Here's what I suggest:

Serious planning. The plans should include constraints, scope, escalation criteria, completion criteria, test and documentation plan.

Enforce single responsibility, cqrs, domain segregation, etc. Make the code as easy for you to reason about as possible. Enforce domain naming and function / variable naming conventions to make the code as easy to talk about as possible.

Use code review bots (Sourcery, CodeRabbit, and Codescene). They catch the small things (violations of contract, antipatterns, etc.) and the large (ux concerns, architectural flaws, etc.).

Go all in on linting. Make the rules as strict as possible, and tell the review bots to call out rule subversions. Write your own lints for the things the review bots are complaining about regularly that aren't caught by lints.

Use BDD alongside unit tests, read the .feature files before the build and give feedback. Use property testing as part of your normal testing strategy. Snapshot testing, e2e testing with mitm proxies, etc. For functions of any non-trivial complexity, consider bounded or unbounded proofs, model checking or undefined behaviour testing.

I'm looking into mutation testing and fuzzing too, but I am still learning.

Pause for frequent code audits. Ask an agent to audit for code duplication, redundancy, poor assumptions, architectural or domain violations, TOCTOU violations. Give yourself maintenance sprints where you pay down debt before resuming new features.

The beauty of agentic coding is, suddenly you have time for all of this.

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sigotirandolas an hour ago | parent | next [-]

To be devil's advocate:

Many of those tools are overpowered unless you have a very complex project that many people depend on.

The AI tools will catch the most obvious issues, but will not help you with the most important aspects (e.g. whether you project is useful, or the UX is good).

In fact, having this complexity from the start may kneecap you (the "code is a liability" cliché).

You may be "shipping a lot of PRs" and "implementing solid engineering practices", but how do you know if that is getting closer to what you value?

How do you know that this is not actually slowing your down?

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dominotw 12 hours ago | parent | prev | next [-]

> Serious planning. The plans should include constraints, scope, escalation criteria, completion criteria, test and documentation plan.

I feel like i am a bit stupid to be not able to do this. my process is more iterative. i start working on a feature then i disocover some other function thats silightly related. go refactor into commmon code then proceed with original task. sometimes i stop midway and see if this can be done with a libarary somewhere and go look at example. i take many detours like these. I am never working on a single task like a robot. i dont want claude to work like that either .That seems so opposite of how my brain works.

what i am missing.

	▲	Leynos 10 hours ago \| parent \| next [-]
		Again, here's what works for me. When I get an idea for something I want to build, I will usually spend time talking to ChatGPT about it. I'll request deep research on existing implementations, relevant technologies and algorithms, and a survey of literature. I find NotebookLM helps a lot at this point, as does Elevenreader (I tend to listen to these reports while walking or doing the dishes or what have you). I feed all of those into ChatGPT Deep Research along with my own thoughts about the direction the system, and ask it to produce a design document. That gets me something like this: https://github.com/leynos/spycatcher-harness/blob/main/docs/... If I need further revisions, I'll ask Codex or Claude Code to do those. Finally, I break that down into a roadmap of phases, steps and achievable tasks using a prompt that defines what I want from each of those. That gets me this: https://github.com/leynos/spycatcher-harness/blob/main/docs/... Then I use an adapted version of OpenAI's execplans recipe to plan out each task (https://github.com/leynos/agent-helper-scripts/blob/main/ski...). The task plans end up looking like this: https://github.com/leynos/spycatcher-harness/blob/main/docs/... At the moment, I use Opus or GPT-5.4 on high to generate those plans, and Sonnet or GPT-5.4 medium to implement. The roadmap and the design are definitely not set in stone. Each step is a learning opportunity, and I'll often change the direction of the project based on what I learn during the planning and implementation. And of course, this is just what works for me. The fun of the last few months has been everyone finding out what works for them.
	▲	hirvi74 10 hours ago \| parent \| prev [-]
		You seem to work a lot like how I do. If that is being stupid, then well, count me in too. To be honest, if I had to go through all the work of planning, scope, escalation criteria, etc., then I would probably be better off just writing the damn code myself at that point.

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bmurphy1976 8 hours ago | parent | prev [-]

Can't upvote you enough. This is the way. You aren't vibe coding slop you have built an engineering process that works even if the tools aren't always reliable. This is the same way you build out a functioning and highly effective team of humans.

The only obvious bit you didn't cover was extensive documentation including historical records of various investigations, debug sessions and technical decisions.