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manan
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manan
@builtin2005
engineer. currently learning ai and how to code in between claude limits
Present Katılım Nisan 2022
199 Takip Edilen289 Takipçiler

thats how it always was. The better ur plan, the better results u r going to get but getting to a good plan is the hard part. It means you actually understand the system you are building, not just the surface. Otherwise you are just asking it to execute something you do not fully grasp and it will try anyway
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GPT 5.5 + Codex with /goal the first setup that turned my work 100% administrative, and I'm getting good at it. There are two outcomes:
→ A: my plan is good → GPT nails it
→ B: my plan is bad → GPT tries anyway → it fails but minimizes it
And this is the catch: once you're used to detecting the apologetic "everything is fine" tone of case B, you can just revert and pivot to another idea. In particular, it seems effective to ask:
"Do you honestly think this is production ready?"
If there is anything smelly, GPT 5.5 will say so, allowing you to evolve towards a better design.
Concrete example:
> Asked it to implement an in-kernel GC for Bend2.
> It did exactly I asked, and declared success.
> Code grew too much, so I suspected and asked:
> "Would you honestly merge that?"
> It then replied in the lines of:
> "Ehh... actually, this kinda sucks due to "
I then investigated and, yes, my idea was bad. Doing GC at that point requires us to track roots coming from many places, which is a massive, fragile endeavor. It is just a bad approach.
So, I reverted it, chatted a bit more, then choose another path: use linearity information (which we already have) to free pattern-matched constructors, with small freelists.
A few minutes later, it came back with a working implementation that completely solved the issue. I asked again:
> "Would you honestly merge that?"
To which it replied (verbatim):
> Yes, I’m confident enough to call it production-ready for merge, subject to normal review. Not “impossible to break,” but the specific requested invariant is implemented, audited, tested, and bench-checked.
When GPT uses that kind of tone, it is very, very likely that whatever it was done is actually solid, robust and trustworthy, and it knows it. I still inspected the code manually and, indeed, it is solid. Doesn't mean fail-proof, but certainly *much* better than before, and mergeable.
That's what I like the most about this model: if your plan is solid, it will almost certainly succeed at implementing it. It only fails if the plan itself is poor, which will cause it to desperately attempt to fit a circle in a square, fail, and be too embarrassed to admit. If you master how to detect which case happened, you can get it to produce a lot of constructive, not destructive, outputs...
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yeah that’s usually how it goes lol. keeping the MCP layer pretty opinionated for now. instead of letting the agent run raw SQL, I’m exposing safer actions like create resource, add fields, enable ownership, inspect schema, etc. goal is to make the agent build the backend without giving it too much rope
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@builtin2005 This sounds fun tbh — these “just exploring” projects usually turn into something way bigger 😄
Curious how you’re designing the MCP layer for agents — more generic or opinionated?
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starting a small side project for fun
basically a local backend that AI coding agents can control through MCP
planning to add simple table creation, CRUD APIs, auth, file storage, a tiny SDK, and maybe a basic dashboard later
nothing serious yet, just seeing how far I can take it
codex is working hard as ever
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@BenjaminDEKR maybe occasionally asking them to enter their password when using the app might help more. Recently i saw this on Signal app where it frequently asks u to enter the inapp password to check if u still remember it
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small update on this local AI-controlled backend project
got the first real slice working now:
- local Postgres
- resource/schema creation
- auto CRUD APIs
- email/password auth
- user-owned resources
- tiny TS SDK
- MCP server connected to Codex
Codex can now create backend resources through MCP instead of writing SQL directly.
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manan retweetledi

One thing I miss about the 90s and 2000s and the part of the 2010s is that every 2 years tech just got better. Games looked remarkably better, the systems you would buy would be significantly better.
Honestly at this point I can barely tell the difference, performance wise, for the last 5 years.
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@Tazerface16 whaaaat? does that mean the billion dollar idea my chatgpt gave me is fake?
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@GregKamradt just wanted to ask if its possible to run the agent overnight if i have a plus plan ?
wont it run out of limits or something ?
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I'm giving away a $2,100 Gaming PC with Paradox Customs!!
To Enter:
• Follow me and @Brparadox
• Like and Retweet this post
• Tag 2 friends
Additional Entries Here: gleam.io/HPGEi/faide-x-…

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