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What Is Software, and Will LLMs Replace It? - Strumenta
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What Is Software, and Will LLMs Replace It?
Written by
Federico Tomassetti
Federico Tomassetti
in
AI, Language Engineering, LLMs, Reflections, Software Development
23 June 2026
Threads
BlueSky
Table of contents
We’ve all been using LLMs for a while now, and we’ve all been impressed by them. At some point it is natural to ask the question: is this it? Is this what is going to replace software? Are we just going to talk to computers from now on, describe what we want, have it appear, and skip everything in between?
I don’t think so, but it’s tempting to believe it. Type "show me sales for the last five years" and you get a chart. Ask for the slide deck and you get the slide deck. Done. Who needs SaaS anymore?
But that misses what software has been doing for us all along. In my opinion, it remains relevant in four ways:
Data organized and normalized.
Consistency enforced.
Things visualized in ways that help us see patterns.
Processes guided step by step. Years of accumulated know-how about how to do a job right, captured and made executable.
So yes, LLMs are showing us something genuinely useful: that interfaces can be far more flexible than we assumed. But I don’t think that’s the same as software disappearing into conversation. Let’s look at why.
What does software actually do?
Let’s ground this in something concrete: a CRM. Yes, CRMs are boring as hell, but every B2B company has one and we are familiar with them. And, let’s face it, most of the software we use does not have to be glamorous. It just has to do some boring job for us.
It organizes data into a structured, queryable, normalized form.
An opportunity is not a blob of text. It is a record linked to a company, which has contacts with phone numbers and emails, a lead-source field that feeds your marketing attribution, and a chain back to past contracts. That structure is what lets you ask "which opportunities came from referrals and closed above €50k in the last six months?" and get an answer you can trust in milliseconds, not a paragraph that sounds plausible.
Yes, just writing free-form notes would be more convenient. But without the discipline of organized data, we would lose the possibility of doing most analysis. Also, we are glad our colleagues have to put information into a standard format, right?
It enforces consistency and integrity.
You cannot create an opportunity without first creating the company it belongs to. You cannot delete a company that still has open contracts. The system stops you, or cascades the deletion through every linked record in a defined order. These are the rules that keep your data from turning into garbage six months from now. You know, giving up immediate gratification for a better future.
It enables visualization and filtering.
Purely textual interfaces do not work very well for everything. We need to see data, notice outliers in a graph, and spot patterns at a glance. For that we need visualizations, and also filtering.
Ask an LLM for a sales chart and it’ll happily draw you one. But where did the numbers come from, and will it give you the same answer next month?
It guides processes .
It encodes your company’s terminology, its sequence of approvals, and the little pieces of domain savoir-faire that took years to get right. "You can’t mark an opportunity as won until the contract is attached," for example. That’s not friction. That’s rules. You may not like them, but you would certainly like your colleagues to follow them if you need to take over some tasks from them.
A historical side note: SQL and the dream of plain English
There is an old dream behind all this. Back in the 1970s, when IBM researchers Donald Chamberlin and Raymond Boyce designed SQL, part of the pitch was that it would be simple enough for non-programmers to use directly. The idea, repeated in talks and papers of the era, was that you wouldn’t need a developer standing between you and your data: a manager could just type out what they wanted in something close to plain English and get an answer back.
The often-cited illustration was something like a home cook typing in the ingredients they had on hand and getting back a list of recipes they could make. It sounded like the end of "the technical layer" getting in the way. Fifty years later, we are still trying to make that promise true, and still discovering that the hard part was never only the interface.
Why can’t an LLM alone replace business software?
Strip away the chat interface and ask: where does an LLM keep its data? It doesn’t. A model has no schema, no foreign keys, no transactions, no constraints.
In many agent setups, the "memory" is a collection of files or notes that the agent reads and writes between sessions. That can be useful, but it is not a database. Notes don’t enforce that an opportunity has a company....