Dedy Kurniawan Santoso

@dedy_ks

Exploring cloud computing solution. Kubernetes, Docker, AWS

Samarinda-Semarang-Yogyakarta

Joined February 2011

285 Following

221 Followers

7.7K Posts

Dedy Kurniawan Santoso @dedy_ks

about 1 month ago

kuterima kekalahanku melawan pengisian coretax, kurang bayar 96ribu entah bagaimana. apa gara2 cashback shopee affiliate

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Dedy Kurniawan Santoso @dedy_ks

about 1 month ago

jam jam coretax down

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dedy_ks retweeted

Rumail Abbas

@Stakof

about 2 months ago

Sewaktu nge-tag BNI, status saya akhirnya direspon oleh BNI lewat akun resminya. BNI bilang mereka "juga pihak yang terdampak" dalam kasus Rp28 miliar dana umat Paroki Aek Nabara. Secara teknis benar. Tapi kan ada jurang besar antara "terdampak" dan "bertanggung jawab". Apakah mereka sedang coba menyamarkan dua kata itu jadi satu? BNI memang keluar Rp7 miliar talangan pada 26 Maret 2026. Reputasi mereka tergerus di mana-mana (lihat saja di X). OJK dan BI sedang mengawasi ketat, dan bisa saja ada sanksi kalau terbukti lalai awasi internal. Secara bisnis, ya, mereka rugi. Tapi "terdampak" bukan sinonim "korban", bukan? Benarkah klaim BNI, yaitu "ada oknum di luar sistem resmi"? 1. Andi Hakim Febriansyah bukan tukang sapu. Dia Kepala Kantor Kas BNI Unit Aek Nabara resmi. 2. Selama 7 tahun (2019 sampai 2026), dia memakai fasilitas resmi BNI sepenuhnya: layanan pick-up service untuk jemput uang, bilyet deposito BNI, rekening koran BNI, seragam, kartu identitas pegawai. 3. Suster Natalia dan pengurus Credit Union tidak menyerahkan uang ke "Andi pribadi". Mereka menyerahkannya ke BNI sebagai institusi, lewat mekanisme yang BNI sendiri sediakan. 4. Semua data transaksi tercatat di sistem BNI. Tapi yang lucu, BNI justru meminta CU menyediakan "bukti pendukung" berulang kali. Padahal catatannya ada di server mereka sendiri. Kalau seorang pegawai bank memakai jabatan, fasilitas, dan dokumen resmi bank untuk menipu 1.900 umat selama 7 tahun tanpa terdeteksi audit internal, itu bukan "oknum di luar sistem". Itu namanya kegagalan sistem! Secara hukum, ada prinsip tanggung gugat pengganti (Grok bilang, istilah ini disebut: vicarious liability). Bank wajib bertanggung jawab atas tindakan pegawainya yang dilakukan dalam kapasitas jabatan. Ini bukan opini saya, Gais. Ini ada di UU No. 10/1998 tentang Perbankan dan POJK tentang perlindungan nasabah. Di satu sisi, BNI adalah Bank BUMN, dengan aset triliunan rupiah, punya tim hukum dan tim humas korporat yang sibuk membangun narasi "kami juga korban". Di sisi lain, ada 1.900 umat Paroki Aek Nabara. Mayoritas dari mereka adalah petani dan buruh kecil. Mereka menabung selama lebih dari 40 tahun, rupiah demi rupiah, untuk biaya sekolah anak, dan biaya sakit. Rencana masa depan yang sederhana, bukan? Jawaban BNI sah secara korporat. Strategi "oknum dan tunggu dokumen" itu klasik. Tapi dari sisi keadilan, ini sangat miskin empati. Uang itu tabungan umat kecil yang dikumpulkan selama 40 tahun, bukan duit korporasi yang bisa dihitung ulang di pembukuan kuartal berikutnya. Kalau setiap kali ada pegawai berulah, jawaban resmi bank selalu "itu oknum, bukan kami", lalu kepada siapa nasabah harus percaya? Besok saya mau menutup rekening saya. Kalau masih antre, ya, saya tarik semua uang saya dari sana. Kalian sendiri gimana baca sikap BNI sejauh ini?

Stakof's tweet photo. Sewaktu nge-tag BNI, status saya akhirnya direspon oleh BNI lewat akun resminya.

BNI bilang mereka "juga pihak yang terdampak" dalam kasus Rp28 miliar dana umat Paroki Aek Nabara. Secara teknis benar. Tapi kan ada jurang besar antara "terdampak" dan "bertanggung jawab".

Apakah mereka sedang coba menyamarkan dua kata itu jadi satu?

BNI memang keluar Rp7 miliar talangan pada 26 Maret 2026. Reputasi mereka tergerus di mana-mana (lihat saja di X). OJK dan BI sedang mengawasi ketat, dan bisa saja ada sanksi kalau terbukti lalai awasi internal.

Secara bisnis, ya, mereka rugi.

Tapi "terdampak" bukan sinonim "korban", bukan?

Benarkah klaim BNI, yaitu "ada oknum di luar sistem resmi"?

1. Andi Hakim Febriansyah bukan tukang sapu. Dia Kepala Kantor Kas BNI Unit Aek Nabara resmi.

2. Selama 7 tahun (2019 sampai 2026), dia memakai fasilitas resmi BNI sepenuhnya: layanan pick-up service untuk jemput uang, bilyet deposito BNI, rekening koran BNI, seragam, kartu identitas pegawai.

3. Suster Natalia dan pengurus Credit Union tidak menyerahkan uang ke "Andi pribadi". Mereka menyerahkannya ke BNI sebagai institusi, lewat mekanisme yang BNI sendiri sediakan.

4. Semua data transaksi tercatat di sistem BNI. Tapi yang lucu, BNI justru meminta CU menyediakan "bukti pendukung" berulang kali. Padahal catatannya ada di server mereka sendiri.

Kalau seorang pegawai bank memakai jabatan, fasilitas, dan dokumen resmi bank untuk menipu 1.900 umat selama 7 tahun tanpa terdeteksi audit internal, itu bukan "oknum di luar sistem".

Itu namanya kegagalan sistem!

Secara hukum, ada prinsip tanggung gugat pengganti (Grok bilang, istilah ini disebut: vicarious liability). Bank wajib bertanggung jawab atas tindakan pegawainya yang dilakukan dalam kapasitas jabatan.

Ini bukan opini saya, Gais. Ini ada di UU No. 10/1998 tentang Perbankan dan POJK tentang perlindungan nasabah.

Di satu sisi, BNI adalah Bank BUMN, dengan aset triliunan rupiah, punya tim hukum dan tim humas korporat yang sibuk membangun narasi "kami juga korban".

Di sisi lain, ada 1.900 umat Paroki Aek Nabara. Mayoritas dari mereka adalah petani dan buruh kecil. Mereka menabung selama lebih dari 40 tahun, rupiah demi rupiah, untuk biaya sekolah anak, dan biaya sakit.

Rencana masa depan yang sederhana, bukan?

Jawaban BNI sah secara korporat. Strategi "oknum dan tunggu dokumen" itu klasik. Tapi dari sisi keadilan, ini sangat miskin empati. Uang itu tabungan umat kecil yang dikumpulkan selama 40 tahun, bukan duit korporasi yang bisa dihitung ulang di pembukuan kuartal berikutnya.

Kalau setiap kali ada pegawai berulah, jawaban resmi bank selalu "itu oknum, bukan kami", lalu kepada siapa nasabah harus percaya?

Besok saya mau menutup rekening saya. Kalau masih antre, ya, saya tarik semua uang saya dari sana.

Kalian sendiri gimana baca sikap BNI sejauh ini?

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Dedy Kurniawan Santoso @dedy_ks

2 months ago

@HappyCiu @ArvinHonami Sudah release bang di web idx laporan full yearnya

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Who to follow

Software Copy-Paster - Mostly speak in @golang while learning others

Dedy Kurniawan Santoso @dedy_ks

2 months ago

@SimmonsAaronP @aakashgupta Microsoft ship both classic Outlook and Outlook (new) , so they coexist and none of it works

dedy_ks retweeted

ahmet alp balkan

@ahmetb

3 months ago

Dropping new kubectx feature after 2M downloads since last release that was 1.5yrs ago: You can now create shells targeting a specific k8s cluster. This prevents targeting the wrong cluster when you change your default context globally. $ brew upgrade kubectx

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dedy_ks retweeted

Ibrahim Arief

@ibamarief

3 months ago

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.

ibamarief's tweet photo. 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.

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dedy_ks retweeted

Bardan - Digital Marketer

@bardanslm

3 months ago

setelah 7 tahun ayah meninggal, ada seorang pria yg deketin ibu saya. sebagai anak posesif dan sayang almarhum ayah, tentu saya larang ibu deket pria baru dan menikah lagi. namun ternyata pria ini cukup gentle, saya dihubungi langsung oleh beliau. jujur saya jadi berasa punya anak cewek yg dideketin cowok dan mau minta restu 😅, padahal ini ibu sendiri ini seiring waktu berjalan dan banyak merenung (tentu dengan tangisan karna inget ayah). akhirnya saya ikhlaskan ibu menikah lagi. ibu bertahun2 sudah setia berkorban ngurusin ayah yg struk dan sakit, ibu bertahun2 kerja banting tulang agar saya bisa kuliah. kalau ini kebahagiaannya, saya jg bahagia. ketika lagi acara lamaran, saya di "tembak" oleh pria yg jadi ayah tiri saya sekarang. "a bardan waktu itu kenapa menolak saya?" suasana hangat pada ketawa orang2, saya ambil mic membalas "iya pak, saya mau ngetes seberapa cinta bapak dengan ibu saya soalnya, kalau cuma karna saya larang bapak nyerah brarti kurang kuat itu cintanya 😁" suasana makin rame dan pada ketawa semua. di hari itu saya jg happy, karna saya tau saya bertambah dewasa, ibu saya dan semua orang disitu happy. itulah hidup, chapter 1 ke chapter berikutnya tidak pernah ketebak akan seperti apa, enjoy dan nikmati saja~

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Dedy Kurniawan Santoso @dedy_ks

3 months ago

@sama Same term that Anthropic reject?

dedy_ks retweeted

HIDEO_KOJIMA

@HIDEO_KOJIMA_EN

3 months ago

Our customary “KJP End of the Month Celebration.”

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dedy_ks retweeted

ilham

@ilhamfputra

4 months ago

i built pasal(.)id during the @claudeai hackathon! 280 million indonesians access their laws through government pdfs scattered across 1,200+ websites. no search. no structure. just pdfs. there's no single ideal place to look up indonesian law. pasal(.)id changes that. we parse government pdfs into clean structured text and expose it through an MCP server. connect claude, ask a legal question about indonesia, get an answer with exact article citations. real law, not hallucination. but here's what gets me excited: at scale, parsing 40k+ pdfs will have edge cases... so we built a correction agent on opus 4.6 that picks up user-submitted corrections, verifies them against the original pdf, and applies fixes autonomously. and when it spots a systemic bug, it opens a github issue with a diagnosis and suggested code fix. the parser gets better on its own! entire codebase built with opus 4.6. video: live site, working MCP server, correction agent all running in production right now. open source and free forever! thank you for organizing the hackathon! cc: @cerebral_valley @iporollo @bcherny @_catwu @trq212 @lydiahallie @adocomplete

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dedy_ks retweeted

Claude

@claudeai

4 months ago

🥉 https://t.co/AlusRimhia by Michal Nedoszytko Patients leave doctor's offices every day without understanding their diagnosis. Postvisit (built by a cardiologist) turns visit transcripts and medical records into ongoing, personalized health guidance.