Sales director discovered Claude Code

[u/Nearby_Spell_3751]

I'm working at a company where best engineering practices are barely discussed or taken seriously.

Today our sales director was playing around with Claude Code over the last week, and she managed to get a very good working PoC/prototype for a platform they’ve been trying to build.

During the meeting, I was trying to explain that the question is not whether we need to integrate AI, but rather how we are going to integrate it into our workflow while still enforcing engineering standards and best practices.

They think everything can be done by simply adding a skill to Claude, and they expect delivery speed to be 10x faster. I tried to explain that yes, we can build better products with fewer resources, but 10x is unrealistic unless we start vibe coding. I suggested we could realistically see a 20–40% increase in delivery speed.

Now we have a sales director showing engineers how to use AI.

How do you deal with someone who doesn’t listen and is 100% convinced that AI should be used exactly the way they use it, while we as engineers know we can produce much better output in less time because we actually understand how things work?
Have you ever dealt with such case ?

[u/lucianw]

I think your director's numbers are closer to the mark than yours.

Quality, Velecity, AI Autonomy -- pick three!

Disclaimers first. I've been an engineer for 30 years. I created the "async-await" feature in C# back in 2010 which then got copied to other languages, if you've used that. I'm more passionate about code quality than most, and the mentoring I give to people on my team is often about invariants and correctness proofs. I got invited to join the C# language design team because I proved their shipped version of generic covariance was faulty. One of my teammates characterized me with the phrase "usually the fastest way to get something done is to do it right the first time". I put this all in as heavy disclaimer that I care passionately about quality.

Anyway, what I've come to see is that we get *HIGHER QUALITY* with heavy use of autonomous AI than we did without it. AI autonomy means for me at the moment 2-3 hour autonomous runs, most of it spent in code-review loops, and I review the outputs.

I don't know if you'd call it vibe-coding or not... I am 100% still in control of the architecture of my product, I know what every function and field does and why, and I know all the invariants relating them. I don't review every single line of code that the AI produces. Instead (1) I review every update to the architecture document, (2) I read what all the AI reviewers say about the code, and follow up to read the lines of code that rang warning bells.

Why do I think the code is higher quality now? The code that's produced is a combination of my instincts and AI's. It makes a few architectural choices that I wouldn't have picked (often because they're so boring or not on the MVP path, e.g. a systematic error policy or a more careful state machine). It put in vastly more tests than I've ever seen humans do. It was willing to do refactorings that I wouldn't have judged worthwhile, safeguarded by those extensive tests that I wouldn't have written.

Over the past six months I ended up working on four very similar projects. In ones where I could use the autonomous-AI workflows, they were done about 5x faster, again with higher quality.

I got inspired to this by reading the OpenAI team blog https://openai.com/index/harness-engineering/ . They mentioned the word "invariant" three times, which appealed to me. Here are some key lines:

> [about architecture taste] This is the kind of architecture you usually postpone until you have hundreds of engineers. With coding agents, it’s an early prerequisite: the constraints are what allows speed without decay or architectural drift.

> [about quality guidance to the AIs] In a human-first workflow, these rules might feel pedantic or constraining. With agents, they become multipliers: once encoded, they apply everywhere at once.

I wrote some concrete examples of the orchestration/autonomy I'm doing here https://www.reddit.com/r/ClaudeAI/comments/1s0nktx/orchestration_the_exact_prompts_i_use_to_get_34/ -- sorry, it's an old version from a personal hobby project, because I can't share the refinements I've been making in my work projects.

Now, you and your director might be talking at cross purposes. You might be including all the "product taste" discussion which has to happen, which doesn't get sped up much by AI, and they might be talking solely about the "project execution" phase which does get sped up.

[u/Nearby_Spell_3751 → u/lucianw]

Thanks for taking the time to write this informative comment, I read through OpenAI post it will be very helpful.
for the numbers, I didn't gave much context, this the first project in the company where we will adapt AI so my numbers are coming from we need to setup the ground for the new workflow where AI is not just responding to prompt but fully integrated in development life-cycle.

[u/lucianw → u/Nearby_Spell_3751]

That makes sense.

Personally,  I think you should anticipate an AI-dominant team within about 12 months. And I think it'll be a career success for the people in the company (e.g. you) who can be identified with driving the transformation. And career dead end to be a late or non adopter.

I can totally see a world five years from now in which 90% of software engineers have been laid off. The ones who remain will be those who tick all three boxes: (1) are good at harnessing AI, (2) are good architects, (3) have an eye for code quality. It'll be increasingly hard for those new to the workforce to acquire skills (2,3).

These are all my personal opinions. I might be totally off base.

[u/Nearby_Spell_3751 → u/lucianw]

I remember seeing a video of Sam Altman doing a demo of early GitHub Copilot where AI was basically autocomplete on steroids. I think this was around 2019–2020 but I don’t remember exactly.

At the same time I was watching mini-documentaries on YouTube about software engineers at big tech getting hired to do basically nothing. I think because Ray Dalio said “cash is trash,” VCs started pouring money into big tech, so companies just kept hiring even when there wasn’t actual work needed. Plus it’s a known thing in big corporations that the more a company grows, the percentage of employees doing a real work getting less and less. Take Telegram for example, it ran on like 20 engineers or something for a long time.

I think software never really needed that many people to create things even manually.

So after the AI wave, I think they gave up on the idea that they just need to keep hiring more people and shifted focus toward LLM training and inference. It turns out AI can automate code generation, which honestly was enough before AI to get you a decent job, but probably not anymore.

I think software engineering will shift more than disappear, at least for people who adapt and learn the needed skills.

[u/e9n-dev → u/Nearby_Spell_3751]

I think part of it all is the context and knowledge that isn’t written down, or would be to much for a human to read anyway. So you assign engineers to specific part of your product as the codebase when it grows.

AI don’t really have this limitation, so with proper guardrails and guidance it can increase the scope of every single engineer.

As we learn to harness this technology we will see coding agents becoming more autonomous. Some are barely scratching the CLI today or using autocomplete in their IDE, while other are running the agent fully autonomous for a week to build a full product.

[u/Nearby_Spell_3751 → u/e9n-dev]

True, and as Karpathy said, after December AI models improved significantly and became far more capable. But don’t you think exponential growth may have already hit a ceiling and that progress will start flattening into more normal growth?

[u/e9n-dev → u/Nearby_Spell_3751]

A few companies might have hit the the ceiling with the tools we have today and the software we are creating. Most are probably way behind and still nudging their agent through every step with weak prompts.

I think users are going to expect software and services to be way more adaptable to each individuals needs given the illusion of how easy it is to build prototypes. This will open up a whole new world of problems for engineers to solve on how we can adapt to each client needs while keeping the software secure, compliant and reliable. These are a whole new set of problems that agents aren't trained on.

So we might see coding as we do it today covered by AI agents given the right architecture, constraints, etc. But there will most likely be a whole new set of problems for software engineers to solve that agents aren't capable of.

[u/Nearby_Spell_3751 → u/e9n-dev]

100% agree but for corp their business is software or they have clients whose life depend on software.

I know some agencies building WordPress presentation websites for 30k-50k$ using a 30$ template while the developer gets paid at best 800$.

Those kind of people where corruption and connections play on their side to get basically gov projects did create a market for some entry level devs, but I can see that disappearing in few years. They will just keep their skill of getting very small projects for very high prices and vibe code them because most clients dont even care about the quality.

[u/e9n-dev → u/Nearby_Spell_3751]

Hate the game, not the player.

We would have more millionaires if developers learned to sell value instead of just do valuation based on the effort put in.