Now I realize why Dario is terrified of opensource models.

After running the above setup with oMLX and Claude Code, I am absolutely convinced that local compute is the future. With models like GLM 5.2 and Hy3, the model gap is closing, the next gap to catch up to is hardware.

Exciting times!

It is very clear that Fable was a differentiated model (as much as it has returned, yes, covered) and came to raise our bars on really intelligent AI.

It’s not about typing code, it’s not about answering with more context.

It’s about delivering real value in the project.

Now, we say goodbye to Fable (because the price via API is far from acceptable, nor fair with delivery)

Where will we migrate to? What’s the plan? How have you been preparing? Move to GLM or another Chinese LLM? Wait for the OpenAI move?

I feel like I’m leaving my sniper rifle aside and going back to hunting ants (bugs) with bow and arrow

Fable 5 leaves the Claude subscription plans tomorrow night (11:59pm PT on July 7, then it's API-only at $10/M in, $50/M out). I have roughly 10% of my weekly limit left and I'm trying to spend it deliberately.

I've been vibe coding with Claude Code for about 10 months and my setup shows it: CLAUDE.md files that grew past their purpose, skills I wrote and forgot, instructions I apparently love retyping by hand every single session. Fast agents let you outrun your own architecture.

I'm not building anything new tonight. I'm having it hand over everything it learned about how I work.

Run 1: harness archaeology

Go through all my Claude history: conversations, docs, projects, skills, and workflows. Answer five questions:

1. What do I actually use you for most? (not what I think I use you for)
2. Which tasks do I repeat that were never turned into anything reusable?
3. Which instructions do I keep rewriting by hand, session after session?
4. Which workflows deserve to become permanent skills?
5. Where was my approach simply wrong? Point at things you watched me do that I should stop doing.

Then convert every answer into artifacts: skills, usage guides, workflow templates. Everything worth keeping should survive as a file, not a memory.

Run 2: agent-native audit

My app gets more user bug reports than I can personally walk through a chat window, so this run reviews the architecture with one goal: an agent should be able to pick up a bug report, reproduce it, fix it, and verify it on a real build with me barely in the loop.

Act as a principal architect reviewing this codebase with a single goal: make it agent-native. Definition: coding agents should be able to pick up a user bug report or a roadmap feature, then reproduce, implement, test, and verify it on a real build with minimal human input.

Audit four things:
1. Human-judgment chokepoints: every place where a change currently requires my personal judgment or tribal knowledge. Which of these could become written conventions, decision tables, or CLAUDE.md rules an agent can follow on its own?
2. Verification gaps: for each core subsystem, what is missing for an agent to verify its own change end-to-end? (behavior tests, live probes, mock event injection, log assertions, screenshot diffs)
3. Reproduction paths: given a typical user bug report (text plus diagnostic bundle), what would an agent need to reproduce it autonomously? What fixtures or replay harnesses are missing?
4. Structural obstacles: modules too entangled for an agent to change safely without reading the whole repo. Propose boundaries.

Deliverable: a prioritized plan ranked by human-attention-saved per unit of effort. The top 5 items must be specified concretely enough that an agent could start each one from this document alone.

But I might be spending my last tokens wrong. If you had one deliberate run left before the cutoff, what would you spend it on?

Looking for the thing I'll still be using three months from now, after the model itself is gone.

I’m a software engineer and since last few months been using Claude code heavily, every new ticket or requirement or spec is just one clever prompt and some back and forth with claude code, Now a days most work is basically reviewing and understanding claude code method and try to get a better solution.

It’s been a while I have written code by hand and I fear I’m relying too much on Claude code, other day claude code was down for one hour and no one in my team did anything, people are having hard time understanding code and slowly code reviews are also becoming hard.

Honestly I would like to code a some parts by hand but our deadlines and expectations are now adjusted based on Claude code output making us use it to develop faster.

How is all your experience with related to this?

maybe i’m doing something wrong, but lately my 5 hour daily limit feels like it’s getting used up insanely fast.

i’ve been trying to optimize things a bit. i’m not using memory.md anymore, my claude.md files are pretty small, usually around 200 lines max, i don’t keep using the same chat forever, and i reset things pretty often.

i also set up automation to trigger claude every 5 hours, but even then, the limit still seems to disappear way faster than i expected.

is there anything that actually affects this? like chat history, context size, project files, long conversations, tool usage, or anything else?

how are you all managing your 5 hour windows? any practical tips to make the usage last longer?

I’ve been testing both Claude Fable 5 and Codex GPT-5.5 for Unity game development and some simple web development. I’m using the $200/month subscription tier for both, and after about 4 days, I have some early impressions.

I’m posting this because I know my sample size is small, and my workflow might bias the results. I’d really like to hear from other people who have used both, especially for Unity game dev, web apps, or longer agentic coding tasks.

My current impressions:

1. Fable 5 feels extremely strong for long-running, loosely specified tasks.
Compared to Opus 4.8, Fable 5 feels less like a tool and more like an employee. I can give it a broad goal with fewer detailed instructions, and it seems better at understanding the bigger picture, planning ahead, and catching edge cases I didn’t explicitly mention.

The downside is cost. From what I understand, the cheaper plan-based access to Fable was limited, and moving forward it seems like using it heavily will require usage credits / API-style pricing, which could become much more expensive.

2. GPT-5.5 feels much better for fast execution when the instructions are clear.
Codex with GPT-5.5 has been very good at carrying out detailed tasks quickly. In my experience, it gets implementation work done faster than Opus 4.8, with similar quality when I give it enough context and specific instructions.

It also seems much more usage-efficient for my workflow. In two days, I used around 92% of my Claude weekly usage, mostly due to Fable and automated workflows. Meanwhile, I only used around 8% of my Codex usage while keeping GPT-5.5 xhigh running quite a lot.

3. Opus 4.8 still feels excellent for frontend/UI work.
For frontend development, visual polish, and UI/UX, Opus 4.8 still feels very strong to me. It often creates beautiful, polished designs with good taste. On the other hand, GPT-5.5 has felt stronger for my Unity/game-dev implementation work.

4. My best workflow so far is: Fable plans, GPT-5.5 implements.
The combination that gives me the best result so far is using Fable to create a detailed masterplan, architecture, or implementation strategy, then giving that plan to GPT-5.5/Codex to execute.

This seems to give me a better balance of quality, cost, and speed than trying to use Claude workflows for everything.

5. My current plan after this month:
I’m considering stopping the Claude subscription and only using some credits for Fable when I need high-level planning, architecture, or deep review. Then I’d keep the $200 GPT/Codex subscription as my main implementation tool.

Does this match other people’s experience?

I’d especially like to hear from people who have used both for:

• Unity game development
• frontend/web apps
• long-running coding agents
• large refactors
• AI-assisted architecture/planning
• cost/usage efficiency on the $200 plans

Am I overestimating Fable because it feels impressive in long tasks?
Am I underestimating Claude workflows?
Is GPT-5.5 actually more efficient long-term, or is that just because my prompts and workflow fit it better?

Thoughts and suggestions are much appreciated.

These are my thoughts, refined by ChatGPT.

Hi Guys ,

I'm building a high-end photography portfolio website for a friend who's a professional photographer and videographer based in Marrakech.

I'm not looking for a simple portfolio template—I want to create something that feels premium, cinematic, and editorial, similar to luxury photography studios.
I'm searching for Claude Code skills, prompts, workflows, or MCPs that can help with:
UI/UX design for premium portfolios
Frontend architecture
Animation systems (Framer Motion / GSAP)
Gallery design and image optimization
Responsive layouts
Accessibility
SEO for portfolio websites
Performance optimization (Core Web Vitals)

https://preview.redd.it/i36d5lhx1obh1.png?width=1090&format=png&auto=webp&s=07c5b3490b852dba6cca08321ed304df118d652d

I'm curriouse about your stats guys. Last week i got aprox. 17M tokens from my 5x + upgrade to 20x. Today I got 4M from my 20x after weekly restart and I'm almost out of quota.

From morning it was going slowly up but through day somehow it burned whole.

I've tried to talk with support bot, but there was no help.

Was thinking about another subscription, but I don't have trust towards their limits and I won't use that many tokens on daily basis.

I found another intristing string "claude-fable-5: 601.6k input, 2.0m output, 78.3m cache read, 5.2m cache write ($254.84)"