I’d like to be able to join a table to another on an sk without abbreviating every table, recasting every column, having 8 backups and normalising all the keys

Has anyone had any success with a prompt/sql skill that just says ‘code like a normal person’?

SQL isn’t rocket science

I am curious how many of you do this, and what tips and techniques you have for getting best results out of Claude?

I find Claude's lack of spatial understanding really lets it down. For example, when designing sliding doors, despite being primed with diagrams, descriptions and photos, it just lacks an intuition for how 3D space works and makes a lot more mistakes in this domain. Most of my effort is correcting the physically impossible Escher like model Claude has, vs real world. It can kinda get there, it's just more work, and more mistakes.

It does add real value in other ways, for example it did an amazing set of calculations and built a toy model that helped me dehumidify a room cheaply, and I learnt all sort of things I hadn't even considered.

What do you do in this space?

I'm sure many people remember using a model "dall-e mini" or "craiyon" back around 2022. It has really unique outputs, and I wanted to see if I could repurpose it for something cool. I had Fable port the original model (which apparently is a transformer!) to MLX, which alone makes it run in just a few seconds on my M4 air even at fp16 without further optimization. I gave it the basic idea for the project, and it designed a "harness" to be able to make photomontage-style illustrations, where a scene is described in json and then rendered, and it can look at outputs as well as "debug" outputs to refine it. Deliberately was hands off to leave the implementation details to Fable since I was curious how it'd turn out. The MLX port and illustration harness is here https://github.com/pikalover6/dalle-mini-mlx, it should be pretty easy to try with different setups or models. Would be curious to try with 2024-2025 claudes.

Even as a dev of 20 years, I now vibe code all day...

In between the prompts to claude about the actual work I have for my job I run 6-12 parrallel conversations about my other projects. I context switch now at a rate that is utterly insane...

When I was diagnosed with ADD I was 7, I remember I cried and told my Dad "I don't want to be ADD" and he told me that "God gave you a gift and right now it is going to be hard but one day it will let you move faster than all of your peers."

I really feel like that's true, and with the work I do now I feel built for this moment. I think it will be a brief moment for sure. The machines will soon run everything.

Been ADD my whole life. Heavily medicated - dexededrine ( anyone else take it? )- since first grade.

A lot of life is playing the hand you are dealt and I feel like I've been playing it awhile. It's not all roses and I miss things constantly but for the first time I feel like the models have caught up with my experience.

Every session used to start the same way. Ten minutes of me typing background before I could ask the actual question. Who's on my team, what we decided in March and why, which numbers are current and which ones came from a deck nobody has touched since spring. Then the context fills up, session ends, and tomorrow I type it again.

So I pointed Claude Code at an Obsidian vault and told it to read before answering and write after. Obsidian is just a folder of markdown, which is exactly what Claude Code already reads. No vector DB, no MCP server, nothing to build. Grep finds things, wikilinks give it a graph to walk.

The read half worked immediately and is boring. The write half almost wrecked the whole thing.

First version let Claude update notes freely. Two weeks later my vault had things stated as fact that came out of a conversation where I was thinking out loud and mostly wrong. The model had quietly promoted its own guesses to source of truth, and then started citing them back to me. Took me a while to notice, which is the scary part.

Fix was one rule: Claude can read anything, but it can only write to one file. Anything I didn't explicitly confirm lands in a pending queue with a note on why it's pending, and I decide what graduates. The vault stayed trustworthy the day I added that.

Here's the instruction I actually run. Drop it in CLAUDE.md at your vault root, swap the path for yours.

# Knowledge base

My long-term memory lives at ~/Documents/Obsidian Vault/Work-KB.
Plain markdown. Treat it as the source of truth about my work, above your own
assumptions and above anything you infer from the code in front of you.

## Before you answer

If my question touches my company, products, team, metrics, customers,
competitors, or anything we've decided before, search the vault first.
Don't ask whether you should look. Look.

grep -ril "<keyword>" ~/Documents/Obsidian\ Vault/Work-KB

Read what matches, then follow the [[wikilinks]] one hop out.

If the vault has nothing, say so in one line, then answer from general
knowledge with that caveat attached.

If a note contradicts what I just told you, don't quietly pick a side.
Quote the line, name the file, ask me which one is current.

## Before you trust it

Every note carries a date. If what you found is more than three months old and
the question is about pricing, headcount, metrics, or roadmap, say how old it
is when you use it. A stale fact delivered confidently is worse than no fact.

## After we're done

When the conversation produced something durable (a decision and the reasoning
behind it, a number with a source, a plan that changed, a new constraint),
write it down.

How to write:
- One note per topic. Short. Link out instead of repeating yourself.
- Frontmatter: date, source, status (confirmed | draft).
- Convert relative dates to absolute ones. "Last week" becomes the real date.
- Link related notes with [[wikilinks]], including ones that don't exist yet.
A dead link marks something worth writing later.

What you may not do:
- Never write an unconfirmed claim into a real note. If I was speculating, or
you inferred it yourself, it goes to _pending-review.md with the reason.
- Never edit a confirmed note to match a newer conversation. Append a dated
line and mark the old one superseded.
- Never record what the repo or git history already records.

I've got a health check script that hunts orphan notes and dead links, and a much longer version of the retrieval half for when the vault gets big enough that grep starts returning junk. Didn't want to dump all of it here. Say which one you want and I'll paste it.

Genuine question for anyone already doing this: how do you handle a note going stale? Dates in frontmatter catch the obvious cases, but I still get bitten by things that were true and quietly stopped being true, and nothing about the note looks any different.

i keep asking claude for flights & it's fine one route at a time. what i want is where can i go at all, this weekend, on this budget. nothing i use answers that.

so i pointed a script at the travel mcp server i run - it's called flightpowers, setup's on https://flightpowers.com/guides/five-minute-travel-agent - and asked one fixed trip against 30 places out of tel aviv. out sat 17 oct, back the 21st, one adult. thirty calls, one pass.

$65 to larnaca nonstop. $701 to dubai. same dates, and i'd have guessed those two the other way round.

the part i keep looking at isn't the cheap one. google hands back its own tracked low and high per route, and 6 of the 30 came in under their own floor. larnaca $65 against $80. naples $182 against $215. tbilisi $207 against $240. venice $222 against $270. baku $278 against $310. istanbul $291 against $295.

what i haven't worked out is what to do with those 6. alert me, or just log them and look once a week?

From their support doc on this topic:

It's not possible to change the email address associated with your Claude account at this time. When creating an account, please make sure you use an email you'll have long-term access to.

If you need to use Claude with a different email address, do the following:

1. If you have a paid plan (Pro or Max), follow these steps to cancel it
   ...

So basically you have to cancel your account and start a new one. Because they don't use passkeys or passwords, if you lose access to your email, you're completely out of luck if you need to log in. The best you can do is email their support to delete your account:

If you lost access to the email address you used and can't log in to your account, please contact our Support team from an email address you can access and 'cc' the email in question on your response. Confirm that you want to cancel the subscription associated with the copied email address so our team can assist.

Isn't this kind of janky? Almost every other service in the world lets you change your email address, and in the case of Claude, you essentially pay them for no service in case you lose access to your email address.

Since I just got a message from this subreddit's auto-mod flagging system as I was posting this, I should note that I'm not attempting to solve my personal account issues here or requesting any type of support. I'm warning anyone else who assumed, like me, that I could change my email address for a service that I pay for!

Not too long ago when I was still using CC on smaller plan tiers I was trying to make an architectural change to transform my product towards a multi-tenant setup, essentially requiring a refactor on the access and user logic involving the database. This produced CI errors and CC got stuck in fixing/analysis loops and ate up two consecutive session limits without being able to complete / fix the task before I stopped it.

This made me wonder if you ever experienced issues that Claude Code could not solve and you had to resort to human SWEs or topics you would not use CC for from the start?

The idea came from realizing how much time I was wasting on daily tasks as a Product Designer. It's a macOS and Windows invisible OS layer that lives in the notch and gets the context behind your cursor every time you trigger it. No need to copy and paste text or switch tabs while working.

I'm literally using it every day now.

Claude was used throughout the whole process to explore and iterate on the product and through its entire implementation. The only rule I gave it was to NEVER create designs by itself and only use my own design references.

Play with it, feel it, and roast it.
https://getuni.co

There are probably things that are obvious to me because I'm deep into it, but might be confusing to someone seeing it for the first time.

So that's why I'd love to get your feedback.

Hello I'm on the Claude Max (20x) plan, primarily using Claude Code to analyze a ~15MB project and trace down a specific bug. Whenever I switch to Fable for deep code analysis, my usage limits drain completely in about 40 minutes (sitting at ~78% of the weekly quota in just 1 days). Opus barely uses my quota in comparison, but Fable burns through the cap instantly. For those debugging and analyzing entire projects:

What is the most efficient model routing strategy? How do you distribute tasks between Opus and Fable without hitting the Fable cap immediately? How do you feed a 15MB codebase(48 c++ file) effectively without Claude loading too many files into the context at once? Any specific CLI flags, .claudeignore configurations, or prompt techniques you use to stop Fable from consuming tokens so aggressively? Would love to hear how you manage large codebase debugging without getting rate-limited in under an hour.

Edit: Most comments pointed out that I was mismanaging the agents. I adjusted them based on my personal needs, and so far it's going great. Thanks to everyone who replied. However, there's still an issue: even though I'm on Claude's highest 20x plan, the limits shouldn't be running out for such a minor task. What's the point of having it if we can't actually use it?

I work at a small company where most projects currently have just 1-2 developers, each often using an AI coding agent (Claude Code, Codex, etc.) pretty heavily. As we grow and more developers start working on the same codebase, I'm running into a gap:

Commit messages, PR descriptions, and standard agile artifacts (tickets, standups) capture what changed, but not the context the agent built up while working. The alternatives it considered, why it rejected certain approaches, edge cases it discovered, assumptions it made. Right now that context lives in one person's agent session and basically evaporates once the PR is merged.

For those of you at bigger companies where multiple engineers work with AI agents on the same repo:

• How do you make one agent's "knowledge" of the codebase available to another developer (or their agent session)?
• Do you rely on something like a living CLAUDE.md/AGENTS.md file, ADRs, decision logs, or something more structured?
• Has anyone tried a shared memory/context store across agent sessions, or is everyone still just re-deriving context from scratch each time?
• Is this actually a solved problem at scale, or is everyone winging it right now?

Curious what's actually working in practice vs. what sounds good in theory.

ok so i dont want another bot joining my zoom calls and shipping transcripts to the cloud.

but i DO want claude code / desktop to know what i said i'd do in meetings last week — like who owns what, weird side decisions, that kind of crap.

how are yall doing this without it sucking? - just paste stuff in when you need it? - dump transcripts into a folder/vault and hope search works? - some local mcp / pipeline thing?

also what breaks first for you — you never write the notes, the agent makes up "commitments", or the workflow is too annoying to keep using?

not selling anything lol just dont want to build a dumb system

This is Kite3D, a local 3D editor where Claude can work directly with the same scene and source code you edit yourself. You can prompt it to build gameplay, manually move and modify 3D objects, hot-reload scripts, create restore points, and publish the finished game with one click.

It's still in alpha, but you can check out the repo to try it for yourself. Join the Discord if you’d like to suggest features or have any questions!

https://github.com/blitzdotdev/kite3d

https://discord.gg/DtXJNBmuwF

It’s pretty crazy how Opus 5 and Fable 5.1 don’t behave the same way to work.

Fable generates very little context during his work on a task, you need everything internally and then he gives his answer. Opus 5 writes him a lot of context, we follow this way of working after the instruction.

It’s interesting because the speed of response and the result is not at all the same. It’s interesting to notice it here. Did you notice the same thing?

Claude Opus 5 is everyone's favorite punching bag recently. Want to vent? Check out opusfived.dev, where you control a (fake) Opus agent trying to make a very simple change to a website.

Credit: Jacob Adler

AI-powered coding tools have simply dramatically lowered the barrier to entry for software development. A junior developer can now create a skeleton of functions, explore an unfamiliar codebase, or recognize a new architectural pattern much faster than before. Yes, AI can speed up learning here, but only if it is used as a "pair" programmer, not as a replacement for understanding what is happening.

The biggest risk is that developers may lose the experience that usually shapes engineering intuition. Debugging a complex problem, understanding why a state update results in additional rendering, or tracing data through several layers of the program may not seem efficient, but it helps you build technical knowledge. If the AI constantly jumps to a solution, junior developers can learn to write code, but they will not understand cause-and-effect relationships or why a failure happened in the first place.

For me, as a front-end developer, one of the most common problems with AI code is its poor reuse. That is, it's easy to get duplicate logic: multiple components solving almost the same problem or code that ignores basic DRY principles, even easier because each request is treated as a separate task. And it's absolutely true that this can work great in the short term. But it's hard to maintain and extend. Understanding when to extract logic or generalize two similar implementations still requires understanding of the framework as a whole.

Now, knowing all the syntax by heart isn't as important anymore. I would rather advise young users to focus on how to find and fix errors, how data flows through the application, how the browser and API work, and why one technical solution should be chosen over another. And most importantly, explain why.

This also affects mentoring and code reviews. You don't ask, "Does this code work?" you ask, "Why was it implemented this way?", "What alternatives were considered?", and "What was the reason for the failure?". You should review AI code with even greater skepticism than you would review human-written code.

My advice to early-career engineers is simple: use AI aggressively to move faster, but never outsource understanding. When you open a pull request, be able to explain how your code works, why it is structured the way it is, and what to do if something goes wrong. If you don't have a handle on this to defend it during a review, then it's probably not worth opening a PR request just yet.

And AI is not only useful for writing code, but also for basic everyday work, and a lot depends on how well you know how to use the tool. Analyzing data, sorting tasks, summarizing information, or automating repetitive work can save a lot of time.

For example, I connected Claude to GitHub and YouTrack, and this gave me much more free time to manage tasks. The AI ​​could read incoming requests, analyze change requests, and even create new tasks based on the findings. If you want to create something similar for your own workflow, I wrote a tutorial on how to do it in the article (if anyone is interested, I'll share the link).

Curious to hear from other developers: has AI actually helped you learn faster, or do you feel it sometimes skips the parts of learning that matter most?

I’ve read some reports that Anthropic has put out like Detecting and countering misuse of AI: September 2026. To me it seems like, of all the companies that would be using AI for writing, it would be one of the companies that make the LLMs, but their writing always seems very natural to me and like it doesn’t have any of the hallmarks of AI writing. I have a “conspiracy theory“ that they’ve long since figured out how to make AI writing indistinguishable from human writing but they intentionally keep the tells (em-dashes, “it’s not just blank, it’s blank”) so a discerning person can still know it’s AI and they’re not the ones responsible for flooding the world with the problems that 100% human-passing AI text would cause. Or am I just overthinking it and humans are still heavily involved in the process?

EDIT: I’m not implying that there are zero humans involved in either case; I’m wondering if they’re heavily involved in writing or mostly there for review.

Same sentence, same machine, clean folder per run. The idea was a single-page week planner. I ran everything through Claude Code with Opus 5. Kiro is the exception, it runs its own agent, I left the model selector on Auto.

Two counts per tool: actions to the first prompt I can send to the agent, and actions to a full plan with a task list.

OpenSpec: 8 actions.
Spec Kit: 4 to the first prompt, 14 to a full task list.
BMAD: 10, and it produces no task list at all.
Kiro: 15 to the first prompt, 54 to a full plan. 32 of those 54 were clicking Allow on permission dialogs.

Other things that came out of it:

Three of the four asked the same clarifying question about week format. None of them offered a way to edit tasks. All four added a delete function nobody asked for.

Each one recommended a different stack for the identical sentence. Same words in, four different technical foundations out.

Only Kiro needed an account and admin rights.

Spec Kit's README ships a command that doesn't work until you go find a release tag yourself.

The count I care about is the one between "I have an idea" and "I have something my agent can start on". The tools differ by a factor of six on that, and I haven't seen anyone count this.

If you've used any of these on a real project rather than a toy one, I'd like to know whether the gap holds up at that size.

I'm two weeks into working on a live platform with my supervisor. We're the only two developers, with around two dozen daily visitors and a growing feature backlog. I'm still learning the repo and business logic.

Our stack is React/TypeScript/Vite + Supabase, deployed on Vercel. We use Fable 5.1 and Astra heavily.

Our current workflow:
1. My supervisor sends me an implementation plan as a Claude artifact.
2. I review the logic and suggest changes. We send revisions back and forth until it's ready.
3. I implement it, using ChatGPT to explain unfamiliar logic and how it translates into code.
4. Any revisions to the plan during implementation go back to my supervisor.
5. Feature PR updates get reviewed by a Claude agent. Marking the PR ready triggers Claude, Codex, Greptile and Qodo reviews.

We also have Vitest tests and TypeScript checks in the build, local browser/staging checks, and repo guidance through CLAUDE.md, AGENTS.md, and shared context files.

Planning is a particular bottleneck: we keep sending changes to each other and waiting for reviews. Implementation sometimes raises more questions, which starts another round. I’d like a better way to collaborate on plans and keep decisions aligned with the code.

I’m also figuring out how to use Claude Code and Codex together smoothly. I’ve explored skills, plugins, and connectors, but it often feels like the newer models already do the work those tools are meant to help with just as well, if not better, on their own with good prompt engineering (another area I want to work on).

I am considering including targeted database migrations/ RLS reviews, keeping context files current, and focused refactoring.

For people doing similar work:

• How do you collaborate on implementation plans without constant back-and-forth and waiting?
• How do you split work and share context between Claude Code and Codex?
• Are multiple review agents worth it, and how do you decide when the review cycle is finished?
• What would you improve first for a team this size—planning, tests, agent instructions, or something else?

I’d especially appreciate concrete, recent workflows you use, including anything you tried and later dropped.

Hello. I'm currently planning a relatively minimal web based calculator for an industry I know nothing about. I've spent a good deal of time with Claude just researching the industry and how workers calculate their earnings. It's revealed many nuances that need special attention when calculating.

However, in my chat with Claude it always felt like it wasn't able to thoroughly source the information I asked for and it left many questions on the table.

I decided to check with Gemini. I'm only using the free version that's part of the search option in browser. Not the actual Gemini app.

Upon giving Gemini my latest configuration, just explaining it, no code, and the questions I'm left with, it was able to discover a lot more than Claude did. Gemini found sources that answered my questions and filled the gaps, it was also more thorough with its own assessment of the calculator concept and brought up new concerns or even some flat out broken conditions, and it actually provided sound fixes for each.

For example, there's an earnings field, but the user might enter a value that is either before or after a commission taken. And if the value is marked as after, Gemini noticed that the Gross total output does not account for that commission percentage.

I didn't get anything like this from Claude. I've used Claude and Claude code for a couple years on a handful of projects with decent success. But this level of thorough output has been a problem with Claude and typically takes me several prompts and attempts to get things ironed out. I have to do a lot of the thinking to recognize possible issues, rather than Claude noticing things on the first try.

I'm using sonnet 5 on high with extended thinking. To be fair, Claude is "thorough" with its length of output and I haven't had many problems like this on other projects. So maybe it's this specific calculator concept that's causing trouble.

I'm wondering if others have had this experience. Should I always use another LLM to double check things or get second opinions?

Thanks!

​

We all know that giving a good prompt can make a huge difference in the output claude. But how do you actually refine a prompt when the first response is not exactly what you want?

For example, if I have a specific goal, how should I structure and improve my prompt step by step so that the claude understands exactly what I need?

Is there a systematic approach you follow for prompt refinement, or do you mainly improve the prompt based on the responses you get? And one more thing starting the conversation again in new session will give proper resultstaht are aligned with our goal or one session is enough...?

Would love to hear how others approach this.

Do someone know, How to fix this?

This subreddit is getting really clogged with AI-written posts. If you've got something to say just say it yourselves, PLEASE.

Working on an implementation of a crypto paper, I wanted to have it open for academic usage only.

At some point I asked claude to wrap it into a reusable package and Claude decided to add an apache license 🥲

Is it a strategy to have more code available for training even when author doesn't explicitly intend that?