Title: Is AI making mid level developers do more testing and grunt work instead of actual development?

[u/Nearby_Sky_6098]

​

Lately, I’ve been thinking about how AI is changing my day-to-day work as a senior engineer.

On paper, AI is supposed to make development faster. And yes, it can generate code quickly, especially when working with an unfamiliar or large codebase. But in practice, I feel like I’m spending less time actually writing and designing software, and more time doing grunt work around AI-generated code.

My workflow increasingly looks like this:

- Figure out what needs to be done

- Explain the requirements to AI

- Review the generated code

- Fix the parts AI misunderstood

- Review it again

- Test edge cases manually

- Verify integrations

- Deal with production issues if something was missed

- Then become even more cautious with the next AI-generated change

The biggest issue is trust. After fixing so many bugs or production issues, I simply can't trust it. As a senior engineer, the responsibility is still mine if something goes wrong.

So instead of AI completely reducing my workload, it sometimes feels like my job has shifted from writing code to constantly reviewing, validating, testing, and correcting code generated by AI.

Ironically, I feel like I'm doing more testing and verification than actual development now.

Is anyone else experiencing this?

Do you think this is just the current phase of AI-assisted development, where we still need heavy human validation? Or is the future role of a senior engineer increasingly becoming someone who manages AI-generated code and acts as the final quality gate?

Curious how other experienced developers are handling this.

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[u/LogicalPerformer7637]

Maybe instead of "explain the requirements to AI" you should do "design the solution" and then let AI implement it.

use AI as partner/assistant, not slave who does all the thinking instead of you.

It is easier/faster to design your own solution (optionally with help of AI) and let AI implement it, than letting AI implement something and then spend lots of time to fix it.

[u/skamansam → u/LogicalPerformer7637]

This is it. I design the solution, have the AI give me a plan and write out that plan as a checklist. Then I refine the plan with the help of the AI. Then I let the AI do the grunt work of writing it out WHILE I WATCH. A lot of times I have to stop it in the middle because it is doing some stupid thing. Once its done, I review the code. My role now is basically just engineering and not doing code monkey stuff.

[u/forever-butlerian → u/LogicalPerformer7637]

If "AI" does the "thinking", who is the master and who is the slave is the reverse of what you seem to imply.

[u/alvarier]

Yeah, I think were moving more towards creating a layer of tests, and the code being more of a black box.

For several use cases it simply doesn't matter if the code is pretty or not, it's more important that it solves the problem at hand - and implemented fast.

Perhaps we keep the prompts that generated the code, so we can quickly rebuild if stuff fail.

[u/canarydev]

im spending more time doing upfront design on architecture, creating very explicit rules, setting up tests, and creating very clear cut contracts that AI has to follow in the actual implementaiton.

the trick i think is that the contract has to be an artifact. schema, protobuf, typed interfaces, whatever. something that can fail the build and lives outside the diff. otherwise the model just edits the schema and "passes". the goal isnt to review AI output harder. its just to make correctness an executable constraint so that the model has less room to be "almost right" and tilt me

[u/Hexamonium]

Even before LLMs were a thing, what developers should have been spending most of their time on was testing. I would venture to say as much as 80%. The job of QA engineers is not to find bugs in your code but to not find them.

I get the frustration though. The fun part is to think though problems and solve them by writing code. It really sucks that LLM is removing the fun part and leaving the hard part on you. So, basically, it's all crappy parts now. Tough luck. Join the rest of us. Your job is not supposed to be fun. You are exchanging your time for money to solve someone else's problem. If you want to have fun, get a hobby.

[u/geekichu]

SWE here, retired. have done 3 projects now, 100% A.I., a multi-process crypto wallet, and two 3D, first-person, open-scene, client-server(authoritative) games.. .. over time, have collaborated with A.I. to create architectural docs, planning docs, progress docs, test suites, etc. i request a feature, we compose a STEP/planning doc, it fires off subagents for new tests, for implementation, for architectural review.. i get notified, i run through some of my own targeted manual tests, rinse repeat. over time we have developed built-in debugging aids - these are easy, quick ways to copy/paste different types of data (JSON), and between the code, the pasted data, and my description of symptom(s), it always finds any issue.

i make sure the overall project is well-architected and organized, but i have yet to look at the code.

[u/Common_Dream9420]

Yeah this matches exactly what I've been seeing. The surface area of unverified code goes up, not down. AI writes the integration layer fast but the verification burden is still fully human, and it's harder because you didn't write it so you don't have the mental model of where it'll break. Honestly I think the "senior engineer as final quality gate" framing is just accurate, not a phase. The tooling will get better but the accountability gap between "code that looks right" and "code we actually trust in prod" isn't something AI closes on its own.

[u/martinbean]

Person uses AI to ask about AI.

[u/Nearby_Sky_6098 → u/martinbean]

We are getting addicted to ai for simple things also

[u/forever-butlerian → u/Nearby_Sky_6098]

the solution to being a crystal meth addict isn't doing more crystal meth

[u/private-peter]

I actually find that AI makes testing the edge cases a lot easier.

I also think it can make testing and verifying integrations easier. It does require an investment in getting all of the integrations working in a development environment. But IMO that's worth doing.

[u/No-District2404]

Exactly, it’s like they assigned to you a junior and told you to train them and you’re responsible from the generated outcome. It’s definitely more tiring than just writing the code by hand

[u/RowbotWizard]

I think testing and monitoring are certainly more important than ever.

Consider what happened with infra as code: instead of updating live servers, we replace them with new ones. Pets turned into cattle.

We’re starting to do more code herding now.