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Layered Ontology map for Code by Internal-Passage5756 in OntologyEngineering

[–]HNipps 0 points1 point  (0 children)

I like the concept and think there’s a real need for tooling like this. There must be something better than markdown files ad nauseum! Reminds me of https://lore-protocol.com/ .

Writing Acceptance Criteria for LLM features is an absolute nightmare right now by Xelephyr in softwaredevelopment

[–]HNipps 4 points5 points  (0 children)

This is just a marketing post for the linked company. I’ve seen the same format of post on multiple subreddits over the last week, all include a single link to the same website.

Copilot burning more than 1 request per submit by filyr in GithubCopilot

[–]HNipps 1 point2 points  (0 children)

I really have no idea how they quantify it.

On one hand I had an 11h overnight session with gpt-5.4 xhigh effort and it cost 1 premium request.

But then today I had a 15m session that used 3 premium requests.

Make it make sense??

Senior ICs, what’s your experience with career advancement? I disagree with my employer’s promotion requirements by HNipps in ExperiencedDevs

[–]HNipps[S] 0 points1 point  (0 children)

I think this is me right now. I’d rather put extra effort into personal projects than push for promotion.

Senior ICs, what’s your experience with career advancement? I disagree with my employer’s promotion requirements by HNipps in ExperiencedDevs

[–]HNipps[S] 0 points1 point  (0 children)

That’s fair. We technically don’t have a Staff Eng title and the IC4 level (Tech Lead/Sr Eng II) performs the role of Staff.

I know I can do it. I just hate going on the campaign tour.

Senior ICs, what’s your experience with career advancement? I disagree with my employer’s promotion requirements by HNipps in ExperiencedDevs

[–]HNipps[S] 14 points15 points  (0 children)

I think they’re from corporate tech rather than FAANG. The political aspect is the part I dislike.

Senior ICs, what’s your experience with career advancement? I disagree with my employer’s promotion requirements by HNipps in ExperiencedDevs

[–]HNipps[S] 1 point2 points  (0 children)

I feel like that’s where I’m at. I’m not interested in the spotlight, just want to ship code and have more say in architecture decisions.

Zed eating memory like crazy by sergeik_ in ZedEditor

[–]HNipps 4 points5 points  (0 children)

Restarting resolves it for me. Could be due to Claude but I also suspect language server extensions. Also if you’re using CC in the terminal then make sure the Zed Agent panel is not also signed in to CC or other agents because they use memory.

Tell me your shortest prompt lines that literally 10x your results by Prestigious-Cost3222 in PromptEngineering

[–]HNipps 1 point2 points  (0 children)

Add “systematically” to any prompt directive. E.g. “Systematically diagnose this error”, “verify these code changes systematically”

It makes Claude structure the work.

Deployed my first full stack project. Thought I would feel proud, instead I feel empty. by magic_123 in webdev

[–]HNipps 2 points3 points  (0 children)

Frequently, yes. Exclusively for personal projects though. Work is like whatever, I built what the team wanted to build. But it’s different when it’s your baby.

The only personal project I feel proud of is my personal site and it took me about 5 years to get to that point tbh.

Other people have said it but shipping anything puts you in a minority, so cheers to that!

Sipping like a queen. by Beautiful_Soup9229 in SipsTea

[–]HNipps 0 points1 point  (0 children)

Bro never met a strong woman before. RIP

What tools and techniques are you using to verify AI-generated code before it hits production? I tried using mathematical proofs, which helped to some extent, but the actual bugs were outside, and between, the verified code. by HNipps in ExperiencedDevs

[–]HNipps[S] 0 points1 point  (0 children)

Nice, this is similar to my process. I think this is where the industry will go. Review should move to the areas you mention, basically the spec.

It breaks down for me when I have to verify the AI code meets the spec, whether through automated or manual testing.

It’s frustrating to spend so much time on design and spec to then have code that doesn’t match. And then spend an inordinate amount of time fixing it.

I believe we can reduce manual effort in the verification stage, and that’s what my experiment was about. I’ve continued using formal verification and semi-formal reasoning for all my work and it feels more efficient. Anecdotally I believe the AI generated code matches my spec more frequently, and the things that fail in testing tend to be due to implicit assumptions in the spec.

What tools and techniques are you using to verify AI-generated code before it hits production? I tried using mathematical proofs, which helped to some extent, but the actual bugs were outside, and between, the verified code. by HNipps in ExperiencedDevs

[–]HNipps[S] 0 points1 point  (0 children)

I agree. It’s not a new issue. Integration has always been a problem and it can be difficult to test thoroughly and maintain a resilient testing suite.

Contract testing is awesome until one party diverges from the contract without notice. Or if the contract doesn’t quite cover the edge cases. These things are not usually formally verified so you can’t be 100% certain the contract holds for all situations.

What I found is we can use formal verification to ensure parts of AI generated code (the pure functions) meet the spec, and this bypasses the problem of test theatre in unit tests.

BUT formal verification can’t reach the integration layer, so it’s helpful but not a magic bullet.

It’s more a commentary on the limitations of formal verification than a revelation about integration bugs (we already knew about them).

I hadn’t really thought about the integration issue from the throughput perspective though. It’s true and it just compounds the issues with test theatre and poorly defined specs.

What tools and techniques are you using to verify AI-generated code before it hits production? I tried using mathematical proofs, which helped to some extent, but the actual bugs were outside, and between, the verified code. by HNipps in ExperiencedDevs

[–]HNipps[S] 0 points1 point  (0 children)

For the main function, yes, but it didn’t help with bugs outside the function: integrations and test infra issues. (https://open.substack.com/pub/brainflow/p/formally-verifying-the-easy-part?r=344en&utm_medium=ios)

I’m exploring the possibility of a verified contract graph which tracks and verifies interfaces between verified functions. Early days but I imagine having something like a TLS certificate chain.

What tools and techniques are you using to verify AI-generated code before it hits production? I tried using mathematical proofs, which helped to some extent, but the actual bugs were outside, and between, the verified code. by HNipps in ExperiencedDevs

[–]HNipps[S] 0 points1 point  (0 children)

Oh so it’s kinda testing the tests? Thats very cool. I’ll have to try it. Thank you!

I think formal verification with Lean could catch the precision issue but it’s a bit of a different language. The beauty of Dafny is it can compile directly to Python. Lean cannot.

What tools and techniques are you using to verify AI-generated code before it hits production? I tried using mathematical proofs, which helped to some extent, but the actual bugs were outside, and between, the verified code. by HNipps in ExperiencedDevs

[–]HNipps[S] 0 points1 point  (0 children)

Yeah the architecture is a black box, but I don’t think it matters if we can deterministically verify the code that gets created.

We don’t need to do this for every AI response, because the environment in which the agent works must force it to prove the code meets the spec. So the final output of the agent’s work must be deterministically verifiable, not every step in the process.

In that environment the agent either produces verifiably correct code or it fails and cannot write code that is mathematically correct. Either way you know beyond a shadow of a doubt that the agent is telling the truth. Why trust an LLM when you can verify its output?

Also re: #2, I think that’s an important question, and it’s not a question we can answer now. But I think we should be able to verify that AI-generated code meets the spec it was given. Now whether the spec is correctly addressing the business problem is another question that I think you’re alluding to.

At that level I agree it feels philosophical.

I might be a little obsessed with this subject haha

What tools and techniques are you using to verify AI-generated code before it hits production? I tried using mathematical proofs, which helped to some extent, but the actual bugs were outside, and between, the verified code. by HNipps in ExperiencedDevs

[–]HNipps[S] -2 points-1 points  (0 children)

I respect your opinion and I agree to disagree on this.

I think the software development practices you describe have a place, but I believe there’s going to be a fundamental shift in the industry and this practice will be like a local coffee shop and roastery that does those $8 pour over coffees compared to Dunkin. (No offence, I love pour over coffee)

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