Jacob Weaver retweeted
10 grok bots you need to make internet money
if you've got 30 minutes this weekend, steal this list and start building:
1. Outbound Prospecting by @kristaletz
finds people who match your ideal customer, researches each one on the public web, and drafts a first message. nothing sends without your yes.
a prospect list and a first draft without living in a spreadsheet all week
x.ai/bot/marketplace/bots/pg
2. Cold Outreach by @notswizz
give it your company url. it researches the business, finds and scores prospects, and writes short personalized cold emails.
outreach drafts lined up so you can actually send something today
x.ai/bot/Xfb__DmiJ_s-FAZKMA6…
3. Haggle Bot by Daniel Gartshein
inventories your saas spend from ramp and bills, finds unused seats, duplicates, and cheaper alternatives, then drafts vendor counters. never spends, signs, or sends without you.
money you stop leaking is money you get to keep
x.ai/bot/marketplace/bots/ha…
4. SEO & AEO Desk by @adamta
turns your keywords or search console data into content ideas and writer-ready briefs for google and ai answers.
write toward what people are already looking for
x.ai/bot/marketplace/bots/se…
5. Pitch Board by @teeRex247
paste a messy client brief and get a flowchart, funnel, or mood board, with every assumption flagged so nothing sneaks in.
sell the plan visually before the scope goes sideways
x.ai/bot/s32IvITvpDM9UE2lAL_…
6. Any CRM by @CorbenH414
works inside whatever crm you already run (salesforce, hubspot, gohighlevel, zoho, pipedrive, dynamics, and more). updates records, follow-ups, and reports.
pipeline hygiene without another hour of data entry
x.ai/bot/16XzSxYwdnnRYlAx6DF…
7. Freelance Invoice Chaser by @crisships
tracks who owes you, watches gmail for payments and replies, and drafts each reminder on a set schedule. you approve every send.
work done should turn into money in the account
x.ai/bot/6XWo6nhodL0bZnP1MnR…
8. Account Research by @weaverwork
research desk for one named enterprise account. maps the buying committee, finds why-now triggers, and drafts outreach for you to review. never invents names and never sends on its own.
walk into the next account call with a real map
x.ai/bot/0CX2DyEQoP7Y88nT7XB…
9. X Growth Manager by @mozamm_el
drafts daily replies, text posts, lead research, and casual dms with follow-ups. nothing goes out without your ok.
growth work and client-finding drafts in one queue
x.ai/bot/xitvwtu2RlmS_HAkYDg…
10. Afterglow by @thecsguy
daily digest of how your posts actually did. what moved, verified vs unverified, what got replies, what died. no drafting, just the data.
stop guessing which posts deserve a follow-up offer
x.ai/bot/0pfVoOQLOV4O8Ujlk27…
follow me for more content systems and internet money
Jacob Weaver retweeted
Here’s why agent swarms are going to be a very big deal. We can finally make compute a critical variable in a large number of important tasks in the economy which wasn’t possible before.
There’s a large amount of work in the world that is essentially only constrained by the amount of time that we put into research, data processing, discovery work, running tests, and more. All of this work is bottlenecked by our ability to plan, execute, review, and coordinate everything happening in these workflows. Which means we basically do very little of them today relative to their economic value.
Agent swarms are the first real ability to parallelize this work in a way where - in theory - the only parameter that matters is how much compute you throw at the problem. Cyber security, life sciences or material science research, trading, QA testing, data processing, and many other fields are essentially compute constrained problems in the limit once models are good enough at these tasks.
The breakthrough is that in a world where agents can use tools, write code, process data, have strong domain depth, and can coordinate with each other, you can begin to solve arbitrarily complex problems by setting the right goals and applying enough tokens to the problem. This changes a lot of fields as well as even the competitive dynamics in these fields.
Jacob Weaver retweeted
Box Mount lets developers mount Box as a filesystem directly in any agent sandbox, so agents can work with files and data just like a person would.
In this article, we show how it works with @DigitalOcean, @E2B, @OpenAI, and @vercel.
Jacob Weaver retweeted
Loved stopping by SF @Techweek_'s Zero Human Startup Hackathon today!
Spoke about giving agents a company brain with @Box. Somewhere to find the docs, decisions, and context behind the work you’re asking them to do 🤠
Jacob Weaver retweeted
Most agent demos end when the chat does. @OpenClaw 2.0's /loop changes that. One prompt, and the agent keeps checking your Box deal room, updating the risk register as new documents arrive.
Check out our full tutorial.
Jacob Weaver retweeted
Reliable extraction requires more than returning the right fields. Teams need a way to evaluate and verify the results.
Box Extract provides field-level confidence scores and source bounding boxes, making it easier to identify uncertain values and trace extracted data back to its source.
See it in action.👇
Jacob Weaver retweeted
Your contract is in Box, and your deal is in @HubSpot. Now they're connected.
Box is now a supported integration in HubSpot's Breeze Assistant. In our demo, a newly signed MSA lands in Box. Ask Breeze to find the renewal deadline and key terms, and it creates a follow-up task in HubSpot automatically, all without switching tabs or lifting a finger.
Your content and your CRM, finally working together.
Jacob Weaver retweeted
Box is now available in @Muse, from Meta! Your personal AI agent can now access governed enterprise content from Box, with permissions intact.
One secure place where everything works together. Connect it in Muse today.
Jacob Weaver retweeted
Come meet the Box devrel team at @WeAreDevs in San Jose today!
Stop by our booth for live demos, conversations with the team, and learn more about how Box is the file system for AI.
See you there!
Box devrel team is at @WeAreDevs!
Come learn how to give your @ChatGPT @bot @Muse @claudeai @NousResearch Hermes company knowledge with @Box as the file system!
We got live demos for ya 😎
Jacob Weaver retweeted
BoxWorks 2026 is where you get the inside track on where Box is headed next.
→ Keynotes from Box Co-founder and CEO Aaron Levie, @nvidia Founder and CEO Jensen Huang, and @intel CEO Lip-Bu Tan
→ A live walkthrough of Box's latest innovations
→ First look at the product roadmap from Box leadership
What does your team need most from enterprise AI right now?
Save your spot: boxworks.box.com/series/boxw…
Jacob Weaver retweeted
Arguably, the most important file in this demo isn’t even in the repo. @vercel's fx pulls the security policy from Box, uses it to fix and test the local app, then saves the proof back alongside the source document
It just works 🤙
🚀@vercel's’ fx is a tiny open-source coding agent built to take action directly in a developer’s workspace. This demo extends that idea by giving fx access to the security policies, requirements, and release docs stored in Box.
Using the Box CLI, fx retrieves an approved policy, compares it with local code, edits the files, adds missing test coverage, and prepares release evidence without being told which lines to change. It asks for human approval before uploading anything, then verifies every file after it lands in Box.
Git stays where the code lives. Box stays where the approved docs and release proof live. fx connects the work across both.
Demo below ↓
Jacob Weaver retweeted
Jev is one of the coolest things I've seen in a while!
It feels like AI is about to have it's regex or jQuery moment, where it gets embedded in the most basic primitives we use to build software.
🆕@typesafeai dropped Jev this week, a new frontier model optimized for decisions. We put it to work on an incident triage workflow in Box.
Jev doesn't generate text. You send it state plus typed questions and it returns booleans with probabilities, enums, and scores in a single pass, so there's no output to parse and no schema to keep in line.
The demo uses Jev to classify and route incidents. It pulls the incident report from Box, builds the state, asks whether it's customer-facing and how severe it is, moves the file into Escalate, Monitor, or Review folders, and sets a metadata template instance with the result.
The answers comes back with a confidence estimate, so anything below threshold goes to Review for a human instead of routing itself.
Check it out.👇
Jacob Weaver retweeted
Pretty sweet. Legal AI needs more than the law everyone can look up. You also need the context buried in years of contracts, playbooks, precedents, matter files, etc.
@OpenAI Astra for Law's got the first covered. @Box helps it work with the second without losing track of who can see what
Box and @OpenAI are partnering to bring governed enterprise content to AI-powered legal work with Astra for Law and @ChatGPT. Legal skills built on Box and ChatGPT help law firms turn their content into practical, secure workflows without weakening the controls around it.
In this demo, a legal professional uses the new Outside Counsel Guidelines skill to review an incoming set of OCGs directly from Box. ChatGPT flags associated risks and leaves comments for human review, all without the content leaving Box.
Jacob Weaver retweeted
Testing Jev since yesterday. Love seeing Khaneman's system 1 in practice. Such a great developer experience, elegant solution, and amazing launch. Well done @typesafeai! ✨ Stay tuned for a full article
🆕@typesafeai dropped Jev this week, a new frontier model optimized for decisions. We put it to work on an incident triage workflow in Box.
Jev doesn't generate text. You send it state plus typed questions and it returns booleans with probabilities, enums, and scores in a single pass, so there's no output to parse and no schema to keep in line.
The demo uses Jev to classify and route incidents. It pulls the incident report from Box, builds the state, asks whether it's customer-facing and how severe it is, moves the file into Escalate, Monitor, or Review folders, and sets a metadata template instance with the result.
The answers comes back with a confidence estimate, so anything below threshold goes to Review for a human instead of routing itself.
Check it out.👇
Jacob Weaver retweeted
We built an incident triage workflow using Box and Jev, a new frontier model by @CompleteSkeptic optimized for decisions rather than text generation. Unstructured content in, typed decisions out.
Jacob Weaver retweeted
🆕@typesafeai dropped Jev this week, a new frontier model optimized for decisions. We put it to work on an incident triage workflow in Box.
Jev doesn't generate text. You send it state plus typed questions and it returns booleans with probabilities, enums, and scores in a single pass, so there's no output to parse and no schema to keep in line.
The demo uses Jev to classify and route incidents. It pulls the incident report from Box, builds the state, asks whether it's customer-facing and how severe it is, moves the file into Escalate, Monitor, or Review folders, and sets a metadata template instance with the result.
The answers comes back with a confidence estimate, so anything below threshold goes to Review for a human instead of routing itself.
Check it out.👇
Jacob Weaver retweeted
The applied layer is where AI creates enterprise value.
@levie joined @sonyatweetybird to discuss why the most intelligent model in the world still has to connect to legacy systems, wait on humans in the loop, and work within workflows that were never designed for AI.
Jacob Weaver retweeted
Box + @Snowflake turn financial documents into queryable history, without losing the path back to the source.
Most financial research workflows follow the same pattern: extract details from documents, write a summary, copy numbers into another system, and hope everything can be retraced when someone asks where a figure came from.
This Python demo closes that loop. Box Extract transforms PDFs into structured financial data while preserving confidence scores and page references. Box Doc Gen produces a readable, sourced memo. Snowflake stores common fields alongside the complete JSON payload, creating queryable records that can be compared across quarters or companies.
The result is unstructured documents become useful data while every number remains connected to its source.