~~

@thoughtsonxpost

📝Opinions are my own

Joined February 2016

4K Following

305 Followers

3K Posts

~~ @thoughtsonxpost

about 2 months ago

@elonmusk I wish you will always allow people to speak. Indian #Students speaking up against #corruption in examination system and overall situation in the country. No #pressfreedom and this is high time #India need #x support to make sure voices are not suppressed !! #CJP

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~~ @thoughtsonxpost

about 2 months ago

@BanterBallHQ @elonmusk I wish you will always allow people to speak. Indian #Students speaking up against corruption in examination system and overall situation in the country. No press freedom and this is high time country need #x support to make sure voices are not suppressed !!

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thoughtsonxpost retweeted

3 months ago

https://t.co/TIlBSKlpjN

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thoughtsonxpost retweeted

4 months ago

🚨 The "𝙼𝚎𝚐𝚊𝚕𝚘𝚍𝚘𝚗" Campaign is live... 𝟻,𝟽𝟷𝟾 malicious commits to 𝟻,𝟻𝟼𝟷 GitHub repositories in a six-hour window. Using throwaway accounts and forged author identities (build-bot, auto-ci, ci-bot, pipeline-bot), the attacker injected 𝙶𝚒𝚝𝙷𝚞𝚋 𝙰𝚌𝚝𝚒𝚘𝚗𝚜 workflows containing 𝚋𝚊𝚜𝚎𝟼𝟺-𝚎𝚗𝚌𝚘𝚍𝚎𝚍 bash payloads that exfiltrate: - CI secrets, - cloud credentials - SSH keys - OIDC tokens - source code secrets Check your repo / Technical details: https://t.co/tua3jYU1wa

safedepio's tweet photo. 🚨 The "𝙼𝚎𝚐𝚊𝚕𝚘𝚍𝚘𝚗" Campaign is live...

𝟻,𝟽𝟷𝟾 malicious commits to 𝟻,𝟻𝟼𝟷 GitHub repositories in a six-hour window.

Using throwaway accounts and forged author identities (build-bot, auto-ci, ci-bot, pipeline-bot), the attacker injected 𝙶𝚒𝚝𝙷𝚞𝚋 𝙰𝚌𝚝𝚒𝚘𝚗𝚜 workflows containing 𝚋𝚊𝚜𝚎𝟼𝟺-𝚎𝚗𝚌𝚘𝚍𝚎𝚍 bash payloads that exfiltrate:

- CI secrets,
- cloud credentials
- SSH keys
- OIDC tokens
- source code secrets

Check your repo / Technical details: https://t.co/tua3jYU1wa

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Who to follow

Data Professional | Animal advocate & rescue volunteer | Dementia caregiver | Asian art addict | California dreamin'

RT & Like are not endorsements

thoughtsonxpost retweeted

4 months ago

Spotify's Chief Architect just showed how they ship 4,5K deployments /day with Claude at Anthropic stage 27-minutes. free. By #1 music app dev "More than 99% of our engineers use AI coding tools. Adoption took off after Opus 4.5" Worth more than any $500 vibe-coding course.

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thoughtsonxpost retweeted

4 months ago

Andrej Karpathy spent 4 minutes in an interview explaining a single idea about how most people haven’t even started learning how to use AI and everyone paying $20/month for a subscription.. that's not really using Claude at all his point is that the real skill gap is the ability to build with AI he identified 4 behaviors that break Claude Code and put them all into one file a developer expanded it into 21 rules and published it - 82,000 stars and #1 on GitHub Trending coding accuracy jumped from 65% to 94% here's what these 21 rules actually are and why most developers using Claude every day have never configured them the full breakdown is covered in the article below 👇

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~~ @thoughtsonxpost

4 months ago

@HelleLyngSvends @Joellaain @RahulGandhi @HelleLyngSvends You should definitely connect with @dhruv_rathee & @TheDeshBhakt Also this gets interesting, I think @RahulGandhi should go to #Norway to expose the real situation and I’m sure it will definitely uplift the moral of activists in the country to save the nation.

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thoughtsonxpost retweeted

Andrej Karpathy

4 months ago

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

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thoughtsonxpost retweeted

4 months ago

We recently built an AI assistant inside @Razorpay called Slash. It reads our entire codebase, debugs production incidents, reviews specs, writes code, reviews every single PR, answer tech queries and also raises PRs for small features. It's easily accessible through Slack. We can tag it in any Slack thread, describe the problem in English, and it gets to work. Six weeks ago, Slash handled 122 tasks in its first week. Last week it handled 14000+. Queries, analysis, bug fixes, PR reviews, test runs and work that earlier lived across scattered tools and teams can now be done with Slash right within Slack. 1000+ people used it in a single week because it got their work done faster. The whole adoption has been completely organic. The numbers from last week have been very encouraging - 14,854 tasks completed. 2,150 PRs raised, 1,152 merged, 45% of those PRs shipped with zero human rework. A payout gets stuck mid-retry during a live incident, an engineer tags Slash and within seconds, it cross-references logs with code and pinpoints a state machine bug blocking the retry-to-failed state transition. Tells the team exactly which logs to check and how to resolve the incident. With its K8s analyzer skill, Slash scanned a single namespace, right-sized all 11 workers using 48-hour P95 pod metrics, and raised the PR. One run saved $560/month. A marketing banner bug was fixed with few prompt iterations with a PR raised, merged to prod and deployed in minutes. No front-end developer touched the code. Security teams ran static security testing and remediation through Slash at org scale. Thousands of findings were purged and many more got validated autonomously. But Slash isn't just an engineering tool. Account managers now trace stuck customer payments and integration failures through Slash instead of pinging engineers on Slack. L2 product support tickets get triaged by Slash before they reach engineering. 250+ non-engineers ran thousands of sessions last week. PMs used it for research on our payments infra, customer interviews and product features sometimes raising PRs of their own. Analytics teams built SQL pipelines. 11% of all sessions came from people outside tech and product. On our company bakkar (watercooler) Slack thread, someone asked Slash jokingly to assign tasks to everyone and it responded in the same tone. It seamlessly started participating in inside jokes and conversations. The quality compounds with use. Engineers who shipped 11+ Slash PRs averaged a 63% merge rate without rework. First-timers averaged 37%. Across the org, human review comments per PR have dropped more than 40% with Slash starting to do in-depth review of every single change. We're still early. Large cross-repo refactors, fully agentic sdlc and plan mode are next. But Slash has already changed how people at Razorpay build, debug, and ship every day.

shashank_kr's tweet photo. We recently built an AI assistant inside @Razorpay called Slash.
It reads our entire codebase, debugs production incidents, reviews specs, writes code, reviews every single PR, answer tech queries and also raises PRs for small features.

It's easily accessible through Slack. We can tag it in any Slack thread, describe the problem in English, and it gets to work.

Six weeks ago, Slash handled 122 tasks in its first week. Last week it handled 14000+. Queries, analysis, bug fixes, PR reviews, test runs and work that earlier lived across scattered tools and teams can now be done with Slash right within Slack. 1000+ people used it in a single week because it got their work done faster. The whole adoption has been completely organic.

The numbers from last week have been very encouraging - 14,854 tasks completed. 2,150 PRs raised, 1,152 merged, 45% of those PRs shipped with zero human rework.

A payout gets stuck mid-retry during a live incident, an engineer tags Slash and within seconds, it cross-references logs with code and pinpoints a state machine bug blocking the retry-to-failed state transition. Tells the team exactly which logs to check and how to resolve the incident.

With its K8s analyzer skill, Slash scanned a single namespace, right-sized all 11 workers using 48-hour P95 pod metrics, and raised the PR. One run saved $560/month.

A marketing banner bug was fixed with few prompt iterations with a PR raised, merged to prod and deployed in minutes. No front-end developer touched the code.

Security teams ran static security testing and remediation through Slash at org scale. Thousands of findings were purged and many more got validated autonomously.

But Slash isn't just an engineering tool.

Account managers now trace stuck customer payments and integration failures through Slash instead of pinging engineers on Slack. L2 product support tickets get triaged by Slash before they reach engineering.

250+ non-engineers ran thousands of sessions last week. PMs used it for research on our payments infra, customer interviews and product features sometimes raising PRs of their own. Analytics teams built SQL pipelines. 11% of all sessions came from people outside tech and product.

On our company bakkar (watercooler) Slack thread, someone asked Slash jokingly to assign tasks to everyone and it responded in the same tone. It seamlessly started participating in inside jokes and conversations.

The quality compounds with use. Engineers who shipped 11+ Slash PRs averaged a 63% merge rate without rework. First-timers averaged 37%. Across the org, human review comments per PR have dropped more than 40% with Slash starting to do in-depth review of every single change.

We're still early. Large cross-repo refactors, fully agentic sdlc and plan mode are next. But Slash has already changed how people at Razorpay build, debug, and ship every day.

shashank_kr's tweet photo. We recently built an AI assistant inside @Razorpay called Slash.
It reads our entire codebase, debugs production incidents, reviews specs, writes code, reviews every single PR, answer tech queries and also raises PRs for small features.

It's easily accessible through Slack. We can tag it in any Slack thread, describe the problem in English, and it gets to work.

Six weeks ago, Slash handled 122 tasks in its first week. Last week it handled 14000+. Queries, analysis, bug fixes, PR reviews, test runs and work that earlier lived across scattered tools and teams can now be done with Slash right within Slack. 1000+ people used it in a single week because it got their work done faster. The whole adoption has been completely organic.

The numbers from last week have been very encouraging - 14,854 tasks completed. 2,150 PRs raised, 1,152 merged, 45% of those PRs shipped with zero human rework.

A payout gets stuck mid-retry during a live incident, an engineer tags Slash and within seconds, it cross-references logs with code and pinpoints a state machine bug blocking the retry-to-failed state transition. Tells the team exactly which logs to check and how to resolve the incident.

With its K8s analyzer skill, Slash scanned a single namespace, right-sized all 11 workers using 48-hour P95 pod metrics, and raised the PR. One run saved $560/month.

A marketing banner bug was fixed with few prompt iterations with a PR raised, merged to prod and deployed in minutes. No front-end developer touched the code.

Security teams ran static security testing and remediation through Slash at org scale. Thousands of findings were purged and many more got validated autonomously.

But Slash isn't just an engineering tool.

Account managers now trace stuck customer payments and integration failures through Slash instead of pinging engineers on Slack. L2 product support tickets get triaged by Slash before they reach engineering.

250+ non-engineers ran thousands of sessions last week. PMs used it for research on our payments infra, customer interviews and product features sometimes raising PRs of their own. Analytics teams built SQL pipelines. 11% of all sessions came from people outside tech and product.

On our company bakkar (watercooler) Slack thread, someone asked Slash jokingly to assign tasks to everyone and it responded in the same tone. It seamlessly started participating in inside jokes and conversations.

The quality compounds with use. Engineers who shipped 11+ Slash PRs averaged a 63% merge rate without rework. First-timers averaged 37%. Across the org, human review comments per PR have dropped more than 40% with Slash starting to do in-depth review of every single change.

We're still early. Large cross-repo refactors, fully agentic sdlc and plan mode are next. But Slash has already changed how people at Razorpay build, debug, and ship every day.

shashank_kr's tweet photo. We recently built an AI assistant inside @Razorpay called Slash.
It reads our entire codebase, debugs production incidents, reviews specs, writes code, reviews every single PR, answer tech queries and also raises PRs for small features.

It's easily accessible through Slack. We can tag it in any Slack thread, describe the problem in English, and it gets to work.

Six weeks ago, Slash handled 122 tasks in its first week. Last week it handled 14000+. Queries, analysis, bug fixes, PR reviews, test runs and work that earlier lived across scattered tools and teams can now be done with Slash right within Slack. 1000+ people used it in a single week because it got their work done faster. The whole adoption has been completely organic.

The numbers from last week have been very encouraging - 14,854 tasks completed. 2,150 PRs raised, 1,152 merged, 45% of those PRs shipped with zero human rework.

A payout gets stuck mid-retry during a live incident, an engineer tags Slash and within seconds, it cross-references logs with code and pinpoints a state machine bug blocking the retry-to-failed state transition. Tells the team exactly which logs to check and how to resolve the incident.

With its K8s analyzer skill, Slash scanned a single namespace, right-sized all 11 workers using 48-hour P95 pod metrics, and raised the PR. One run saved $560/month.

A marketing banner bug was fixed with few prompt iterations with a PR raised, merged to prod and deployed in minutes. No front-end developer touched the code.

Security teams ran static security testing and remediation through Slash at org scale. Thousands of findings were purged and many more got validated autonomously.

But Slash isn't just an engineering tool.

Account managers now trace stuck customer payments and integration failures through Slash instead of pinging engineers on Slack. L2 product support tickets get triaged by Slash before they reach engineering.

250+ non-engineers ran thousands of sessions last week. PMs used it for research on our payments infra, customer interviews and product features sometimes raising PRs of their own. Analytics teams built SQL pipelines. 11% of all sessions came from people outside tech and product.

On our company bakkar (watercooler) Slack thread, someone asked Slash jokingly to assign tasks to everyone and it responded in the same tone. It seamlessly started participating in inside jokes and conversations.

The quality compounds with use. Engineers who shipped 11+ Slash PRs averaged a 63% merge rate without rework. First-timers averaged 37%. Across the org, human review comments per PR have dropped more than 40% with Slash starting to do in-depth review of every single change.

We're still early. Large cross-repo refactors, fully agentic sdlc and plan mode are next. But Slash has already changed how people at Razorpay build, debug, and ship every day.

shashank_kr's tweet photo. We recently built an AI assistant inside @Razorpay called Slash.
It reads our entire codebase, debugs production incidents, reviews specs, writes code, reviews every single PR, answer tech queries and also raises PRs for small features.

It's easily accessible through Slack. We can tag it in any Slack thread, describe the problem in English, and it gets to work.

Six weeks ago, Slash handled 122 tasks in its first week. Last week it handled 14000+. Queries, analysis, bug fixes, PR reviews, test runs and work that earlier lived across scattered tools and teams can now be done with Slash right within Slack. 1000+ people used it in a single week because it got their work done faster. The whole adoption has been completely organic.

The numbers from last week have been very encouraging - 14,854 tasks completed. 2,150 PRs raised, 1,152 merged, 45% of those PRs shipped with zero human rework.

A payout gets stuck mid-retry during a live incident, an engineer tags Slash and within seconds, it cross-references logs with code and pinpoints a state machine bug blocking the retry-to-failed state transition. Tells the team exactly which logs to check and how to resolve the incident.

With its K8s analyzer skill, Slash scanned a single namespace, right-sized all 11 workers using 48-hour P95 pod metrics, and raised the PR. One run saved $560/month.

A marketing banner bug was fixed with few prompt iterations with a PR raised, merged to prod and deployed in minutes. No front-end developer touched the code.

Security teams ran static security testing and remediation through Slash at org scale. Thousands of findings were purged and many more got validated autonomously.

But Slash isn't just an engineering tool.

Account managers now trace stuck customer payments and integration failures through Slash instead of pinging engineers on Slack. L2 product support tickets get triaged by Slash before they reach engineering.

250+ non-engineers ran thousands of sessions last week. PMs used it for research on our payments infra, customer interviews and product features sometimes raising PRs of their own. Analytics teams built SQL pipelines. 11% of all sessions came from people outside tech and product.

On our company bakkar (watercooler) Slack thread, someone asked Slash jokingly to assign tasks to everyone and it responded in the same tone. It seamlessly started participating in inside jokes and conversations.

The quality compounds with use. Engineers who shipped 11+ Slash PRs averaged a 63% merge rate without rework. First-timers averaged 37%. Across the org, human review comments per PR have dropped more than 40% with Slash starting to do in-depth review of every single change.

We're still early. Large cross-repo refactors, fully agentic sdlc and plan mode are next. But Slash has already changed how people at Razorpay build, debug, and ship every day.

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thoughtsonxpost retweeted

4 months ago

No company is as bhikari as @VFSGlobal They are legalised extortion supported by entire @EU_Commission

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thoughtsonxpost retweeted

4 months ago

The latest 𝕏 algorithm has been published to GitHub https://t.co/ZCOm51uxmh

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thoughtsonxpost retweeted

4 months ago

A preview for Pro users: a new personal finance experience in ChatGPT. Pro users in the U.S. can securely connect financial accounts, see where their money is going, and ask questions based on the information they choose to connect. Your full financial picture, now in ChatGPT.

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thoughtsonxpost retweeted

4 months ago

Today we're launching Jacq. A coding agent built together with the small models we've been training at @relace_ai for the past 1.5 years. It runs entirely in the cloud, and decides when to pull context from any of your connected devices. It uses all the software you already live in: Slack, Linear, GitHub, email, etc. Plus, threads are now durable — a real record of how work happened. Just drag them into a new chat to get context for your next task.

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thoughtsonxpost retweeted

4 months ago

Introducing the OpenAI Deployment Company, which will help businesses maximally succeed with their deployments of AI. Starting with 150 Forward Deployed Engineers and Deployment Specialists, and $4 billion of initial investment from 19 partners.

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thoughtsonxpost retweeted

4 months ago

The Claude Platform on AWS is now generally available. AWS customers get the full set of Claude API features, with AWS authentication, billing, and commitment retirement.

claudeai's tweet photo. The Claude Platform on AWS is now generally available.

AWS customers get the full set of Claude API features, with AWS authentication, billing, and commitment retirement. https://t.co/9WPrEgCpkg

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thoughtsonxpost retweeted

4 months ago

Anthropic is about to announce a $1.5 billion joint venture with multiple wall street firms to sell AI tools to private-equity backed companies. Anthropic, Blackstone, Hellman & Friedman and Goldman Sachs are all major investors. The announcement is expected tomorrow morning.

AndrewCurran_'s tweet photo. Anthropic is about to announce a $1.5 billion joint venture with multiple wall street firms to sell AI tools to private-equity backed companies. Anthropic, Blackstone, Hellman & Friedman and Goldman Sachs are all major investors. The announcement is expected tomorrow morning. https://t.co/DYMEaZLqP0

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~~ @thoughtsonxpost

4 months ago

@BradSmi @Microsoft Similar to what @evisort #Evisort already provide , a CLM ( Contract Lifecycle Management )

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thoughtsonxpost retweeted

Tips Excel | AI Productivity

@gudanglifehack

6 months ago

Claude Cowork can apply to 50 jobs in under 30 minutes. Here's how to set it up.

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thoughtsonxpost retweeted

Felix Rieseberg

@felixrieseberg

6 months ago

Today, we’re releasing a feature that allows Claude to control your computer: Mouse, keyboard, and screen, giving it the ability to use any app. I believe this is especially useful if used with Dispatch, which allows you to remotely control Claude on your computer while you’re away.

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thoughtsonxpost retweeted

6 months ago

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.

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