Arys Wisnu

Physical media junkie.

[Arys Wisnu @ARYSWISNU]

Cooking is 90% timing. Ever started "rebus ayam" and then got distracted by a phone call?

I just pushed a major update to MasakApa AI to make sure that never happens again.

[Arys Wisnu @ARYSWISNU]

Ternyata ngomongin immigrants...

[The White House @WhiteHouse]

They walk among us.

https://t.co/7HysdUuNVM

[Arys Wisnu @ARYSWISNU]

Went through the publicly released US gov UFO files this morning and found this handwritten anagram/code page inside one of the PDFs.

This rabbit hole is already getting weird.

https://t.co/k89dzTRySU

[Arys Wisnu @ARYSWISNU]

@PosIndonesia halo tolong cek dm

[Arys Wisnu @ARYSWISNU]

@HeyGen Hyperframes

[Ibrahim Arief @ibamarief]

Mengapa Negara Menzalimi Suami Saya, yang Tulus Berkorban Banyak Untuk Negara?

Sebagai istri, sakit hati rasanya. Enam belas tahun aku kenal Ibam, dia ngga money oriented. Niatnya tulus. Kalau sudah mau bantu, dia akan benar-benar bantu.

Ibam dituntut penjara 15 tahun dan harus bayar Rp16,9 miliar, kalau tidak maka pidananya ditambah 7,5 tahun.

Berarti, Ibam dituntut 22,5 tahun penjara.

Ibam, yang pernah menolak tawaran puluhan miliar karena merasa misi bantu negara lewat bangun teknologi masih belum selesai.

Sekarang ironisnya dituduh korupsi. Padahal sampai 57 saksi diperiksa, tidak ada satu pun bukti Ibam memperkaya diri. Tidak ada konflik kepentingan untuk memperkaya orang lain.

Dia hanya konsultan teknis, rela tolak tawaran asing, turun gaji demi negara, ngga punya jabatan dan kewenangan, selalu profesional dan netral dalam kasih masukan, tapi terjebak dalam pusaran para elite birokrasi.

Masukan teknis Ibam yang sudah terdokumentasi baik, transparan akan kelebihan dan kekurangan, diceritakan sepotong-sepotong saja oleh pejabat pengadaan. Sehingga seakan-akan Ibam memaksa hanya Chromebook.

Untungnya, Ibam punya banyak dokumentasi yang sudah jadi bukti di persidangan. Sudah terungkap di sidang bahwa:

1. Ibam bukan pejabat, tapi konsultan yayasan. Gaji Ibam sama sekali bukan dari APBN.

2. Ibam baru kenal Nadiem setelah dia jadi menteri. Ngga ada persekongkolan, dan ngga pernah ketemu personal.

3. Di banyak bukti chat & notulen rapat: Ibam tidak mengarahkan pengadaan, tidak buat kajian, bahkan Ibam minta kementerian untuk uji Chromebook dulu.

4. Pejabat Eselon I akhirnya mengakui: dia yang menolak masukan pengujian Ibam, dia yang memutuskan Chromebook lewat SK yang dia keluarkan.

5. Ahli IT telah menyatakan masukan Ibam sudah netral dan profesional, sesuai best practice keahlian, serta benar dalam menyerahkan keputusan ke kementerian.

Puncaknya, nama Ibam dicatut ke dalam SK pengadaan yang tidak pernah dia ketahui sebelumnya. Dalam pengesahan kajian Chromebook yang ditugaskan SK, tidak ada tanda tangan Ibam.

Terungkap juga di sidang, belasan pejabat, termasuk yang berupaya ‘menyalahkan’ Ibam, mengakui telah menerima ratusan juta rupiah suap dari vendor. Namun mereka semua bebas, tidak ada yang jadi tersangka.

Disaat mereka bebas, Ibam ditahan dan dituntut penjara. Bagiku perkara ini jelas. Suamiku bukan pelaku, tapi korban permainan elite birokrasi yang seenaknya melempar semua keputusan mereka pada Ibam.

Sekarang, kami hampir sampai di ujung jalan.

Ibam dituntut 22,5 tahun penjara.

Dua terdakwa lain, pejabat Eselon II di Kemendikbud, yang mengatur pengadaan dan sudah mengakui ada aliran dana sampai miliaran rupiah, dituntut 6 tahun saja.

Semakin kontras ketika surat tuntutan sendiri mengakui: tidak ada aliran dana ke Ibam.

Tuntutan bilang di laporan SPT 2021, kekayaan Ibam naik Rp16,9 miliar. Ibam sudah tunjukkan bukti di persidangan kalau itu dari saham Bukalapak yang didapat jauh sebelum Ibam menjadi konsultan Kemendikbud, tidak ada kaitannya sama sekali dengan Chromebook atau Gojek.

Bukti itu ditolak JPU dalam tuntutannya. Mereka bilang karena Ibam sudah resign, sahamnya hangus. Mereka tidak paham kata-kata dalam surat pemberian saham, bahwa yang hangus hanya “saham yang belum diberikan”. Padahal, sebelum resign juga ada sebagian saham yang sudah diberikan.

JPU menyatakan, karena mereka tolak bukti itu, Rp16,9 miliar Ibam diduga hasil korupsi, jadi mereka tuntut 15 tahun ditambah 7,5 tahun.

Bagi kami, ini puncak dari kezaliman. Ibam yang tidak pernah, sekali lagi, TIDAK PERNAH ADA ALIRAN DANA SAMA SEKALI, dikriminalisasi atas prestasinya bantu negara, yang tidak ada hubungannya dengan perkara.

Dua minggu lagi putusan Ibam akan dibacakan oleh Majelis Hakim, kami tetap berharap keadilan putusan bisa sesuai dengan fakta persidangan.

Karena, ini bukan sekedar perkara hukum, ini menyangkut nasib seseorang, masa depan keluarga kami, anak-anak kami, serta kemerdekaan kami sekeluarga.

Setahun terakhir ini adalah masa yang sangat berat bagi kami. Keluarga kami kehilangan penghasilan, kesehatan jantung Ibam kian memburuk, bahkan tabungan hidup kami terkuras habis untuk biaya medis dan biaya hukum.

Namun, aku bersaksi bahwa Ibam adalah seorang perintis. Hidupnya penuh perjuangan dari kecil, insya Allah kami siap bangun dari nol lagi.

Hanya saja, jika pengabdian untuk Indonesia harus dibayar semahal ini. Jika bukti persidangan sudah seterang ini, dan jika upaya mengkambinghitamkan Ibam sudah sekentara ini, dia tetap dipenjara puluhan tahun...

Ini adalah ketidakadilan yang teramat pahit.

Bukan hanya bagi Ibam, tapi bagi siapa pun yang pernah atau akan bantu bangsa ini dengan niat tulus.

Apa memang berbakti bagi merah putih seberbahaya ini?

Apa memang tidak ada keadilan bagi orang jujur yang sudah berkorban banyak bagi negara?

Tolong bantu kami mencari keadilan untuk Ibam selagi masih ada waktu. Mohon bantu bagikan tulisan ini, pada rekan atau kerabat, konsultan atau pejabat, siapapun yang bisa bantu menyuarakan keadilan dan memberi perhatian.

Agar tidak ada lagi profesional seperti Ibam yang jadi korban kriminalisasi.

Jakarta, 16 April 2026
Ririe - Istri dari Ibrahim Arief (Ibam)

[Chaofan Shou @Fried_rice]

Claude code source code has been leaked via a map file in their npm registry!

Code: https://t.co/jBiMoOzt8G

[Arys Wisnu @ARYSWISNU]

AetherMaster is the audio mastering plugin I made for my own workflow: fast, honest, and fully local. It's ready as a VST3, listens to 8 seconds of the incoming mix/premaster, analyzes the audio, then applies EQ, compression, saturation, width, and limiting moves directly.

[Stanlee | Web developer @stanlee0nX]

“npm install” :

[Arys Wisnu @ARYSWISNU]

Richard Hendricks' Pied Piper in real life

[Google Research @GoogleResearch]

Introducing TurboQuant: Our new compression algorithm that reduces LLM key-value cache memory by at least 6x and delivers up to 8x speedup, all with zero accuracy loss, redefining AI efficiency. Read the blog to learn how it achieves these results: https://t.co/CDSQ8HpZoc

[Andrej Karpathy @karpathy]

Software horror: litellm PyPI supply chain attack.

Simple `pip install litellm` was enough to exfiltrate SSH keys, AWS/GCP/Azure creds, Kubernetes configs, git credentials, env vars (all your API keys), shell history, crypto wallets, SSL private keys, CI/CD secrets, database passwords.

LiteLLM itself has 97 million downloads per month which is already terrible, but much worse, the contagion spreads to any project that depends on litellm. For example, if you did `pip install dspy` (which depended on litellm>=1.64.0), you'd also be pwnd. Same for any other large project that depended on litellm.

Afaict the poisoned version was up for only less than ~1 hour. The attack had a bug which led to its discovery - Callum McMahon was using an MCP plugin inside Cursor that pulled in litellm as a transitive dependency. When litellm 1.82.8 installed, their machine ran out of RAM and crashed. So if the attacker didn't vibe code this attack it could have been undetected for many days or weeks.

Supply chain attacks like this are basically the scariest thing imaginable in modern software. Every time you install any depedency you could be pulling in a poisoned package anywhere deep inside its entire depedency tree. This is especially risky with large projects that might have lots and lots of dependencies. The credentials that do get stolen in each attack can then be used to take over more accounts and compromise more packages.

Classical software engineering would have you believe that dependencies are good (we're building pyramids from bricks), but imo this has to be re-evaluated, and it's why I've been so growingly averse to them, preferring to use LLMs to "yoink" functionality when it's simple enough and possible.

[Arys Wisnu @ARYSWISNU]

OpenClaw = hacker playground
Claude = polished product your boss will actually approve

[Claude @claudeai]

You can now enable Claude to use your computer to complete tasks.

It opens your apps, navigates your browser, fills in spreadsheets—anything you'd do sitting at your desk.

Research preview in Claude Cowork and Claude Code, macOS only.

[Arys Wisnu @ARYSWISNU]

MasakApa AI: AI Cooking Assistant. Mainly for Indonesia recipes. https://t.co/UQZRPrf0dT via @producthunt

[Ibrahim Arief @ibamarief]

Since last year, I've arguably been wrongfully accused in a state corruption case.

To defend my innocence, I spent past 6 weeks building an agentic AI swarm that:

Analyzed 4700+ pages court docs
Mapped 8900+ testimonies
Found dozens of contradictions

This is how I fight 👇🏼

First off, some context may be necessary.

Even though I'm accused in a state corruption case, I'm not a government official. I'm a software engineer. I spent over 15 years building large-scale tech systems across Europe and Indonesia. I've led engineering teams of up to 600 people and helped grow a small tech startup into a unicorn.

In 2016, I moved back from Europe to Indonesia, because I believe technology at scale could make a real difference to the millions of people in the nation.

Six years ago, working as a tech consultant under a nonprofit foundation, I started advising Indonesia's Ministry of Education on building large-scale technology platforms.

Public sector work pays significantly less than private sector, and I took close to a 50% pay cut to make the switch. I was fine with that. Using what I knew to help underserved communities in Indonesia felt like the right trade.

Our mission was to build a user-centric superapp for public education, specifically for teachers and public schools, the kind of work the private sector ignores because there's no money in it.

At some point, officials at the ministry asked for my input on one of their procurement plans. I helped them work through the technical details, shared what I knew, laid out the pros and cons, and recommended a set of tests they should run to determine which options were the most suitable.

By the time they made their final decision and executed the procurement, I had already resigned from the consulting work, so I didn't think much of it.

Fast forward to May 2025. My house was raided as part of a newly opened corruption investigation tied to that procurement. Two months later, I was named a suspect and placed under city detention due to my health.

The trial started in January 2026. We've been through more than a dozen sessions so far, and not a single piece of evidence or testimony has been presented showing I received a single cent from the procurement.

What came to light was the opposite: evidence and testimony that my recommendations were neutral and likely were ultimately ignored by the ministry's own team, who went ahead and made the call on their own.

So why am I the one on trial? Because the ministry officials who did take money from the procurement vendors needed someone to blame for the decisions they made. Blaming an outside consultant is the easy way out.

Witness testimonies in court has shown that the officials actively directed the procurement while claiming it was done on my instructions and even misled their own team within the ministry by saying I held a position of authority.

We needed evidence to dispute those accusations, questions to cross-examine the witnesses, and we needed them fast.

This is where my AI comes in.

A few days before the trial began, we received a 4400-page printed document containing all the witness statements collected during the investigation, plus several hundred pages of other related documents.

The information asymmetry is staggering. Those with deep enough pockets to hire large law firms can throw dozens of paralegals and associates at a document like that and mount a proper defense on short notice.

I didn't have that kind of money. By then, I had been out of work for more than six months. The AI startup I founded had to shut down. Our investors asked us to return their funding. I had to lay off the entire team.

Most of my lawyers are friends of my wife from her college days, who stepped up and waived most of their fees because they could see I was being railroaded.

The whole situation felt hopeless. But somewhere in the middle of the despair, a spark lit up.

Combing through and analyzing thousands of pages of documents is exactly the kind of problem AI was built for.

I've built AI systems before, so I know the key to applying AI to a real-world problem is understanding the strengths and limitations of the available models, and figuring out how to make things not just work, but work efficiently enough to put into production.

I was placed under city detention due to health issues with my heart, compounded by a tumor that has been growing rapidly over the past few months. But it also means I still have access to my dev PC.

So I started with small experiments. My lawyers found a printing service that could scan the thousands of pages in a couple of days. At first, I tried simply uploading the scanned PDF into existing chatbots like ChatGPT, but the file was far too large for anything they could handle.

Even when I managed to get it working through external cloud storage, the results were atrocious. Half of the strategies and "facts" the models surfaced were hallucinations. That wouldn't just be useless in court, it's actively dangerous and can jeopardize my defense.

My experience building complex AI systems told me that the key to reducing those hallucinations is better data preprocessing.

So I spent the first couple of weeks focusing on parsing the uploaded PDFs, running various kinds of text extraction, and eventually settled on building an agentic AI swarm that performs multiple layers of preprocessing and analysis.

This multi-step analysis by several AI agents that swarm the PDF and extract different aspects of the case produces a dense knowledge graph where we can even trace the flow of money involved.

My lawyers can now easily browse, filter, and search through nearly 9000 witness statements. We even discovered several witnesses with duplicate testimony, raising suspicion of coordinated efforts or tampering among them.

But I didn't stop there. The processing chain includes several higher-level intelligence layers that draw from all the signals in the extracted knowledge graph. These layers add semantic understanding that powers a Chat AI feature, where we can ask specific questions about the case and get grounded answers.

I even built a self-reflective sub-agent that automatically challenges and inspects the results to make sure there are zero hallucinations.

Overall, the AI has helped me and my legal team uncover the big picture of what actually happened, and build questions that span hundreds of separate testimony sessions, giving us an unprecedented ability to cross-examine witnesses in court and significantly improved our defenses.

But I have grander vision than just helping my own legal team. Indonesia's legal system is severely overburdened, with a huge number of cases flowing through the courts every year. This kind of AI could be a useful tool not just for lawyers, but also for judges and prosecutors trying to make sense of their caseloads.

With the cross-examinations we've conducted and the weight of evidence that has come to light, we are aiming for an acquittal.

Should that be the case, my pledge is to keep building this AI platform into something that can meaningfully improve the quality of justice in our legal system: by helping investigators analyze cases more thoroughly and shine a light on any potential crimes, by raising the standard of what prosecutors bring before a judge, and by giving lawyers the ability to uncover the truth in their clients' cases faster than ever before.

Because in the end, I want what I've built to help more than just myself. I believe it can ease the burden on our judges and raise the quality of justice across the system in Indonesia.

[Qwen @Alibaba_Qwen]

🚀 Introducing the Qwen 3.5 Small Model Series
Qwen3.5-0.8B · Qwen3.5-2B · Qwen3.5-4B · Qwen3.5-9B

✨ More intelligence, less compute.
These small models are built on the same Qwen3.5 foundation — native multimodal, improved architecture, scaled RL:
• 0.8B / 2B → tiny, fast, great for edge device
• 4B → a surprisingly strong multimodal base for lightweight agents
• 9B → compact, but already closing the gap with much larger models
And yes — we’re also releasing the Base models as well.
We hope this better supports research, experimentation, and real-world industrial innovation.
Hugging Face: https://t.co/wFMdX5pDjU
ModelScope: https://t.co/9NGXcIdCWI

[Arys Wisnu @ARYSWISNU]

That's about it. Happy to see more recipes are generated everyday.

I placed all recipes that everyone generated since the beta-launch last week on the site https://t.co/IHfjC3Crx6, including some feedback from beta users.

[Arys Wisnu @ARYSWISNU]

Cooking is 90% timing. Ever started "rebus ayam" and then got distracted by a phone call?

I just pushed a major update to MasakApa AI to make sure that never happens again.

[Arys Wisnu @ARYSWISNU]

The "under-the-hood" upgrade to make it all seamless, I've overhauled the Shopping List. It now uses LLM to distinguish between "cooking measurements" and "buying quantities."

It knows you don't buy "3 sendok makan kecap asin", it just tells you to grab a bottle.