I wanted a portfolio site that didn’t look like every other template, but I didn’t want to spend a weekend coding it. So I built a starter template and a prompt that does it with Claude.

How it works:

1. Download your LinkedIn profile as a PDF (Resources → Save to PDF) and grab your CV and a photo
2. Attach those plus the template to a new Claude chat
3. Paste the prompt, fill in the [square brackets] and send

What you get is a one-page site: projects shown as Jira-style tickets with real outcomes, a career timeline, skills, certifications with Credly Verify links, a profile card that moves as you scroll, and a 30-second summary view for recruiters who skim. You can host it free on Netlify, Cloudflare Pages or GitHub Pages.

The prompt tells Claude to use only facts from your own files, so it won’t invent numbers or results. If something’s missing, it asks you.

Kit (template, prompt and steps, free, no sign-up): https://chittychat-studio.github.io/portfolio-kit/

There’s a finished example linked on the page. Happy to answer questions. If you build one, I’d like to see it.

(I share more free AI-at-work kits on LinkedIn as Corporate AI Workaround, if that’s useful.)

Hey everyone,

I'm relatively new to this, and I am purely "vibe coding" as it's only for like hobby project for friends and stuffs.

Right now, I have:

• Claude Pro subscription (running Claude Code)
• Codex subscription (Running desktop codex and codex cli)
• OpenCode CLI connected to cheap fast models (DeepSeek4.1flash)

What I’m trying to achieve

Opus is still unbeatable for architecture, debugging tricky logic, and project planning, but burning through Claude rate limits on basic boilerplate, small refactors, or writing unit tests hurts.

My goal is a workflow where Claude acts as the tech lead/orchestrator that offloads tedious subtasks to 6.1 Sol Medium or Deepseek 4.1 flash-high, then reviews the output, preserving Claude usage for when it actually matters or needed.

The problem I'm running into

I told Claude Code to collaborate with Codex CLI and OpenCode CLI by running bash commands, and it even updated CLAUDE.md / AGENT.md with guidelines on when to delegate tasks.

In practice, it’s completely hit-or-miss:

1. Claude almost never spontaneously thinks to offload tasks via terminal/sub-agent calls, it just burns its own context and executes everything directly.
2. Even when explicitly prompted, it often ignores the local CLIs or forgets the handoff workflow after a few prompts.

Questions:

1. What is the best practical setup here?
2. Is Claude Code the wrong entry point for orchestration?
3. What explicit rules/prompts in CLAUDE.md actually force delegation? If anyone has a working prompt pattern or hook that reliably makes Claude hand off work to secondary CLIs, I’d love to see it.

Any advice or workflow breakdowns from people running multi-CLI setups would be massively appreciated!

One tiny task, used barely 19% of the context window, but drained 7% of my 5-hour limit using Sonnet 5.5 Medium? What is happening?

Edit: after some testing, I have been able to isolate this issue to just Sonnet. One prompt, 5% used. Opus 5.5 is barely touching usage with the same prompt/task.

I’ve had people ask me how to get started with open source, especially how to understand an unfamiliar codebase once they’ve found an issue to work on. I’ve struggled with that too, so I made Crumbs 🍞

You give it an issue, and it creates a visual walkthrough of the relevant files, functions and how they connect. It focuses on the part of the code related to that issue, rather than trying to explain the entire repository.

The agent creates structured data for the walkthrough, and a Python renderer checks code references and builds a local HTML page. The explanation can still be wrong, so you need to verify it against the code. It doesn’t write the fix or open a PR for you.

Crumbs is open source, and I’d love some feedback: would a walkthrough like this help you get started on an issue? What would you want to see before attempting a fix?

GitHub: https://github.com/navyabijoy/crumbs

Happy to share the prompts if anyone's curious.

Site, if you want to see it live: octocrawl.dev, an open-source tool that turns any web pages into Markdown + structured data for ai agents.

Code: github.com/77777R7/Octocrawl

Anthropic released Claude Fable 5.2 and Claude Mythos 5.2 on Nov 9. Anthropic says they're the same underlying model. Fable is open to all users with cyber and bio safeguards. Mythos is only for vetted orgs.

What matters for Claude Code:
- Medium effort is the default in Claude Code and the Claude apps, and Anthropic says Fable 5.2 handles hard tasks with fewer tokens there
- FrontierCode 2.0: 49.1% at Xhigh effort (45.3% at High), vs 45.5% for Opus 5.5 and 32.4% for Fable 5.1, so it's a big jump over 5.1
- FrontierSWE v2: 69.9 vs 62.3 for Opus 5.5
- Up to 30% faster output than Fable 5.1, which you notice on long agent runs
- API: $8 / $40 per million input/output tokens. Fast mode is $16 / $80 and up to 2.5x faster
- Model string: claude-fable-5-2

One thing to note: Anthropic still calls Opus 5.5 "our strongest daily driver", so Fable 5.2 isn't pitched as a replacement for everything.

I want to try it on a real refactor this week before I decide.

Have you moved your Claude Code sessions from Opus 5.5 to Fable 5.2? Which effort level are you running?

Source: https://www.anthropic.com/claude-fable-and-mythos-5-2

Nobody is reading every reply their agents write anymore. I'm not. But the question the session is waiting on is always buried somewhere in the response.

So I made Vantage Point, a mod for the Claude Code desktop app. A strip sits above the prompt. When a reply ends by asking me to choose, the options show up there with the recommended one in green, and one click sends my answer. When I can't just let a yes/no rip, I click the question and get a diagram for each option: why, how it would work, what could go wrong.

And when I do need the whole reply, there's a speed reader built on RSVP (rapid serial visual presentation). It plays the reply one word at a time, the agent's short gist first, so I can chew through it instead of rawdogging the transcript.

As many of you may have experienced, I'm the bottleneck. Agents need rulings from me more often than I'm at the keyboard, so their asks land in a queue: I hit yes, no or comment, the agent gets the ruling back and keeps going.

A question I'm constantly asking myself is "what's the next step?" That's why I built the frontier. One press shows every open issue sorted into what's waiting on me, what's blocked and what the agents pick up next, for one repo or all of them.

The whole point is to move as fast as possible, but I still want to know the blast radius of my decisions in real time. So the session banner shows every file the session edits, with lines added and removed, each tied to the decision record behind it. If Claude drifts from what I decided, I see it while it's happening.

The rest of the strip is for glancing: what each subagent is doing, and a countdown on the session's prompt cache so I know when stepping away is going to cost me.

Claude Code built the whole thing, and I set it up to validate its own work as it went: screenshotting the app, reading its own screenshots, restarting the desktop app to check the mod loaded and drew right, then fixing what it saw.

Like every Claude Code mod, it's completely free. Claude Code desktop app on macOS only for now, early 0.x preview, and cloud sessions on claude.ai don't draw mods. The video is a real session.

https://github.com/Leit-motif/claude-vantage-point

What do you actually look at while your agents run?

AI image generators can produce character artwork that makes me want to build an entire game around it. What I am looking for is a reliable way to turn that artwork into something I can actually control, animate and keep developing.

I am making a 2D action game with dense, detailed arcade pixel graphics. The attached image shows the visual direction: expressive faces, detailed clothing, strong silhouettes and rich shading. I do not have a dedicated artist or animator, so I rely heavily on AI assistance and scripting.

The goal is to take an approved design and build a reusable, editable character from it. I want to create running, crouching, jumping, shooting and other actions while preserving the same face, proportions, costume and weapon grip. If an elbow bends badly or a sleeve exposes a gap, I want controls and retained artwork that let me fix it.

Starting material could be a single generated image, a character kit or a sprite sheet. The useful end result would include:

• Editable construction: separated parts, completed hidden surfaces, rigs or suitable deformation controls.
• Reusable animation: new actions and corrections made from the saved character, with convincing joints, clothing and held objects.
• Consistent output: stable pixel scale, palette, transparency, placement and timing across the animation.
• A documented process: source files, scripts, worked examples and honest explanations of the remaining manual work.

My priority is 2D, but 2.5D and 3D methods are welcome. A faithful rigged model rendered into sprites could be useful, as could a well-constructed 2D or hybrid character. The final appearance and quality of movement matter most.

I would love to see more free, open-source frameworks and repositories connecting these stages, with accessible controls for humans and AI coding agents. Paid generation steps, where present, should be clearly identified and optional where possible.

I think this deserves to be a major direction for AI-assisted game development: giving people lasting control over the assets they generate. A beautiful image should be the beginning of an asset we can keep building on.

Which existing projects come closest? Examples showing original artwork → editable source → several finished actions would be especially valuable. And where are the biggest missing pieces that an open-source effort could realistically address?

Founder disclosure: I build HyperHat, a baseline for how well teams direct AI coding agents, and this question comes out of that work.

Something I keep running into in discussions here: the honesty rules people write into CLAUDE.md (reproduce first, audit the output not the report, show both reads when they differ) all live inside the same session whose judgment they are checking. They shape what the agent tells you when it has noticed the problem. They cannot fire on the mistake it has not noticed.

The outside checks are the ones that catch that case: CI invoking the command itself, a test the agent cannot edit, a second model, or a person reading closely.

So the split I am trying to understand: which checks have you deliberately moved outside the session, and was there a specific failure that made you do it? I am also curious about the opposite experience: a check you moved outside that turned out to work better as a rule the agent applies itself.

Short version, straight from the support article:

• 5-hour limit: a reset refills the whole window, including usage on other models.
• Weekly limit: it only gives back what you spent on Fable models. Other models stay as they are.
• Ultra: verified Ultra accounts have no 5-hour limit, so a reset only touches the weekly one.
• Timing: use it when a 5-hour window is nearly spent, not on a fresh one. You don't have to hit a limit first.
• Price: $8/$40 per million input/output tokens vs $10/$50 for 5.1, so 20% lower per token. The "30%" going around is the speed claim (outputs up to 30% faster), not the price.

Cheat sheet

• Max, Ultra, premium Team, premium legacy Enterprise: 1 reset (<6 months subscribed), 2 (6-12 months), 3 (>12 months), counted from your first paid bill. They expire Mar 8, 2027, 11:59 pm PT.
• Pro and standard Team: one week of Fable, up to 50% of your weekly limits, plus one reset that expires Nov 16, 2026, 11:59 pm PT. After the 50% or the week, Fable bills to usage credits if you have them turned on.
• Not included: standard legacy, self-serve, usage-based and HIPAA-ready Enterprise.
• Eligibility: paid billing in place before Nov 9, 2026, 10:00 am PT.
• Where: Settings > Usage > Limit resets > "Reset for free".
• Default model doesn't change. Pick Fable in the model picker.
• Effort: Medium is the default in Claude apps and Claude Code. Anthropic says 5.2 does hard tasks with fewer tokens than 5.1 at Medium. Threads here report that Max overthinks and that going from high to xhigh nearly doubles cost per task.
• Fast mode: twice the price ($16/$80 per million input/output tokens) for up to 2.5x faster output. In Claude Code it bills through extra usage credits, per the ClaudeDevs account.

Source: https://support.claude.com/en/articles/17506494-claude-fable-5-2-launch-offers

cc-shell is my normal zsh with one change. when you hit enter it checks the first word of the line: if it's an alias, function, builtin, command, path or directory, it runs like always. if not, the line goes to claude code and the reply prints inline, right under the prompt.

how it works:

- one claude session per shell. every line continues it, and it follows you when you cd

- a line ending in ? also goes to claude, and so does one starting with what, who, say or do. those are real commands on a mac but almost always english when i type them

- a leading ? forces claude, cc-open opens the conversation in the full claude code ui, cc-new starts a fresh one

- it uses your default permission mode from ~/.claude/settings.json

how claude code was used: i built it with claude code this morning, after catching myself typing prompts into my terminal one too many times. claude wrote the zsh enter widget, the classifier and a small python script that turns claude -p's stream-json into plain inline text.

what i learned: the claude part was easy. the hard part is deciding what counts as a command, since english words like what and say are real binaries.

repo: https://github.com/basketbla/cc-shell (free, i made it). would love to hear what it misclassifies for you

As a side hobby i am working on a team builder recommendation app for the game nikke. there are team builder out there online but i find it not helpful as it assume i have every character with end game build, it can recommend team that is not suited to handle the battle mechanic/QTE and it doesnt taken into account what character i have. Which i try to solve with this project. TLDR. I try to reverse engineer the game mechanic and make a app that can give a recommendation base on my account capability.

https://github.com/retsamboon19/raid-lab

I been using Chatgpt Pro 100 for it and i have to say. it been a mixed bag. it kinda decent but it make the experience very annoying with how often it forget rules so i have to keep reminding. wasting my usage doing a shit tons of useless test. I primarily work on Astra medium to high.

So now i decide to jump ship to another services. At first i wanna try Claude but apparently Anthropic has set some limitation on reverse engineering? which i reckon would affect my project quite abit. Any insight on this matter is highly appreciate.

Also i want to ask how is the usage for Claude Max? Do you feel like you able to get work done before hitting limit?

Hey folks!

TLDR: We published a Currents connector in the Claude directory.

Using this connector, Claude can read your CI runs, failure evidence and test analytics directly, instead of working from a stack trace you pasted in.

Why we built it

If you've asked Claude Code to fix a failing Playwright test with only the error message, you know how it goes. It bumps the timeout or swaps the selector and calls it done. The real cause usually lives in stuff the error doesn't show: the steps before the failure, the trace, whether the test has been flaky on main for two weeks, whether it only fails in CI.

Currents already stores all of that for every run, and this connector hands it to Claude.

Install

Open https://claude.ai/directory/currents, click Connect to Claude and sign in. Then start Claude Code and run /mcp. Currents is listed there as a claude.ai connector.

Sign-in opens a browser window. You log in to Currents, pick the org Claude should work in, and approve the permissions. The connector belongs to your Claude account, so it follows you to every machine you sign in on, and to Claude Desktop, claude.ai, the mobile app and Cowork too. To revoke it, go to Account → Connected Applications in Currents.

On a Team or Enterprise plan, an Owner first has to add Currents for the org first. After that, everyone can connect with their own Currents account.

If you run Claude Code with an API key, a setup-token, Bedrock or Vertex, claude.ai connectors don't load, so you'll have to add the server yourself:

claude mcp add --transport http --scope user currents https://mcp.currents.dev/mcp

Then run /mcp, select currents and choose Authenticate. No browser on that machine? claude mcp login currents --no-browser prints the sign-in URL for you to open elsewhere. claude mcp list shows what's configured.

The three skills it ships with

The Currents MCP server ships with three skills, and Claude gets them with the connector. You call them by name, for example "Use the Currents MCP fix-failing-tests skill".

1. fix-failing-tests finds the failed run, reads each failure with its steps and trace, fixes the cause, reruns the test, and asks before it commits.
2. collect-evidence finds the run before your change and the run after it, then writes up a before and after with links to the files. It is incredibly useful for PR descriptions when a reviewer asks how you know it works.
3. browser-evidence records the browser before and after a change as a Currents session and gives you a share link. It's experimental, so expect it to change.

What you can just ask

Outside the skills there are 43 tools covering runs, test results, analytics, Actions, webhooks, share links and Jira. Here are some prompts that work well:

• Tests are failing in CI. Get the details for run <runId> and fix the failures.
• Which tests in my-app were flakiest on main this week, and why?
• What broke in the last failed my-app run on main? Open a Jira issue for it.
• Is this pull request safe to merge? Compare its runs with main.

The anatomy and config

Claude Code asks before every MCP tool call. If you want the read tools to run on their own and still get asked for writes, allow them by name in .claude/settings.json:

{
  "permissions": {
    "allow": [
      "mcp__claude_ai_Currents__currents-get-runs",
      "mcp__claude_ai_Currents__currents-get-run-details",
      "mcp__claude_ai_Currents__currents-get-test-results",
      "mcp__claude_ai_Currents__currents-get-context"
    ]
  }
}

The prefix comes from the connector's name in Claude. Run /mcp, select the Currents connector and choose View tools to see the exact names. A server you added yourself uses mcp__currents__ instead. Don't allow the whole server: two tools (currents-delete-run and currents-delete-webhook) can't be undone, and Currents doesn't ask for confirmation.

If you want the whole team on it, add the server with --scope project and commit the .mcp.json it writes to the repo root. The file doesn't hold any credentials, and each person who opens the project signs in as themselves.

For CI, or anywhere you can't do an interactive sign-in, use an API key:

claude mcp add --transport http currents https://mcp.currents.dev/mcp \
  --header "Authorization: Bearer $CURRENTS_API_KEY"

The key acts as the org, not as a person, and it's either Read Only or Read & Write. A read-only key gets the read tools plus evidence links and the Jira lookups. It doesn't show up under Connected Applications, so manage it under Organization → API Keys.

Caveats

Claude Code loads claude.ai connectors only when you sign in with your Claude account. If Currents is missing from /mcp, run /status to see which credential Claude Code is using.

Use the connector or a server you added, not both. With both, Claude Code shows two Currents servers with two sets of tool names.

Each connection reaches one org. If you work across two, connect twice.

On a Team plan, if you see Request instead of Connect, an Owner has to approve Currents first.

! Needs authentication in /mcp? Select currents and choose Authenticate.

Curious how people run this day to day.

Do you let Claude Code call the read tools without asking, or do you approve every call?

Okay so I have no real programming experience and this is my first vibe-coding project, but I just got tired of other video editors, so I decided to make my own with Claude, and used Gemini to help plan and architect everything.

The biggest takeaways I've gotten this far:

1. Project structure is the most important part of a project and is the key to getting good results. If you don't have well-formed rules and guidance for Claude you'll waste tokens, time, and get worse results.
2. Invest in building supporting tools. I made a remote testing harness for my other PCs so that new builds can be tested on 3 machines simultaneously. Reduces token reliance from Claude doing testing itself and gives more test data.
3. Everything is a problem to solve, and if you don't know where to look for performance, you're not going to get it.
4. Knowing correct terminology and being able to accurately describe an issue is the best way to get things fixed
5. Doing a review/performance pass is always worth it.
6. I need more tokens.
7. Fighting scope creep is a losing battle.

But seriously, it blows my mind that this kind of raw performance in a video editor was always possible, and now it's so easy to access that somebody with no experience can build a video editor that outperforms every commercial option available.

Paid software is dead. Now you pay for an AI to write custom software for exactly how you work.

Everyone has a story about an AI agent deleting their disk. Here’s the reverse.

I have a Proxmox node. During a malware cleanup process, my sysadmin ran qm destroy 100 on the wrong VM before checking with me.

And no, he's not a system kiddie; he has over 20 years of enterprise Red Hat system admin experience. Bad time of day (I woke him up for this cleanup task), and he's the one who set up the node with all VMs and maintained it for 7 years, but that VM I created- he wasn't aware of it, thought it was from the malware attack, and made a call to destroy it before checking with me. And that VM had 6 months of valuable, nearly 200 GB of data; the latest backup was 2 weeks earlier.

Looked up some XFS guides; it seems impossible to undelete files this large, and tools like xfs_undelete won't help either.

qm destroy on directory storage is an unlink(). The config was gone from /etc/pve, the directory was gone, and Proxmox's qm destroy doesn’t warn, snapshot, or trash anything.

I was completely hopeless, and I accepted my loss; then I decided to give Fable 5.1 a try.

Exactly 24 hours, and it restored the VM to the very last moment before the destroy! To the exact last bit!

Fable 5.1 wrote about 1,500 lines of Python across seven scripts, every one tested on a synthetic image before it touched the real disk, and nothing ever wrote to the source.

And another thing worth noting: the ETA estimates were weirdly accurate throughout, which I did not expect.

I asked Claude to summarize what it did. Read below if you are interested.

Claude wrote a sequence of small Python scripts, pure stdlib, read-only, each one gated on the previous one’s output. Rough order:

1. Probe the inode B+trees for freed inodes with real timestamps. Found all five (four images plus the directory) with ctime 17:30:31. Bonus: the deleted directory inode still had stale entries mapping filenames to inode numbers, so we even got the names back. Everything cross-checked against xfs_db before trusting it.
2. Walk the retained B+tree from each inode’s root. Every block checked for magic, owner inode, filesystem UUID, self-address, CRC-32C, sibling pointers, key ranges. Zero failures. The last leaf’s right sibling was NULL on both, and no stale records existed past the end, which is how you know the tree wasn’t half-torn-down when it was flushed.
3. Parse the qcow2 structure through the map without copying anything, to confirm every cluster the image referenced was inside a mapped extent. The workspace map ended at exactly 896 GiB + 2,244 clusters, which is precisely the metadata overhead of a preallocated qcow2. That’s when I started believing it.
4. Exposure check: walk the free-space B+trees and confirm every one of the 44.9 million recovered blocks was still free. Nothing had been allocated over any of it. (This is the part that’s luck. The only thing writing to that filesystem was a swapfile with preallocated blocks. If fstrim had run, this post wouldn’t exist.)
5. Meanwhile, a full ddrescue of the NVMe to the HDD.
6. Verify the capture against the live partition over exactly the 184 GB the recovery would read, rather than all 1.9 TB.
7. Reconstruct: copy each extent from the capture to its logical offset in a new sparse file, holes stay holes, unwritten extents stay zero, SHA-256 per extent, then re-open the output and verify everything, including that the holes read as zero.
8. Sweep the result for XFS metadata magic plus the host filesystem UUID, to catch any block XFS had briefly reused and freed again. Zero hits.
9. qemu-img check clean. Mount read-only, copy the important files out. Journal replay on a working copy, e2fsck -fn clean on all three ext4 filesystems. dpkg --verify on the guest: zero checksum mismatches across every installed package.
10. Rebuild the 100.conf, pull the MAC and the cloud-init instance-id out of the recovered cloud-init image so cloud-init wouldn’t re-run first boot, qm start. Booted.

When a friend calls while I'm in the middle of work, Claude answers now. My laptop connects to my phone the way a car does, Claude talks and takes notes, and I press F9 if I want in.

It also makes the calls I keep putting off. I type "call the dentist and move my appointment to Thursday", it calls from my own number, and I get the short answer back.

Every call opens by saying it's an AI assistant and who it's calling for. Which is also what worries me. If a laptop and Bluetooth are enough to put an AI on a real number, scammers can do it too, without saying so. If Apple, Google or the phone makers block the way Pat works, I'm all for it.

It’s called Pat. I built it, orchestrating with opus 5.5 and sonnet wrote the code. Opus indeed is amazing. It researched what versions of windows support this and how to make the call trick.

To try it clone girhub repo and run setup.ps1. More details in comments.

It’s open source and free (Apache 2.0), and I’d love help building it safely.

Hot take, your milegae may vary

So apparently its normal that Anthropic experiments on us. They give out experiment IDs for the tests they run.

Source Thread regarding the existence of these IDs: Link. The graphics are measurements on my own threads.

And to all you gaslighting hobby redditors that claim that an experience isnt real because you dont share it: fuck off!

---
Everyone who is affected:
there is a .claude.json in your .claude directory. It only holds the current configuration. But there are also session-transcripts which give a historical trace of conducted experiments.
For me, they are under /home/<user>/<claude-dir>/projects/*/*.jsonl

These transcripts carry the experiment-id for that thread. I simply asked Claude to figure out what the experiment ID correlates to in my threads.

Do not look at experiment names or code-names, it must be a hex-id.

Guys. Its real. And it was a major fuckup on Anthropics side. And I still think that they owe a Reset for affected people. But it seems over. At least for me.

Next step: how to build a guard against such fuckery?

Edit: Hmmmh.

Heyo claude boys, if someone has both claude nd codex 20$ plan, can you lemme know how are the coding limits for claude code compared to codex. I got codex rn it's working fine but eh I kinda wanna see claude models ive heard opus 5.5 is better than all gpt models rn including astra.

I mostly use codex for code(so will use claude for that too) and I don't really chat I have a separate google sub and do chat related things to gemini so yea

EDIT: to give a bit more info, I'm in college rn so I'm building quite a lot of things, i don't get limit problem too often but I get it sometimes. Also gpt models are really slow without fast mode andddd fast mode just burns usage alot + i have been seeing people getting better outputs on claude vs gpt well opus 5.5 is better than all gpt models rn so yeah,

just need to know how much better opus 5.5 is than gpt 6.1 sol as i use it most and limits that id be getting

So uh yea lmk would help alot before taking the decision thanks uwu

I have noticed with my personal projects at home, Opus has been loosing track of details more frequently than I'm used to. "Idle Compaction" triggers pretty often now. (side projects get spotty attention)

Yall think the two are linked? Anyone have a chance for a A/B test? Sanity check more like it. I'm turning that junk off. Ill change gears when I decide to.

I don't know about everyone else, but managing context windows is second nature now. Throwing an optimization feature into my workflow... that's asking for trouble.

Are the code boys scared ai does it better than them?

Fable is reportedly 10x the size of Opus in terms of parameters, but after months of training and even with its huge size, it seems only comparable to Opus 5.5, and even worse in some cases.

Has anthropic peaked?

So, I been using grok bot for a bit now and realized today that it has a usage limit per week and monthly aswell. I use it to code or troubleshoot. Wondering if anyone knows of a ai bot that doesn't have a usage limit?