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One codebase, three identical PRs, three different CodeRabbit review profiles quiet - only the most important feedback chill - balanced (the default) assertive - most comprehensive Dial in the review depth that fits your team. More signal, less noise, tuned to your team.

21,927,402 просмотров • 3 месяцев назад •via X (Twitter)

Комментарии: 36

Фото профиля Kelvin Lee
Kelvin Lee3 месяцев назад

I had a message today saying my trial was ending , very sad moment until I subscribed. Guys thank you for such awesomeness 🤙🏻 🫶🏼 sending some man love

Фото профиля CodeRabbit
CodeRabbit3 месяцев назад

🫂

Фото профиля S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles.
S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles.2 месяцев назад

Ok this is leaning more towards my style. Will dive in once I have a proper set up.

Фото профиля CodeRabbit
CodeRabbit2 месяцев назад

🤝

Фото профиля S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles.
S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles.2 месяцев назад

Orange bunny is fren 😂

Фото профиля Toufiq Qureshi
Toufiq Qureshi1 месяц назад

Genuine question for CodeRabbit 👀 I’m using Claude Code to write my code, and then CodeRabbit reviews that same code and says: “Here’s an issue with your code.” So I’m curious — what makes your review different? If the underlying AI reasoning is similar, why can one AI confidently write the code while another confidently flags it as wrong? Is it the context, system prompt, tools, review methodology… or something else? Would love to understand what’s actually happening under the hood. 🤔

Фото профиля Borboleta silenciosa
Borboleta silenciosa2 месяцев назад

Confesso que só agora fui descobrir o que é o @coderabbitai 😂 Uma IA que revisa códigos, encontra erros e sugere melhorias. Pelo tanto de elogios que vejo por aqui, parece que os programadores ganharam um ótimo parceiro de trabalho! 🤖🐰 vou indicar para meu filho que é TI Conheça o CodeRabbit

Фото профиля Dipanshu Kushwaha
Dipanshu Kushwaha2 месяцев назад

This is a neat way to customize the review process. It's great to have options for different needs.

Фото профиля Talha Raza
Talha Raza1 месяц назад

three profiles, same codebase, but who decides what counts as signal. the quiet mode isn't less noise, it's less accountability. teams tune out what they don't want to hear

Фото профиля Shashank Bhardwaj
Shashank Bhardwaj2 месяцев назад

You are my best friend, bro

Фото профиля Noah Sheldon
Noah Sheldon2 месяцев назад

Customisation of review agents are amazing thanks

Фото профиля CodeRabbit
CodeRabbit2 месяцев назад

Glad you like it!

Фото профиля Ariel Lillie
Ariel Lillie1 месяц назад

dial in quiet when codebase reviews get noisy

Фото профиля Salise
Salise1 месяц назад

this sounds super useful for tailoring feedback to team needs. nice way to cut through the noise

Фото профиля BiOne_98
BiOne_981 месяц назад

This is not three reviewers and not three analysis depths on the same PR. It is one pipeline — change graph, tools, agent pass, judge — with a publication threshold and some static-analysis strictness cranked up or down. Docs make that explicit: PHPStan under chill is roughly level 3 (real type/offset bugs); under assertive it jumps to level 8 (dead code, null safety, typehints). The “intelligence” does not change. The policy for what is worth a comment does. “One codebase, three identical PRs” is a weak claim for three reasons. 1. LLM review is stochastic. Without a fixed SHA, model version, identical knowledge-base/learnings context, and a comment-level diff, this is a montage, not an experiment. Three chill runs can already diverge. 2. If analysis is identical and only the emission filter changes, the comparison is fair — then say that: you are cutting output. If the agent is re-run with a different system prompt, the findings are not comparable: coverage and hallucinations both move. 3. “Most important” is undefined. Importance without a risk model (prod impact × likelihood × blast radius) is prompt taste. Quiet mode cuts noise and raises false negatives on the hard stuff: cross-file logic, races, API contracts, migrations. That is already where AI review is weak — decent precision on individual comments, poor completeness. The two extremes are not symmetric. • assertive burns trust faster than it catches bugs. Alert fatigue on a bot is worse than missed nits: the team starts skipping every comment, including security. • quiet creates a false “all clear.” No comment ≠ no defect. Especially dangerous for junior-heavy teams. A three-level enum is too coarse. A real review policy needs orthogonal axes — some of which CodeRabbit already has, and which the tweet hides: • category: correctness / security / observability / style / docs • severity + confidence (block merge vs nit) • path policy: src/api/** ≠ **/*.test.ts ≠ generated/lockfiles • dedup against CI you already run (ESLint, Ruff, Semgrep). Repeating a failing pipeline check is noise, not “comprehensive review” • separate max-depth analysis from filtered publication. Otherwise quiet does not just stay silent — it searches worse Practical setup for a mature team: chill or quiet + path_instructions + style tools disabled if they already live in CI + hard pre-merge checks only on security/correctness. Keep assertive for onboarding, legacy audits, or repos with no linters. Not as the rabbit’s personality. As an SLO: how many comments per 100 LoC of diff the team will actually triage. Short version: useful as an SNR knob. Not evidence of deeper engineering. It is prompt/policy routing with three labels. The real question is whether quiet drops only nits, or also the defects a human reviewer was supposed to catch.

Фото профиля ag
ag2 месяцев назад

this is awesome massive respect for tuning review depth

Фото профиля dophp.dev
dophp.dev2 месяцев назад

I would love assertive but credits don’t even last on chill. Frustrating as I want to use the tool but it is so restrictive in its availability for my code for some reason.

Фото профиля Chris Petersen
Chris Petersen2 месяцев назад

Sentinel Fuel Yield ($SNFY) is a Solana-based security infrastructure token designed to protect crypto users from scams, rug pulls, and malicious transactions in real-time. Built by someone who got scammed and decided to fix the problem instead of walking away, Sentinel uses AI-powered transaction analysis to flag dangerous wallets, phishing attempts, and suspicious smart contracts **before** users lose their money. This isn't a meme coin. This is a security layer the entire Web3 space desperately needs. --- ## 💔 **THE PROBLEM** **Crypto scams stole $5.6 billion in 2023 alone.** Every day, thousands of people: - Connect their wallets to fake dApps - Send funds to scammer addresses

Фото профиля CryptoSuggest
CryptoSuggest2 месяцев назад

Revenue → Buyback → Burn. That's a model worth watching. Execution will decide everything. 👀

Фото профиля Amanda Lauren Machen
Amanda Lauren Machen2 месяцев назад

Cloud flare needs constant repair , so much ! My mind is creating rain with thoughts and projecting plasma from the sun into the air to make rain 🌧️.

Фото профиля Blondie Spark NFT
Blondie Spark NFT1 месяц назад

Great to see customizable review profiles! Quiet, chill and assertive on the same codebase – how do these practically affect team productivity and the number of issues found long-term? More signal, less noise.

Фото профиля Jone smitt
Jone smitt3 месяцев назад

From code rabbit Ai please help for me

Фото профиля Navneet Kaur
Navneet Kaur2 месяцев назад

Having options for how much feedback you get is a great idea.

Фото профиля nellyd
nellyd1 месяц назад

I really need $550 and I just will appreciate so I not broke and stessed out every. Day

Фото профиля RajX-dev
RajX-dev2 месяцев назад

I made something better than you guys Reach out to me . This is my website

Фото профиля していたー
していたー1 месяц назад

これめっちゃ便利そう!👍

Фото профиля Bia Bia
Bia Bia1 месяц назад

👏👏

Фото профиля 汤姆
汤姆2 месяцев назад

可以可以

Фото профиля PD_KoDak
PD_KoDak2 месяцев назад

This is exactly how AI code review should work. Not every team needs more comments. They need the right comments. Quiet when you want signal. Chill for balance. Assertive when you want to leave no stone unturned. More signal, less noise.

Фото профиля Chris
Chris2 месяцев назад

J

Фото профиля Ajcrowlex1177
Ajcrowlex11772 месяцев назад

Where is my apology? (Mothers side of family) (Liberal friends from college) (Two girlfriends) Fuck all of you bastards, the truth shall prevail

Фото профиля mohan lal
mohan lal2 месяцев назад

B. Vo kabhi PM nahi banega

Фото профиля Mrfuszy
Mrfuszy2 месяцев назад

Ones on meth, ones on coke, the others on Adderall! Help is out there my friend stay strong were gonna get thrw this

Фото профиля Parvez
Parvez2 месяцев назад

BAS

Фото профиля kong
kong2 месяцев назад

70

Фото профиля SD House Mafia
SD House Mafia2 месяцев назад

Lmao no thx

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