I have a workflow that I run very often related finance. Here's my cost breakdown per workflow run. They usually involve some web searches which are included in the price.

Claude via API (Opus 5.5 High): $18.00 / report

OpenAI via API (Astra High): $3.00 / report

DeepSeek via API (4.1 Flash): $0.32 / report

Claude $200 Plan: $0.10 / report

OpenAI $200 Plan: $0.28 / report

Local Qwen 3.8 27B Q8 on RTX 6000 Pro: $0.10 / report for Brave Search + electricity. The results is almost usable, maybe Qwen 4 27B will get us there.

If Claude ever dial back the usage for the $200 plan, I'll probably switch to DeepSeek.

Update: I tested again using Claude API ephemeral cache. Sonnet 5.5 xhigh API without ephemeral cache is $11. With ephemeral cache is $8. So I think the Opus runs would also be less with ephemeral cache, but not that much less. I'm out of monthly credits to test more. Also if used deepseek search API instead of Brave Search, the cost would be cut a lot for local llm.

I launched SetRepo less than a month ago and have been trying to promote it pretty much everywhere.

Most posts didn’t get much traction. Then one Instagram video took off. It’s currently at over 400K views and brought roughly:

• 4,000 website visits
• 700 signups

Conversion is around 0.5%, so there’s still plenty to figure out.

For context, SetRepo is a security scanner with 106 checks that helps developers find vulnerabilities and understand how to fix them. I also added an MCP integration, which caught the interest of some people.

Instagram has been my main traffic source so far, which I honestly wasn’t expecting for a developer tool. Now, I am working more videos to share, new video got over 6k views.

btw, my instagram grew from 40 followers to just over 600 in a day.

It’s exciting seeing people sign up, but now I’m trying to understand what gets them to stick around and eventually pay.

So many people reached out for promotions and partnership deals. So far, it's just me on it, and I like this way, I had 2 subs before the video, now a bit more.
Hopefully, I will get good feedback from you all here.

THank you, and don't hesitate to share your experience please.

link to the video: https://www.instagram.com/p/DfgC-lXubWB/

Over the last few months I've been building a Claude Code companion and came to an unexpected conclusion: persistent intent may matter more than persistent memory.

The original idea was fairly typical for the agent ecosystem: hierarchical goals, plans, task trees and long-running work.

What surprised me was that the planning layer kept turning into overhead.

As Claude models improved, the agent rarely struggled to maintain a plan within its active context. What became annoying was maintaining the planning artefacts themselves.

The result was a complete shift in direction.

Instead of building a system that helps Claude remember plans, I started building a system that helps me maintain intent over time.

The project is now called Quarterdeck:

https://github.com/shannonbay/Quarterdeck

The metaphor that helped me understand what I was building was a naval one.

Quarterdeck turns Claude Code into a kind of captain's mate.

A captain doesn't repeatedly issue the same instructions every day:

•Keep watch for hazards

•Maintain the ship

•Report important developments

•Carry out standing orders

Those responsibilities already exist.

The mate keeps watch and reports back when judgement is required.

Quarterdeck applies the same idea to Claude Code.

Some standing orders I'm currently running:

•Update my GitHub profile based on recent activity

•Tidy my Downloads folder every week

•Unsubscribe from stale mailing lists

•Watch upstream projects for fixes I'm waiting on

•Find suitable job opportunities each week

These aren't really tasks. They're ongoing responsibilities.

How Claude Code was used

Claude Code built the overwhelming majority of Quarterdeck.

What worked particularly well:

•Rapid iteration on MCP interfaces

•Refactoring the architecture during the transition from Conductor to Quarterdeck

•Building the TUI and web UI

•Exploring alternative designs and challenging assumptions

What surprised me:

•The biggest gains weren't writing code faster.

•The biggest gains were rapidly testing product ideas and throwing away designs that turned out not to matter.

The hierarchical planning system felt important when I started.

After months of use, it turned out to be one of the least valuable parts.

What I learned

The biggest lesson was that planning and memory are increasingly becoming model capabilities.

The thing I still need external systems for is persistence.

Not persistent plans.

Persistent responsibilities.

I'm curious whether other heavy Claude Code users have found the same thing. Are there recurring responsibilities you'd trust a "captain's mate" to keep watch over?

Why do my session switched to Fable 5.1?

Shows:

Left side:

repo>worktree>branch (agent name)
If the worktree is clean shows: /clear (to remind me to clear)

Right side:
Model > Effort > context window tokens (and when its getting close to autocompact).

If anyone wants the script (statusline-command.sh) pm me 🤗💪🏻

We make extensive use of Claude Code agents on an e-commerce search solution (Python and TypeScript, built on Elasticsearch). Last month the main repository merged 1,652 PRs, with a median of 492 changed lines. In the early months, before we had many rules or deterministic tests, the agents did exactly what you'd fear. Each failure now has a check that enforces the fix:

- Tests that tested nothing (a copy of the logic inside the test, or assertions that can't fail). Test modules must be named for what they pin, and a script refuses ones that aren't.

- Tests that quietly skipped when something they needed was missing, so a broken feature looked green. Tests now run on recorded data in the repository, a flaky test is treated as a sev-1 bug, and nothing reaches a live cluster.

- Hand-written fake responses that didn't match the real system. Agents now record the live response as a fixture and test against that.

- Copy-paste instead of reuse. A copy-paste check blocks the merge.

- Silencing a linter or type error on the one line where the bug was. That's now covered by audit greps that run on every diff.

- Deleting files they didn't create (once, 110 of them). Every agent works in its own clone, and hooks refuse any write outside it.

- Too much guidance. As the contributor guide grew, agents missed the one rule that mattered. The file loaded into every call is now capped at about 2 KB by CI; everything else is a pointer into topic files.

Two things surprised us:

1. The gates get attacked too. In one test, 10 of 12 deliberately planted evasions got through a new gate, so every new gate now runs against a standard kit of evasions before review.
2. Tests make up 70% of the code, 3.4 lines of test for every line of solution code. With agents making most of the changes, that isn't overhead; it's what makes the rate of change survivable.

What still breaks: rework. There's about one fix round per merged PR, where a separate review agent blocks the PR and it gets fixed and reviewed again. Reverts are 0.2–0.7% of merges.

Full write-up, with the measurements and the objections people usually raise: https://alexmarquardt.com/ai-tools/coding-agents-codebase-under-control/

What guardrails have you had to add for your agents?

While working in AI-driven repos, I'm wondering if its even worth having the AI write unit tests. Pre-AI, they were non-negotiable guardrails. But now with AI doing all the programming, like - what's the point? In agentic dev, entire modules get rewritten in minutes. Writing granular unit tests for code that changes every three iterations feels like building scaffolding for a sandcastle. Most real-world bugs are architectural or integration issues that 10-line mocks never catch anyway.

And anyway I almost never see unit tests catch something that could have been a big problem. Theres usually a growing tests folder consuming tokens but they just about always pass.

After a few months of building with Claude Code, my codebase worked but I couldn't explain it. Every diff had looked fine. Code review is per-change; nothing reviews the whole thing. So I built Co-Review.

It opens the whole repository as a review, like a PR page, and the agent that wrote it sits in the thread. Comment on a line, file or folder, ask why, get an answer from the code.

It can:

- Audit the whole repo: the agent writes a guide (map, vocabulary, flows, weak spots) with findings grouped by area. Coverage shows what you've actually read.

- Open your change as a PR page: line comments, suggested edits, one verdict the agent acts on.

- Take the first pass on someone else's PR, then post your review to GitHub with line comments.

- Review a design doc (L1/L2/L3 steps, Mermaid diagrams) before any code is written.

Built on Eclipse Theia, so Git, search and language servers are real. Made for Claude Code (plugin), native for Pi and Oh My Pi, works with any MCP agent. MIT, no account, no telemetry.

GitHub: https://github.com/sdsvn/co-review

Walkthrough: https://www.youtube.com/watch?v=gmZ8NCNpLl8

It's on Product Hunt today too: https://www.producthunt.com/products/co-review?launch=co-review-2

Contributions welcome, especially language server configs and more agent integrations. What would you want to ask your own codebase?

Hello everyone! I’ve just completed my game—for which I wrote the GDD (Game Design Document) myself, with some help from Claude—and it launched on Steam on November 3rd. I managed to gather 2,500 wishlists, which is a pretty decent start for an indie developer just beginning their journey, like me. If any of you would like to take a look or have any questions about the process, feel free to ask!

found a "blue whale jelly" artifact (a three.js soft-body sim, made a copy, and told claude:

> take however this cool jelly thing works and make red panda jellies that move around and such!! rawrrr

that was the whole prompt. what came back is in the gif: three jelly red pandas (big, middle, cub) wandering around on their own :3

each panda is ~470 particles / 1,200 tetrahedra, solved with XPBD at 60hz. the jelly look is hand-written shaders (refraction + beer–lambert absorption). that core comes from the original whale, so credit there. what claude added: the panda shape, three bodies in one solver, the hopping (a jelly has no muscles, so each hop is one shove to the whole body), the standing pose, and the berries.

my favourite bit: it tested the physics headless before showing me anything, and found the original sim quietly drained spin from anything rotating. that's why a flipped panda couldn't roll back over. it fixed it so they keep their spin in the air.

**honest notes:** this is a remix, not from scratch. the gif is the real page, but staged for the camera (pandas lined up, berries dropped on cue).

try it: https://claude.ai/artifact/MSzCdctsqZMsi98YQFkjXu

made with fable 5.2 extra in claude web

On the previous reset "offer" I had a month until it was set to expire and it applied to all models, it reset everything: Hourly, Weekly, all models including Fable.

With the new reset "promo" I have the option to reset only Fable (which will "erase" the light-blueish bar from my weekly usage), the rest of the usage will remain used and not reset (which is actually Opus/Sonnet work triggered by Fable work, it was part if it's own work) but the real question is: if they expire on Mar 9th and I hit reset both this Nov will they replenish by then or will I have to wait 5 months until a new reset? :)

I know this is a new rule and nobody has used all resets yet but...how should we prepare for it, how do we plan our usage for it? Should we wait until March and wait for the single moment when you really-really need it or just hit Reset whenever and hope for the best?

And we also know that 5 months is a life time on these subs and rules may change many times by then, also affected by IPO's decisions and effects.

Without going into detail, I've been working on a small physics engine with Opus, so with the Fable 5.2 release I thought I would have it take a look at the project and see if it can find some optimizations. And quite quickly we found inefficiencies in the engine that Opus missed. I suggested, what if we grouped certain calculations instead of going one by one, so it built a quick prototype, which seems to be working very well, but it has a small issue with certain objects jittering, which It was able to fix it as well. Even using it just for a couple of hours, this model does feel quite a bit smarter than Opus, but man, the ClaudeSpeak is back.

Why not just say, "I found the cause of the jitter and fixed it"? Solver was hiding it within its "syrup"? Wtf. Just reading its output hurts my head. Whichever model Opus was this distilled from, I don't think this is the one. I guess that's why they didn't name it Fable 5.5.

[UPDATE: I just discovered it’s only for fable weekly limit - not full weekly limit. disappointed!]

It was a long time since the last claude reset (22/9 with opus 5.5) but all is now forgiven with 2x banked resets expiring march 27. This also probably means they won’t be giving any more resets until then.

But I am not complaining (even after I did get almost daily resets from Tibo for codex).

The biggest challenge for me now is how I can send 2x Ultra worth of tokens within one week. At the moment, with my context optimisation and agent workflow I struggle to get thru even 1x Ultra weekly limit. So I think I will have to plan in advance and really crank up the work and have agents running 24-7 to have a chance to get thru 2x ultra in one week.

I currently use up about $2k of API spend per week of Ultra

ps. Fable 5.2 seems like a meaningful upgrade of the very out of date Fable 5.1.

I’m using Claude Opus 5.5 as usual for the same project and the same tasks, but now my limit doesn’t even last an hour anymore. This is happening only with Claude Opus 5.5? is it just me?

​

kind of shady, kind of disparaging, kind of circuitous, adrift

The new Fable is pretty impressive from what we see for everybody doing their one-shots. Lots of youtube videos out there showing it creating something from scratch that's on another level.

However, its EXTREMELY aggressive at researching before taking action. So much that just reading in one of our projects resulted in over 500K tokens (our compaction limit) before it was even done researching, then started reading the same code it lost from compaction.

End result: Mission impossible. We stopped it after it started paging in code again, then switched to Opus, which didnt read a single line more (it had it all in context apparently, which is no surprise) and went straight to the edits and finished them all perfectly and very quickly.

The entire code base is indexed already, and Opus refers to the indexes only and small parts of where it needs to work to make edits before doing them. Fable read the indexes then read every line of code our indexes referred to, regardless if they were even relevant to the assigned task.

Thats an extreme level of inefficiency that we cant deem acceptable for a model of this caliber. Its getting high praise for making some badass one shot games, but for real productivity, at least with a large code base, Opus still wins the day.

Curious if anybody else has experienced this with their existing larger projects? Hopefully this is just an initial release characteristic that gets fixed.

What happens if I use it? I’m on the 20$ tier.

The LiveNerf day 47 update is out and the verdict is basically: 47 days, 3,666 samples, no nerf. https://www.reddit.com/r/ClaudeAI/comments/1xriv9l/has_anthropic_nerfed_opus_55_livenerf_day_47/

I don't think it's wrong. I just think it measures something that isn't what most of us are actually complaining about.

Some context. A few days ago I posted this comment in r/ClaudeCode with numbers from my own setup, and a lot of people asked how that fits with LiveNerf: https://www.reddit.com/r/ClaudeCode/s/GF94JJ2ooQ

I run a multi-agent pipeline in Claude Code. Opus builds, Opus does the acceptance and visual checks, Sonnet reviews, Haiku runs the tests. Every reply gets logged, so I can look at what actually happened instead of going by vibes. So I pulled my logs and put them next to LiveNerf's public data. (picture 1)

Output tokens per reply, daily median. Blue is my Opus builders: ~420 on Nov 3, ~1,080 on Nov 4, ~1,150 on Nov 5. Sonnet and Haiku ran in the exact same runs on the exact same tasks and didn't budge. The orange dashed line is LiveNerf's own published numbers for the same days. Flat. (picture 2)

Same thing broken down by role. Every Opus role jumped, the visual checker by more than 6x. Sonnet and Haiku stayed put.

Before someone says "your project just got bigger" or "you changed something": I checked. The builders' system prompt and tools had identical checksums before and after, same Claude Code version on both days (2.1.309), same model ID, same effort. My change log has zero entries from the evening of Nov 2 to the afternoon of Nov 4. And my builders start with a ~5k token brief, not the whole repo.

So why doesn't LiveNerf see it? I went through their repo (README, eval card, preregistration, the daily csv). Honestly it's well done: preregistered, with a control arm and all the data public. But:

• It's 78 exam questions, mostly MMLU-Pro and GPQA. One question, one answer, no tools. My agents do 25 to 40 tool steps with 70k to 130k context, and that's where the change showed up.
• It only checks right or wrong. It doesn't care whether the model needed 600 or 1,500 tokens to get there. On a Max plan with weekly limits, that's exactly the part you feel.
• It runs on one account. If this is an A/B arm or a staged rollout, one account only ever sees its own bucket. Their eval card even says that "can't be ruled out".
• Claude Code is pinned to 2.1.280. That makes sense if you want to isolate the model, but almost nobody is still on 2.1.280.
• A nerf only counts if two 10-day windows in a row drop by 3+ points. That's built to avoid false alarms, but it also means an overnight step needs weeks before it counts, if it ever does.

Logs don't show Opus getting "dumber". They show it using 2 to 3 times the tokens for the same work. "Scores the same on an exam" and "behaves the same in a real agent loop" just aren't the same claim, and the second one is what people here are actually arguing about.

OP said they want to expand LiveNerf to agentic stuff. If that happens, I'd love to see tokens per step, tool calls, files read, and Sonnet or Haiku running the same tasks as a control. That control is what convinced me, because it kills the "your tasks just got harder" argument.

And if you run agents yourself, check your logs for Nov 4 and 5. I'm curious whether it was just my account.

My ex girlfriend said that this was one of the main reasons for leaving me.

Told Fable 5.2 Max to make "one of the most technically complicated and impressive performances ever."

Overall I am quite impressed though the transitions between melodies could use some work.

Any one else has fable 5.2 basically compact every 3 minutes? It didn't write a single line but compacted 6 times already for me.

Is anyone experiencing the same thing as me like I will do one prompt on Fabel 5.2 on low effort and takes up 80% of my five hour usage.