would perform a Google search, click on result, read results, and pass the results back to the language model for analysis,

As it does all this, it tries to fulfill the goal. If it does, it stops.

If it doesn’t fulfill the goal, and this is the key – it creates its own next step, using AI. And it keeps doing this, over and over again, to infinity (or for many steps as you limit it too).

There’s a hurricane of AI information this year but I feel that this is one of the most important pieces of it. It takes a little practice to use an agent like this, as with Google or ChatGPT. It also takes a little more planning.

But if you can figure out how to delegate parts of your work to it, then maybe you’ll figure out how your products and services solutions can do the same.

One interpretation of the movie, The Black Swan, is that the lead character, the Swan Queen and her rival, the Black Swan, are two aspects the same person.

Like Jung’s “shadow self”, the repressed black swan is a problem – a tangle of motivations and desires that are not acknowledged or even understood.

Is our refusal to acknowledge them a matter of self-survival? Ogilvy thought so. He said: customers fear that accepting their hidden desires will destroy their vision of themselves – and like a protective blanket they need that vision to survive.

But why? Because they fear that the desires will run wild; that was the Swan Queen’s fear. Examples of black swans running wild:

• Extreme laziness
• Extreme overeating and drinking
• Obsession with material things and money
• Controlling behavior

But repressing them doesn’t mean they don’t exist; that’s why fine-tuned messaging speaks to the Black Swan and says it’s Ok.

Netflix: it’s delightfully ironic to binge-watch series all weekend!

Here’s the thing, though – “swan-whispering” isn’t always sinister, because in moderation, most desires are harmless if not fulfilling. Using Basecamp and Asana, the team gets some control over its work – that’s nice for everyone.

There’s a product design and messaging sweet spot here.

There was a guy in Sicily who obtained high quality prints of historical maps, hand-colored them, and sold them in the public market in Catania, not far from the seafood stalls.

When he sold them, he described the historical and cultural details they captured in detail. He was a cultural historian; the lecture was part of the deal for me.

Was he a “map maker”? I’m inclined to say yes, but wth do I know.

Message Maps isn’t a “real” map maker either; instead, its “strategic message maps” exist to help grow a business, basically.

Meanwhile, the first map of any kind, as far as we know, was Imago Mundi, created by a Babylonian 2,700 or so years ago.

Here it is with Babylon at the central point of the world’s great commercial and cultural internet, the Euphrates (the vertical swath):

Nowadays, geographic maps are more utilitarian but this map’s main job was not to “give you directions to a taco stand” but to convey key messages:

• Babylon sits at the intersection of the world
• Babylon is a great commercial hub and a center of riches
• Babylon is a cosmopolitan city of knowledge, learning, artistry
• Babylon is the most multicultural and multi-linguistic place in the world – you are welcome here

So I guess I’m not the first to make a message map.

But here’s the real takeaway: strategic message maps are nothing new and they have helped organizations grow for a long time.

“Build uncool solutions for uncool problems”

– Anonymous

You’re kitchen sink has a leak – what do you do?

For most of plumbed history, you called the plumber. But now, you use plumber.ai.

Plumber.ai lets you diagnose the problem with your phone using pictures, video, audio, and a series of questions about about the particulars of the problem. It works something like this:

• It analyzes the imagery you provide using computer vision to find useful clues
• Each question it asks you is newly crafted with generative AI based on everything it has learned up to that point
• Based on the above steps, it advises you on what to do next: fix the problem yourself, which will involve ordering replacement parts for you, or call a plumber.

When you “call” a plumber though, the plumber also diagnoses the problem remotely – also using AI, repeating a similar process.

*      *      *

As of now, plumber.ai is a non-existent business (and Handyman Hank is a long way off of this vision). Will it exist? I have no idea. Will it belong to reddit, because reddit owns the data? I don’t know.

I’m just trying to make a point: in the near-term future, the imperative for many solutions providers, especially if you can get your hands on the right data, will be to to make an AI version of whatever human best understands the solution.

I was talking to a friend today about small things, such as smart cars, folding fans, and “bets” – as in the small actions you take in business and product development.

It got me thinking about product messaging – and keeping it short.

You might have heard the short story by Margaret Atwood, who wrote A Handmaid’s Tale:

“Longed for him. Got him. Shit.”

The “him” in this story could have authored this short story:

“I met my soulmate. She didn’t.”

Or maybe you’ve heard this bullet of sadness attributed to Hemingway:

“For sale: baby shoes, never worn.”

The last hits hardest, but but they’re all good; they all hook you in and tell the story at the same time.

At a campfire or a kitchen table – the skillful storyteller captures the entire essence of a story in just a few words, hooks in their listener, assesses  interest, then decides how much of the rest of the story to tell.

As it it with a case study – get good at compressing them down to one sentence and they become hooks.

The point is: don’t think you don’t have enough room to tell a story in your messaging.

When you work at a huge software firm, there’s a behind-the-veil effect when you realize this: 1-to-1, non-scalable relationships are a massive part of the business model.

Every such firm has its own services, some free, some paid,  from customer support, technical services, and training all the way up to full-service digital agency and consulting services. All provided by full-time humans, not code.

On the same token, large consultancies and agencies package more IP with their services, the bigger they get. Sometimes even a micro-SaaS.

Conversely, if a software company is smaller, there are usually fewer services around it, maybe just customer support. And when a consulting firm is small, there isn’t much IP.

Thus, most small firms in the B2B space are one or the other – solutions or services. With this distinction come very different company structures, sales and marketing processes, and brand messaging.

But LLMs might change that.

Small services firms can quickly build custom software products for clients – if they use LLM assistance in research, coding, system administration, UX design, and data management.

Small product firms can create  bigger customer support,  account management, and client services programs – if they leverage LLM capacities in research, content creation, sentiment analysis, data science, and categorization.

In either case, it’d be humans leading this work, of course. But a special kind of human – ones who know how to ask their LLMs the right questions.

What if you had an add-on for your product that let it do:

1. general research and documentation
2. summarization
3. categorization
4. sentiment analysis
5. personality analysis
6. code generation/editing
7. configuration assistance
8. pattern matching/vetting
9. editorial assistance
10. project management
11. questioning & ideation

Well you do, you just have to figure out the right way to add it.

To do so, it is crucial to become good at writing custom add-on code – ie. mastering your human language of choice. Which in turn involves mastering the art of providing a series of questions in a sequence, with context as needed, like Socrates, any artful purveyor of the 5 Whys, and surely, our homo sapien ancestors who first started to develop modern natural language technology 50k to 100k years ago.

Anyway, you guessed it – the add-on is LLM technology and the proof of concept is ChatGPT.

Jonathan’s right: Steve Job’s “next big thing” is here.

And yes, I left content generation out on purpose –  that’s better done by humans, at least if you’re interesting in getting new ideas out of your writing, and sparking them in your readers.

So what do mr. clean, pringles, and quaker oats have in common with b2b brands like mailchimp, hootsuite, and intercom?

Faces  – they all have faces.

We like faces by genetic inclination; a University of Nottingham study from 2015 showed that people prefer a gambling machine with a human-esque face.

But why do we like faces? A subset of gamblers surveyed who believed they had the ability to manipulate people were more likely to choose the humanoid one-armed bandit.

In short, we like faces on our brand because we like people, even in our business software, we want there to be someone there. Like Clippy but not an annoying geek.

Clippy was sort of a starting point for anthropomorphism in products and while he was “fired”, he’s back.

If you trace the arc of product UX since the advent of Internet software, the human presence gradually inserts itself.

For example, product onboarding went from “read the manual please” to a guided human-like tour, then  we got personalized recommendations, then chatbots.

B2B tech platforms levelled up in the last decade by pairing chatbots with not just real people, with clear faces and real names, but with intelligent people; for a time, a support chat on Pantheon.io yielded a conversation with legit open source web developer.

But the pinnacle is the real person you know, collaborating inside the software with you, inside the tool, doing the work with you – Basecamp, Balsamiq, Invision, Figma, Google Docs.

That’s quite an arc – from a the mustachioed cartoon guy on the Pringles can, all the way to the real person you know and trust, in the chat thread.

The message is pretty simple: use our product and work in collaboration to get what you need.

Peter Caputa made some great points yesterday on this LI post. He said:

“The old way of inbound marketing was about proving your own expertise.

…

This new way is about curating the expertise of your market.”

Yes! Stop proving, start curating.

What if?

• TEDx talks are commoditized and mass produced
• Even “real” TED speakers are smug and hard to watch
• Long, in-depth essays are rarely full of insight end-to-end; they are SEO plays
• People read web content even less than in 2022, let alone 2012 (per data Peter cites)
• TikTok-style short videos are now where most people seek “brain-on-fire”

Exceptions prove the rule, of course, but the point is that it’s getting harder to achieve brain-on-fire by reading web content by experts. Traditional expert-content is oversupplied and misaligned with our desire for equal exchanges.

Meanwhile, GPT lets us converse with collective essays of millions.

I think that’s where the brain-on-fire effect is now mostly relegated to – conversations:

• in public on social media, mostly in comment threads
• on conversation-based podcasts, especially when comments are enabled
• on personal newsletters, if replied to
• on cozy web discussions (Slack, Discord)
• in DMs and emails

And it happens between people who don’t necessarily need anything from one another – other than to exchange ideas.

It makes you think about where to take your message – and how.

When we’re young, we believe words have fixed meanings. But word meanings are fluid and change over time. Noam Chomsky, the father of modern linguistics, said,

“What we call definitions are not definitions … they’re just hints that a person who already knows the concept can use to understand what’s really going on.”

This is obviously true in the b2b tech ecosystem, with its new jargon, buzzwords, platforms, and frameworks. At some point in many conversations, you hear, “Ok but what do you mean by that _____”?

Maybe this has happened to you, where a customer asks a question that forces you to define a key part of what you’re selling:

• ‘What does your “customer success” program actually mean – what is that?’
• ‘Ok for the purposes of this conversation, what do you mean by “digital transformation” – you mean just putting our data in the cloud?’
• ‘What do you mean by single-source of truth? Isn’t our Avectra instance already that?’

It’s easier to field questions like this if you have written down your definitions. It’s also a lot easier to work these definitions into your product messaging. (And you don’t need that many.)

The alternative is letting someone else write your definition for you. Some other company, pundit, authority, tech journalist, whoever. And your customer uses their definition instead of yours.

What sounds like the better option to you?