@NewsAlgebraIND @bchesky considers loneliness as one of the biggest human problems.
This guy is in the air mattress phase of solving this problem
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Biswaroop Palit
977 posts
Biswaroop Palit
@bpalit
Products at @box| Love traveling, hiking, squash, football and @FCBarcelona| Foodie| Views my own
Palo Alto, CA Katılım Şubat 2010
3.2K Takip Edilen516 Takipçiler
🚨 Mumbai Beach Viral : Man charges people to listen to problems.
REPORTER : Do people come? 🤯
MAN : "Yes, For small troubles, ₹250. For bigger worries, ₹500, and to cry together, ₹1,000. I am here to listen to people’s problems" 😳
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LLMs are very fluent in CLI - it's the most frequent tool-use pattern in their training data. That's why we built the @Box CLI as a first-class interface for agents. One install, and any agent gets governed access to enterprise content.
npm install --global @box/cli
Aaron Levie@levie
The official Box CLI is here. Now you can use Box via Claude Code, Codex, Perplexity Computer, OpenClaw & more as a full cloud file system for agents. Available to all users, including free users with 10GB of free storage. npm install --global @box/cli
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@nvidia just launched Agent Toolkit at GTC - a platform for autonomous enterprise agents. @Box is the governed content layer underneath: secure access, policy enforcement, full audit trails. No shadow copies, no ungoverned data. This is the agent infrastructure for the enterprise
Box@Box
Box is teaming up with @nvidia to close a critical gap in enterprise AI agent infrastructure — giving agents the access they need to be productive, with the security controls that make them safe to deploy. As part of the NVIDIA Agent Toolkit, NemoClaw and OpenShell enable a secure runtime for autonomous agents. Box plugs in as the governed file system — giving agents the content access they need while enforcing the permissions, compliance, and audit trails enterprises require. Here's what Box + Agent Toolkit unlocks for your agent strategy: →A modern integration pattern built for autonomous agents →Content security with Box governance and runtime enforcement with OpenShell Gateway and Policy Engines →Pre-built Box Skills and integration with the Box file system via the Box CLI →Auditability and security at enterprise scale Find out more → blog.box.com/connecting-ope…
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@yenkel @GeoffreyHuntley @chamath @theallinpod @levie @yenkel happy to help - let me DM you. let’s definitely catch up when you are here
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everyone started talking about the AI “software factory” in 2026
@chamath has been taking about it in @theallinpod since 2024
credit where credit is due 🔮
Chamath Palihapitiya@chamath
Our cracked team just used Software Factory to rebuild and replace Jira in a little more than a month. We first spent 3.5 weeks planning. This is Software Factory’s superpower. It allowed our lead PM, Designer and Architect to thoughtfully describe and detail exactly what they wanted. Software Factory then did the heavy lifting in filling in the blanks and allowing our senior tech folks to sharpen the direction of what they wanted. Then in 2.5 weeks 2.5 junior devs built a replacement. This will launch as an updated Planner module inside of Software Factory on Tuesday. It’s beautiful, clean and super useful. Try it here: 8090.ai
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@levie Spot on! Processes are going to change in every area - including drug discovery 💡 Individuals, teams and companies who start thinking differently will separate from the pack soon
vittorio@IterIntellectus
this is actually insane > be tech guy in australia > adopt cancer riddled rescue dog, months to live > not_going_to_give_you_up.mp4 > pay $3,000 to sequence her tumor DNA > feed it to ChatGPT and AlphaFold > zero background in biology > identify mutated proteins, match them to drug targets > design a custom mRNA cancer vaccine from scratch > genomics professor is “gobsmacked” that some puppy lover did this on his own > need ethics approval to administer it > red tape takes longer than designing the vaccine > 3 months, finally approved > drive 10 hours to get rosie her first injection > tumor halves > coat gets glossy again > dog is alive and happy > professor: “if we can do this for a dog, why aren’t we rolling this out to humans?” one man with a chatbot, and $3,000 just outperformed the entire pharmaceutical discovery pipeline. we are going to cure so many diseases. I dont think people realize how good things are going to get
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There’s a fundamental difference between taking an existing process and applying AI agents to it vs. taking a process from scratch and designing it from the ground up for AI agents. The gap we’re going to see will widen between the teams and companies that are able to do the latter instead of just the former.
In theory it would have been ideal for all the gains of AI to have come “for free”, but there are both clear constraints of AI (like getting the context right) and clear upsides (like being able to execute code and run in parallel) that the workflows themselves must be redesigned to take full advantage of this technology.
One of the biggest implications that will come into focus is that agents that can write and run code, and interact with any API, will lead to agents effectively being expert engineers applied to your business process.
So to some extent one of the biggest ways of reengineering a workflow is to ask yourself: what would you do if you had an infinite number of capable engineers write software for this process. What if those engineers wrote code to connect your disparate data sources, comb thorough any amount of unstructured data, automate your repeated tasks, connect your various systems together specific to your process, and so on.
Not every process has that upside, but there tons of tasks that we do every day across marketing, finance, operations, and even sales, where a programmer with infinite code writing and API access would be able to make something go far faster or produce way more output. The teams that start to think this way will start to operate entirely differently.
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"Make something agents want" The best framing for what's coming next in software. The entire stack has to be reimagined to be API-first with first class tooling like CLIs. Filesystems for agents is what we're building at @Box - core infra for a world with trillions of agents.
Aaron Levie@levie
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As agents evolve from Assistants to Coworkers - they need a filesystem to store, retrieve and share context. @Box works with @LangChain to provide the enterprise ready filesystem for your agents!
LangChain JS@LangChain_JS
Filesystems are proving to be an incredibly powerful layer for organizing context. One facet of deepagents is that these files can come from anywhere and from multiple places! Use the same file store you and your team already use. Here's how to do it with Box!
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Agents like @openclaw don't just chat, they work. They write code, process docs, and collaborate across tools. AI now needs what every worker needs: a filesystem. @Box gives agents a secure place to store, share, and collaborate on work with right permissions and governance.
Box@Box
Agents are moving from copilots to operators. But operational agents need something simple and powerful: a real filesystem to operate in. Not just chat. Not just APIs. A governed content environment where they can read, write, route, and collaborate. In this demo, @openclaw operates inside Box — scoped to a specific intake folder — turning contracts into structured workflow within a secure, permission-aware system. This is how agents begin to operationalize enterprise work. Dive in to get started: bit.ly/4r8Urij
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Agent identities is going to be a super fun and hard problem for software in the coming years. Most agentic systems today assume that the agent can do everything the user can do, and just operate as an extension of that user. This has worked well and is how most auth has worked for cloud software, and it has made integrations super easy over time.
But then comes along systems like Openclaw, and suddenly we get a new view into what becomes possible with agents that can operate on their own. And when you have many of them running in parallel. You start to work with them like a colleague, not just as an extension of what you do.
But of course this now introduces an all new complexity than the traditional approach. What if you want an agent to access only a small subset of your data? What if you want an agent to have its own sandbox to operate in without any risk of a blast radius if it goes off the rails? What if you want to create an agent that can work with others, without you seeing everything it’s doing?
For all of these cases, agents will start to need their own identities inside of platforms. To do this, we likely will need new mental models for how we delegate controls and access to them, how you handle authentication, who gets to manage them in an organization and so on. Lots to figure out in this space right now.
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Processing and creating unstructured data is a crucial first step for agents to automate knowledge work. Now you can easily integrate Box as a cloud filesystem into deepagents from Langchain.
Lots more coming in this space soon from @Box ...
Box@Box
AI agents need a structured place to do their work and access relevant content. A filesystem provides a clear, navigable way to manage that context. Here’s how Box can back that abstraction in @LangChain Deep Agents — preserving the simplicity of the filesystem interface while adding enterprise-grade security, permission controls, version history, and collaboration at the storage layer. Explore our implementation: blog.box.com/filesystems-co…
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@Stevenhurtador @Box @levie Bunch of other improvements coming too! Happy to work with you as you test things out
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Rally interesting move by @box & @levie.
Before starting with agents & Claude Code/Cursor, I basically had everything on the cloud and I’d lose nothing changing laptops.
Now, I’m always looking for ways to ensure my files are safe & synced. I’d been using github for it, but not always the right choice. Happy to test these out for our internal use and also for corporate customers embedding agents in their workflows more and more at Simpladocs with @thecodaguy
Box@Box
File systems are quickly becoming a core abstraction for AI agents for knowledge work. By having access to a file system, agents can effectively manage context, process any amount of information, and create new files and data. The challenge is that local file systems are inherently limited in size, lack governance capabilities, and are inherently personal -not collaborative- in nature. Now, with the Box API and @LangChain's deepagent SDK, you can bring the full power of a secure, collaborative cloud file system to your AI agents. Repo ↓ github.com/box-community/…
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@gokulr In consumer, CPO can be mostly about product & growth loops. In B2B, product leadership is inseparable from GTM: ICP selection, positioning, pricing & customer facing cycles. AI compresses how we build, but doesn’t remove the complexity of how enterprises buy, deploy & expand
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PREDICTION: THE CPO ROLE, AS WE KNOW IT, WILL VANISH IN FIVE YEARS
At young AI native companies, the traditional PM role is on the wane, replaced with a product builder archetype that’s a combination of Product, Design and Engineering.
These companies will never hire a CPO. A separate product leader leads to too much cognitive dissonance when the IC roles doing the actual work are blending, extra overhead and imposes an unnecessary coordination tax on the product development organization.
Five years from now, these companies will be the leaders and set the cultural tone for the next generation, so my prediction is that all tech companies will stop hiring for the CPO role in five years. There will be a singular product development leader at each org. Ironically, this new role might still be called the CPO, except they will run the entire product development org.
CPTO is far too unwieldy of a title and only exists today to alleviate confusion.
Career implication: early / mid career product leaders need to stop aspiring to become CPOs. instead, you need to develop a panoply of product development skills across all three disciplines (+ analytics), be able to fluidly navigate the roles, and become a product builder, period.
Farewell, CPO! It was a good 15-20 year run for this role in tech. But like everything else, it’s time to evolve.
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@Box Very useful enterprise use case, and demos the power of @cursor_ai to build such apps! cc @leerob
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Great example of agentic UI automation - removes the need for tooling / scaffolding to set up Playwright tests.
More power to PMs / Designers / Support - describe the flow and ask for proof of success
Kenn Ejima@kenn
We’ve fully automated our app’s end-to-end tests with ChatGPT Atlas. Log in as a school counselor to confirm everything works as expected. Sure, we have Playwright — but this approach enables deeper integration testing that wasn’t possible before, like opening Gmail and clicking a link or going through Stripe Checkout for a real purchase — and letting the model report any anomalies it finds. @OpenAI did a great job.
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@kevinweil Whatsapp messaging is free on United, Delta - on flight has been one of the primary situations when I used ChatGPT through Whatsapp!
Also friends and relatives in India tend to use the Whatsapp ChatGPT interface more frequently.
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Hard to believe Meta is shutting off 1-800-CHATGPT, which has many millions of happy users. If you're one of them, you can migrate to our app, website, and browser to preserve your conversations.
RT if you agree that WhatsApp is better with ChatGPT.
OpenAI@OpenAI
Meta changed its policies so 1-800-ChatGPT won't work on WhatsApp after Jan 15, 2026. Luckily we have an app, website, and browser you can use instead to access ChatGPT.
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The fundamental breakthrough: you can compress a 1,000-word document into ~100 "vision tokens" instead of 1,000 text tokens. 10× compression with 97% accuracy!
Paper: github.com/deepseek-ai/De…
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The Deepseek OCR paper has lots of implications for knowledge work agents:
- Load lots more docs in context
- Cheaper and faster processing - reminiscent of hot/warm/cold storage tiering
- Progressive detail: load full detail only when needed (e.g. contract comparisons)
Jerry Liu@jerryjliu0
What i also like about this paper is it implies new architectures for both retrieval/RAG and conversation history - by storing the data representation natively as image tiles, you can render "old" text to progressively lower-resolution images. This means you might be able to fetch a *lot* of document context into the prompt for coarse-grained tasks like document summarization by simply fetching the low-res variants. Also offers an alternative to the memory compaction mechanisms in Claude etc.
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OpenAI opening an office in Delhi suggests that it’s more about government relations than tech talent
Greg Brockman@gdb
We've just announced plans for an OpenAI office in New Delhi:
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Biswaroop Palit retweetledi
Transform your enterprise documents into intelligent, context-aware AI applications with advanced agentic processing techniques.
Join us September 30th at 9 AM PST as our VP of Product @bpalit shares a year's worth of enterprise learnings about parsing, extracting, and indexing complex documents with LlamaCloud:
🔄 Converting unstructured data into reusable, governed data products that go beyond basic OCR
📊 Layout-, table-, and chart-aware processing techniques for higher accuracy enterprise document handling
👥 Embedding human-in-the-loop review processes with citations, explanations, and confidence scores
💰 Balancing cost and accuracy strategies for scaling large document volumes effectively
This free virtual webinar covers real enterprise best practices we've built into our platform for intelligent AI agents.
Register for the webinar: landing.llamaindex.ai/agentic_docume…
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