[knightabu]

Same mistakes Indian IT Service firms already did, trusting third-party AI Service providers across every division and department in companies.

Now Open AI and Anthropic are launching own Service firm/wing for maximizing ROI. Direct Competition. Huge Loss for Indian IT Service Firms.

They paid AI providers to Train own automated competition end to end so much so that they are learnt the gaps and how-to own the market by corrections, private IP Source code access and embedded expertise extraction (stopping short of calling it literal corporate espionage, they got all the know-how and especially for modernizing legacy tech and integrations).

They are untrustworthy especially where IP is involved.

Indian and other IT Firms who did not use private self-hosted AI for important things nor monitored the usage and did not train their employees to think what ( or how much) of our institutional knowledge goes out to third-party are already facing trouble.

[cermicelli]

I couldn't parse all of it, but largely I honestly think software is a sum of it's details you write better software the more details you add to the picture while maintaining simplicity. The art of software is balancing the two.

You can also find this in science, I feel like software is about finding the Gauss’s law for the dozens of electrostatic principles the masses keep coming up with.

AI strips away the need for simplicity by making brute forcing details via verbosity that ruins the need for "good" software, and makes all software by definition unmaintainable since maintainable product as a unit has to be simple enough for a LLM or a human mind to understand.

Currently a human context window is in 100s of billions of tokens, while LLMs seem to max out at 1M.

For anyone thinking but humans can't produce all of the text verbatim, that's the difference b/w humans and machines we can parse and take the most essential parts from 100B token context it's just are speed of prefil and recall is slower. And we memoize learning so if we know X then all variants of X are learnt on the same foundation.

Human learning is so very different from LLMs is so very fascinating as a trad "AI engineer", well some person who has worked and built/shipped ai agents and models at scale.

[knightabu]

I accept AI is a tool for a user who knows the fundamentals, and hope it makes the citizen developers or people who are not trained in programming to get more systems thinking. Its best if it makes more programmers when they want to understand the stuff.

Fun analogy Kinda like power tools like are we tightening a screw using a screwdriver or doing it with a power drill. Case in point there is chance of ease as well as more risk while doing it with power drill.

You are absolutely right, it can be guided to produce code but needs corrections like its too easy to create unmaintainable solutions.

Also to untrained eye without good architecture, it does the job but when one who doesn't have architectural skill will think that's enough and there's no more room for improvement. This cause troubles in their production.

Like if it solves their pain points and makes them think systematically and critically. That is better.

What i don't like is giving much information to 3rd party service providers of AI developer tooling LLMs + Copilot and such, which is causing lot of real market level Risk for Indian IT Service Firms and has started costing jobs and literally erosion of market share because the service providers like Open AI launched their own firms like Deploy.Co.

Smaller companies who didn't know any better using tooling and developing stuff and on growth bringing professionals to fix mistakes has been happening long. There are literally companies who made solutions by Access and Sold it to clients, we literally told them even as competitors to compile the things as programs to avoid from future cases of fraud by their Users who were doing shady things.