How is human expression changing because of how LLMs express?

It's well recognized that LLMs have a certain writing style. Most of them follow common patterns like em dashes, 'a, b and c' structures, punch - then expand, 'it's x, rather than y', 'it's not p, it's q', and so on. But with so much content being written by LLMs, including that in research papers - where it's generally permitted to use AI for editing and improving readability, it's quite possible that the way humans write is also changing. With most of the content we consume being AI generated, the influence on our written expression is expected, and in my observation, starting to emerge. As evolved monkeys, most of our learning is through copying. Being quite intelligent, we are able to copy even complex patterns. The same intelligence allows us to adapt, improvise and customize - leading to both similarity and uniqueness in every aspect. (The previous line looks most definitely AI.)

I would expect the adjustment to be mutual, but I don't know whether AI is still learning from us in the way we do from it. But in future, we'll definitely have difficulty figuring out what's AI generated, because with time, NI would start looking like AI. (NI is natural intelligence. I guess I can (can I?) claim the term as the 'natural' counterpart to AI, which existed before AI.)

But the bigger concern is that, perhaps, we may not have any purely NI based writing in some distant future. We'll only be fixing drafts generated by AI based on what we tell them, just like most coders only tweak pre-written code. What we 'tell', and how we do, would be the only pure and natural expression from NI, although not polished to the eventual intended format. It's hard to imagine how that informal expression might change, but it certainly will.

There is still some way to go before we start talking to AI more than we talk to humans. That will have interesting ramifications on how we communicate, not only with AI, but also with other humans. (A close parallel, purely natural, is how American accent(s) came about, although nobody in the source countries of the OG immigrants in America spoke like that. Same goes for Australian accent.)

It's interesting how the various forms of human expression would evolve with AI playing an increasingly central role here on. I'll be watching this closely. And would love to hear what others are observing and experiencing.

IT services outsourcing - trapped in the cost play

IT services business started and evolved as a cost-reduction offering. First, offshoring offers a direct drop in costs to customers. Then greater productivity - doing more with less resources - offers greater cost savings with time. It's funny how most IT deal reviews by leaders hover around ON-OFF (onsite-offshore) ratio and YoY (year-on-year) productivity, while trying to hit an attractive price at an acceptable margin. Often, it's people with limited understanding of technology trying to buy and sell technology services.

These ratios, of course, are just high-level indicators of solution optimality, and benchmarks like 90-95% offshore headcount and 50-60% productivity-gains over 5 years are hard to push further. It's all in excel after all.

Seeking higher productivity has helped shape IT services with efficient processes, tools, and mechanisms, including automation and AI. But the pursuit is endless. Every new large deal, you are still asked - how will you bring your team to half its size in 5 years? There are no real, rather complete, answers. There's some experience, at times. There's automation. There are tools. There's AI. There's God. There's - 'we'll figure out when we get there'. Mostly, there's leap of faith compelled by fear: if we don't offer this, somebody else will, and the deal will be theirs; we have to take the risk... a calculated risk.

Peeling layers, you start looking for people mix - the pyramid. More the junior people, lower the cost - that's one lever you can pull. What about skill? - we'll train them - let's assume for now; and there's AI.

Once you've totally beaten this chain iteratively to its bare minimum cost configuration: # of people - ON-OFF ratio - Pyramid - Productivity - # of people - ON-OFF ratio - Pyramid - Productivity - ... You'd now turn to other costs - infrastructure, shifts, cabs, management, overheads, nickels, dimes, chillar!

For at least a decade now, IT service providers have recognized this need to get out of the cost play and move to value play. Mostly through talking, without really investing in genuine capabilities. So, outcomes have been only in pockets. The problem, I think, is in the nature of the buyer-supplier relationship - the relation is designed to be transactional, and both parties enter with short-term motivations.

And that probably explains why GCCs are emerging as a stronger value creation model.

The story around the picture...

Often when I look at a picture posted by someone, I can't stop myself from thinking how that moment came about, what happened before, what happened after, how that day must have looked like for people in the picture, how they interacted, what was going in each of the minds, what happened! They say 'a picture is worth a thousand words'. But the beauty of life is in what the picture doesn't convey but merely represents - all of which is in memories of those in the picture - each his/her own, fading slowly with time. And after long, the picture remains to serve only as the reminder that the moment truly happened.

Solution Modeling and Pricing Tools in IT Services Companies

I have been part of presales and solution architecting in various IT services firms. One common struggle and frustration in all these firms is with using tools (software, often web-based) for solution modeling and pricing. They keep trying, but just can't get them to work reliably.

The reason may be within the underlying data and the process. And it's complicated.

The sequence of steps to get to a price, in simple terms, is: resource-estimates → resource-loading → costing → pricing. In other words, there's a 'solution' to customer requirements - which is primarily the 'how', but also the 'who', the 'what', the 'when' and the 'where', which would determine the cost of doing it.

(1) Understanding the requirements, depth of solutioning and confidence in resource estimates is the foundation the commercials would be built on. This is also the first input, and the most common source of errors.

(2) The solution - including the estimates, staffing and the delivery model - have to be mapped into the modeling/pricing tool, coz the architect who built the solution is unlikely to be able to do it 'on' the tool; it's a technical and creative process.
On the surface it sounds like a simple porting of data. But this is the point where using the tool starts feeling like a waste of time, especially for large and complex deals. The transferring of data is pretty much manual, and each major or minor change in solution will need a repetition of the whole effort. A lot of tools have capabilities to read excel sheets, but those are rarely seamless, and still require manual effort to get to certain formats each time something changes.

(3) The next input tools require is access to an accurate, exhaustive, complete and well-maintained database of costs. Besides people, there are a whole host of delivery model considerations that determine a lot of the costs, most of which are very context specific. Most companies don't have such databases with all the characteristics listed above. They end up working with averages or ballparks - another source of errors.

(4) Solutioning and pricing are iterative, and may involve numerous rounds of back-and-forth adjustments, even manipulations, to make pricing attractive. Besides for the humungous manual effort it implies, there are things that don't add up, which are easier done in excel spreadsheets.

Errors add up in strange ways.

Conventional wisdom says processes and tools bring greater efficiency and reliable outcomes. But in the case of solution modeling and pricing, the tools seem to represent vicious circles companies don't know how to get out of, yet they are things they can't get rid of.

Companies that have the best handle on the four areas - (i) depth and confidence of solution, (ii) standardized solution modeling, (iii) robust cost database, and (iv) minimum solution meddling for better pricing - also have the most successful delivery, manage risks better, make healthier margins and have sustainable growth.

China to publish less in international scientific journals

Chinese scholars being urged to prioritize domestic journals as opposed to 'international' journals may open up some room. I wonder who'll take it. How wonderful it would be if the Indian context and Indian voice became so interesting to the international journals that they'd want more of it. Journals must reflect the choices of the audience. And audience for research requires not just a mindset, but an economic model where incentives from hyperinnovation are enormous, where institutions reward novelty, where perfection and aesthetics take precedence over fail-fast, and where capital is abundant. People in academia deliberate on the importance of having some top journals from India, with the highest reputation, standards and reach. But do we have the audience? Are they asking for it? Are they ready for it? We probably need the ecosystem first and the rest will follow.

China cools on overseas publication of scientific research

Originally posted on LinkedIn on 08 July 2026

Empathy, Emotional Intelligence - ‘show’ vs ‘have’

Past couple of decades, the discourse on personality, relationships and values has laid a lot of emphasis on empathy and emotional intelligence. While the underlying intent is goodness of heart, and the emphasis intends to condition humans to be good to each other and also to themselves, the outcomes we are marching towards are performative, rather than internalized. We are taught to ‘show’ empathy, not necessarily to ‘have’ empathy. We must ‘appear’ emotionally intelligent, not necessarily to ‘be’ emotionally intelligent. A key aspect to consider here is the vantage point, of course, i.e., the world sees what it sees about you — so “look” the part; and you know what you know about yourself — so “be” the part. The worldly material incentives are tied to performances. The internal incentives (which are?) are tied to being true to oneself. Through parallel discourses on personal branding, looks-maxing, and individualism, we are only validating performance as the means to worldly success, without offering any incentive to inculcate genuine human values. I wonder whether there’s truly a way to do the latter? And what kind of success would it offer? Why does it often take experience and maturity? What if we aren’t truly anything? What if we are all just performing — as best as we can and to the extent our abilities and impulses allow — to being whatever helps us get what we need, want, desire, crave or love?

Let's make some theoretical contributions today

Good morning. As I am sucking this 'heart' in, and starting my day, the thing I am thinking about is "Theory". Ability to theorize is what differentiates a scientist from a mathematician, a statistician, a data analyst or a consultant. While all of them draw 'conjectures' and rely on data to validate them, only a scientist 'hypothesizes', tests, and offers an explanation - a theory - one that works most of the time, preferably 99.9% of the time. Until it doesn't. Until someone, also a scientist, finds a nuance which demands an additional explanation, offers one, which becomes a 'theoretical contribution' - and then, with the padding, the theory claims to go back to 99.9% success rate.

Let me pour the 'heart' out and make some theoretical contributions today.

Originally posted on LinkedIn on 17 June 2026