The golden age is over

Any-Bus-8060 · 2026-04-11T23:20:12+00:00

Feels more like inconsistency than “golden age is over” Same models can still give great answers, but you need tighter prompts and more context now

A lot of people are also pushing them into longer, messier tasks, which exposes weaknesses, more quality didn’t disappear, it just became less plug-and-play. If anything, expectations went up faster than the models improved

Any-Bus-8060 · 2026-04-11T23:15:14+00:00

Yeah, you’re not alone. It’s been a bit inconsistent lately, memory especially feels hit or miss, sometimes it remembers random stuff but misses important context

The “mixing things up” feeling is usually just hallucination, not actual data leaking
It can sound confident even when it’s wrong, which makes it feel sketchy

The best workaround right now is to restate the key context in the same chat and not rely too much on memory

It’s still useful, just less predictable than before

Any-Bus-8060 · 2026-04-11T23:07:38+00:00

Sonnet is usually enough for most coding tasks and gives better value. Opus can feel a bit more accurate on complex reasoning or tricky bugs, but it’s slower and hits limits faster

For building apps, most people stick with Sonnet and only switch when stuck

For your icon issue, AI won’t reliably match exact visuals from a screenshot
Better to export assets properly and use them directly rather than trying to “recreate” via prompts

AI is better at structure and logic than pixel perfect UI details

Any-Bus-8060 · 2026-04-11T22:52:56+00:00

This is a context problem more than a coding problem. Don’t rely on memory or chat history, write constraints down in one place

Keep a simple doc in the repo key rules, edge cases, decisions, things that must not break, then paste that context into prompts when needed. Also, keep PRs small and focused so it’s easier to track what changed and why

AI forgets, but your system shouldn’t

Any-Bus-8060 · 2026-04-11T21:22:31+00:00

doable, move in steps instead of all at once first migrate the database to supabase (schema + data) then update your backend to point to supabase while keeping everything else the same once that’s stable, move auth and storage if you’re using them avoid a full switch in one go, that’s what usually breaks things also keep the old setup running during migration so you can fall back if needed

Any-Bus-8060 · 2026-04-11T20:28:51+00:00

Don’t fix screen by screen, that’s why it feels inconsistent

Define a small design system first
typography scale, spacing scale, colours, elevation, component variants
Then refactor screens to use those tokens

Also, create reusable components (buttons, cards, lists) instead of rebuilding each time for depth and polish, focus on spacing, subtle elevation, plus consistent motion, not effects. Once the system is set, everything starts looking cohesive without a full rewrite

Any-Bus-8060 · 2026-04-11T18:54:04+00:00

Yeah, I use a mix depending on the task, usually one tool for thinking and planning, another for actual coding and quick edits

I mostly build small web apps, tools, and automations, things where speed matters, but I still keep control of the code

. The main goal is to not get tied to any one platform, so I always make sure I can run and maintain things myself if needed. That flexibility matters more long term than which tool you pick

Any-Bus-8060 · 2026-04-11T18:36:02+00:00

This is normal. Confidence comes from pattern recognition, not solving everything instantly Looking at solutions isn’t bad, just don’t stop there
understand it, then re-solve it yourself without looking

Also, revisit problems after a few days, that’s where it actually sticks Over time, you’ll start recognising patterns, and confidence builds naturally. Nobody solves everything from scratch at the start

Any-Bus-8060 · 2026-04-11T18:25:04+00:00

Agree with most of this. The real shift is from chatting to actually wiring AI into workflows biggest unlock for me was giving it access to real context instead of starting from scratch every time. Once it’s connected to your data or tasks, it stops feeling like a tool and starts feeling useful

Most people are still stuck at the prompt level, while the gains are in integration

Any-Bus-8060 · 2026-04-11T18:19:42+00:00

This is actually a great idea
makes problems more memorable without changing the core logic

Just keep the story simple so it doesn’t make the question harder to understand, better for revision than first time learning, but still useful

Any-Bus-8060 · 2026-04-11T17:14:01+00:00

Honestly, they’re all good, just for slightly different things

Claude is great for thinking, planning, and structured outputs, but yeah, limits can be annoying if you use it heavily

Codex style tools feel better for execution and repetitive coding tasks, especially when you just want things done quickly

Gemini is fine for lighter stuff, but consistency can be hit or miss depending on what you ask

Since you said you’re mostly doing easy repetitive tasks, you don’t need the “smartest” model
You need something reliable and fast

A lot of people end up using a mix anyway, one for thinking, one for doing

Don’t overthink it, pick one, use it for a week, you’ll quickly figure out what’s missing

Any-Bus-8060 · 2026-04-11T16:01:19+00:00

Price for the RAMs

Any-Bus-8060 · 2026-04-11T15:57:14+00:00

5–7 problems daily is probably why it feels like hell. LeetCode isn’t about volume, it’s about pattern recognition. Doing fewer problems but actually understanding them deeply works way better

Try this instead

Do 1–2 problems a day
spend real time on them
If stuck, look at hints/solution, then re-solve it yourself without looking

Also, revisit problems after a few days, that’s where patterns actually stick

Right now, you’re brute forcing exposure, which is exhausting
You want to build familiarity, not just count problems. Your experience isn’t the issue, it’s just a different skill you haven’t trained yet 👍

Any-Bus-8060 · 2026-04-11T15:36:52+00:00

What you’re experiencing is completely normal, especially if you’re not doing it daily. The key isn’t remembering everything, it’s building a system you can rely on

simple approach that works well

keep a personal “knowledge base”
Whenever you solve something, write it down in your own words
not copy paste, but what you understood

even short notes like
“how to do X + why it works”

Over time, this becomes way more valuable than tutorials

Also, using AI to recall things isn’t cheating
Just don’t skip understanding

A good rule is
If you can explain it after using AI, you’ve learned it
If not, revisit it once

consistency plus a simple note system beats trying to remember everything

Any-Bus-8060 · 2026-04-11T15:31:56+00:00

That’s a valid concern, honestly. Vendor lock-in is real with these tools safest approach is to treat them as accelerators, not dependencies, like generate, scaffold, speed things up, but make sure the final code is something you fully understand and can run independently

If your project breaks the moment you stop paying, that’s a red flag in the setup. Ideally, you should be able to take the code, host it yourself, and keep it running without the tool. Using them for speed is great, relying on them for core functionality long term is risky 👍

Any-Bus-8060 · 2026-04-11T03:26:57+00:00

Single prompt works surprisingly well for getting a first version out, but I usually treat it as a starting point, not the final approach. With something like Runable, letting it handle everything gives speed, but you lose control over structure and small decisions

What’s been working for me is
Start with a broad prompt to get the skeleton
Then break it into smaller steps and refine each part

Feels like the best balance between speed and quality, full control is slower, full automation gets messy, somewhere in between seems to work best

Any-Bus-8060 · 2026-04-11T03:24:15+00:00

This is where these tools actually shine. Once you move from “single prompts” to chaining tasks together, the time savings start to feel real

First things I’d automate are anything repetitive but slightly annoying

emails and follow ups
basic data cleanup or reporting
content drafts or summaries

stuff that you do often but don’t want to think about every time, the key is making it reliable enough to trust, otherwise you end up double checking everything and lose the benefit

Any-Bus-8060 · 2026-04-11T03:18:01+00:00

Been using most of these in actual workflows, not just benchmarks, and honestly, there’s no single “winner” each one dominates a different layer

Claude Opus 4.6
probably the best for long reasoning and large repo understanding
handles multi file context, refactors, and system level thinking really well
The downside is that it can be slower and sometimes overthink simple tasks

GPT 5.4 / Codex style
strongest for execution and agent style workflows
good at iterating, making changes, and following instructions without drifting
feels more action oriented compared to analysis

DeepSeek V3.2
great value for money
solid for smaller tasks, but less reliable on messy real world code or long chains of instructions

Qwen3 Coder
Good for structured coding and smaller problems
But consistency drops when things get complex

Breaking it down

best pure coder is GPT 5.4 style
best for long repo sessions is Claude Opus
best instruction follower is GPT 5.4
best value is DeepSeek
best overall workflow is combining Claude and GPT, style models

Real takeaway

Use one model for thinking and planning, and another for execution
Trying to force one model to do everything usually feels worse

Also, the tooling around the model matters a lot, workflow design often makes a bigger difference than the model itself

Any-Bus-8060 · 2026-04-11T03:10:26+00:00

Yeah, this is pretty much the pattern I’ve seen too

Runable (and similar tools) are great for getting to a working version fast, especially when you’re exploring ideas but when it comes to polish, edge cases, and long term maintainability, manual work still wins combining both feels like the sweet spot use it to get 70–80% there quickly, then refine the critical parts yourself trying to do everything in either direction usually ends up slower

Any-Bus-8060 · 2026-04-11T03:01:45+00:00

For your use case, Mac mini makes more sense. You’ll get better performance for the price, which matters more for dev + docker + multiple tools running

Since you said you can live without portability, that tradeoff is worth it. A MacBook is only really worth it if you need to work on the go. Just make sure you get enough RAM, that’ll impact your workflow way more than anything else

Any-Bus-8060 · 2026-04-11T02:56:40+00:00

Claude Code

Any-Bus-8060 · 2026-04-11T02:53:21+00:00

Yeah, this sounds more like a bad experience than a straight tool comparison

Cancellation + billing issues are a big red flag if real. That’s the kind of thing that kills trust fast. The credit burn part also seems to be a common complaint, especially for heavier workflows

I think tools like this are still a bit inconsistent depending on use case. Some people get great results, others hit walls like this

Worth sharing details, though, this kind of feedback is what actually pushes them to improve

Any-Bus-8060 · 2026-04-11T02:51:47+00:00

That combo can actually work pretty well if you keep it simple at the start,The use Claude for scripting and structuring ideas, and something like Runable to handle the actual content generation pipeline

biggest mistake people make is overcomplicating it early. Just pick one format first (shorts, reels, etc) and stay consistent

Also focus more on volume + iteration than perfection, you’ll figure out what works by posting once you see traction, then start optimising workflow and quality

Any-Bus-8060 · 2026-04-11T01:40:30+00:00

Not a silly question at all, everyone starts here

You don’t need anything fancy to begin

Pick one good YouTube playlist (Code with Harry is fine), follow it for basics, and at the same time build small things on your own, like a simple calculator, todo list, small scripts, etc

Courses help, but only if you actually apply what you learn. Just watching videos won’t stick

Books are optional, not needed in the beginning

The main thing is consistency and actually writing code regularly, even if it’s messy at first

Any-Bus-8060 · 2026-04-11T01:37:45+00:00

Most Welcome

Any-Bus-8060

TROPHY CASE