by admin | Oct 30, 2026 | AI Tools
Your AI assistant can now text you first. OpenAI just started letting a small group of ChatGPT Pro users talk to their “Dot,” the company’s always-on personal agent, through ordinary text messages. No app, no browser tab, just a conversation in your regular messaging app. It sounds small, but it is a genuine shift in how these agents fit into daily life, and it is worth understanding before it reaches more people.
What a “Dot” actually is
OpenAI launched dots at its DevDay event in late September 2026, describing them as always-on agents built on its GPT-6 Astra model. Unlike a regular ChatGPT conversation that ends when you close the tab, a dot keeps working in the background on goals you give it: watching for new information, drafting updates, or handling small recurring tasks, then checking in with you before anything important happens.
Each user gets a “primary dot” they can name, and it runs in its own isolated cloud environment rather than on your actual laptop or phone. If you want it to use apps or pull in information, you connect those permissions yourself, and OpenAI says the agent cannot send messages or change files on its own without a check against your instructions first.
What is new: texting your Dot directly
At launch, dots could only be reached through ChatGPT and workplace tools like Slack or Teams. The feature rolling out now adds real text messaging over iMessage and RCS, handled through a third-party messaging partner. You can send your Dot a task by text, photo, or voice note, and it can text you back proactively when it has something worth telling you.
Tip: this is currently a limited beta for select U.S. ChatGPT Pro subscribers only. If you are on Plus, Business, or Enterprise, you will not see the option yet, so do not worry if “Texting” does not appear in your Dot’s settings.
For the people who do have access, setup is simple: open your Dot’s profile in the ChatGPT app, toggle on “Texting,” and verify a domestic phone number. Texting “STOP” at any time turns it off again, though it does not erase whatever your Dot has already learned or remembered.
- Available to: select U.S. ChatGPT Pro subscribers (beta)
- Channels: iMessage and RCS, via a third-party relay
- Not available to: Plus, Business, or Enterprise accounts yet
One thing worth knowing before you opt in
Because the messages pass through a third-party relay to work over iMessage and RCS, the conversations are not end-to-end encrypted the way a normal iMessage chat between two people is. That does not mean your messages are public, but it is a meaningfully different privacy setup than texting a friend, and it is worth knowing before you send anything sensitive to your Dot.
From my own experience testing early access features on new AI tools, this kind of detail is exactly where people get caught out. New capabilities roll out fast and feel exciting, and the fine print about how your data actually moves gets skipped. Worth a minute of reading before you connect anything you would not want relayed through a third party.
Is this actually useful, or just a gimmick?
That depends on what you would actually use it for. Reporters covering the launch have pointed out that most of what a dot can do was already possible through OpenAI’s existing agent tools; what is new here is packaging it into something as low-friction as a text message. If you already rely on an agent to track something ongoing, like monitoring feedback or watching for a change in data, getting a text instead of having to check an app is a real convenience. If you do not have an ongoing task like that, it is not something you need to chase down.
If you are still getting your head around what an “AI agent” even means, our beginner-friendly explainer on AI agents is a good place to start, and if you want to try building a simple one yourself, we walked through it in how to make your own AI assistant. We have also covered what it is actually like working with AI agents day to day, which is a useful read before you hand one anything important.
Common questions
Do I need a special app to text my Dot?
No. If you have access to the beta, you text it like you would text any contact, using iMessage or RCS on your phone, once you have verified your number in the Dot settings.
Can other people text my Dot?
No. Access is tied to your own verified phone number, and your Dot cannot message other people or join group chats on its own.
Is this free?
No. Dots are included with ChatGPT Pro, and the texting beta is currently limited to select U.S. Pro subscribers, not available on cheaper plans.
What if I do not want it texting me?
Texting is opt-in. You can turn it off in your Dot’s settings at any time, or simply reply “STOP” to the number.
Final takeaway
Texting your AI agent instead of opening an app sounds like a small change, but it is a sign of where these tools are heading: less like software you visit, more like a contact in your phone that happens to be an AI. If you are not in the beta yet, nothing to do but wait, but it is worth understanding how it works now so you can make an informed choice about opting in once it reaches you.
by admin | Oct 29, 2026 | Research & Productivity
Ask most people how long it takes to turn a promising lab discovery into an actual medicine, and they usually guess a year or two. The real answer is closer to ten or twelve years, and most of that time isn’t spent on dramatic breakthroughs. It’s spent on paperwork, repeated lab tests, and narrowing down thousands of possible molecules to the handful worth pursuing.
That’s exactly the part of the process Anthropic just showed its Claude models chipping away at. On October 27, 2026, the company published detailed results from deep research partnerships with six drug developers, plus an early look at a drug program it’s running itself. It’s one of the clearest real-world looks yet at what “AI for science” actually means once you get past the slogan.
What Anthropic Actually Announced
The partnerships involve BigHat Biosciences, Bristol Myers Squibb, Divergence Labs, Enveda, Generate Biomedicines, and The Column Group. Anthropic is careful to frame all of this as early and mostly preclinical work, not finished cures. But the specific numbers in each case study are worth slowing down for, because they show AI being used for genuinely technical science work, not just summarizing PDFs.
Designing a Smaller, Stronger Cancer Therapy
Generate Biomedicines is trying to make CAR T-cell therapy, which has mostly worked against blood cancers, effective against solid tumors too. Six of its scientists used Claude Code to redesign a key genetic component of the therapy. One of the resulting designs was about 70% shorter than the standard version. When tested in the lab, it let immune cells produce roughly ten times as many receptors, killed tumor cells more efficiently, and stayed active in the body longer. (You can read more about how researchers are approaching solid-tumor CAR T-cell therapy at the National Institutes of Health.)
Thousands of Antibody Designs in About a Month
Divergence Labs is working on food allergy treatments that physically detach the IgE antibody from immune cells, rather than just neutralizing it in the bloodstream. Claude turned the team’s scientific goals into a design plan, then largely on its own generated roughly 35,000 antibody designs over about a month. Out of those, researchers found three strong binders and twenty designs that could successfully dislodge IgE, with three of those twenty outperforming the standard allergy medication in early tests.
Catching What Human Reviewers Missed
Not every case study is about inventing new molecules. Enveda’s manufacturing chemists were spending up to 75% of their time on compliance paperwork instead of chemistry. After connecting their documents to Claude, it reviewed 1,061 pages, caught all eleven issues human reviewers had already found, and flagged seven more that had been missed. Review time dropped from over 25 hours to under three. Claude also drafted a regulatory document in four hours that would normally take about three months by hand.
Important tip: if you work in a field with heavy documentation (regulatory filings, compliance reports, research write-ups), this Enveda example is the more realistic near-term use of AI than “AI invents a cure.” Document review and drafting is where the time savings show up first, for almost any industry.
Anthropic Is Also Building Its Own Medicine
Maybe the most human part of the announcement is Mithril Medicine, a company Anthropic acquired that started as a one-person operation. Its founder, Cody Tranbarger, was working on treatments for two rare forms of muscular dystrophy and used Claude to organize contracts, logistics, and experiments across eleven external labs. A possible treatment for one form went from an idea to promising results in mice in under eighteen months. He’s now joined Anthropic, and if the early results hold up, a drug could be ready for human trials as soon as late 2028.
From my own experience working with websites, online tools, and automation projects, this pattern feels familiar even outside medicine: the AI isn’t doing the creative or judgment-heavy part by itself. It’s clearing out the slow, repetitive overhead (the paperwork, the first-pass analysis, the thousands of variations nobody has time to check by hand) so the human expert can spend their attention where it actually matters. I’ve also seen, through research into medical imaging and AI that explains its own reasoning to doctors, how much unglamorous groundwork has to happen before a model can be trusted with something this serious. These case studies read the same way: a lot of verification sitting underneath each headline number. If you want the background on how that kind of AI reasoning gets checked, our guide on explainable AI and how AI reads medical scans cover the fundamentals.
What This Means for You
You don’t need to work in a lab for this to matter. It’s a preview of how AI is likely to show up in most serious technical fields over the next few years: not as a replacement for experts, but as a tool that handles scale (thousands of designs, thousands of pages) while people make the final calls. If you’re a student in biology, chemistry, or data science, these partnerships are a real signal of where hands-on AI skills are becoming genuinely valuable, not just nice to have on a resume. Anthropic also recently opened an Anthropic Guest Investigator Program for outside researchers in the life sciences, and our guide on how AI can help with research and productivity has more ways to apply this in your own work.
Common Questions
Is AI actually discovering new drugs on its own?
Not yet, and Anthropic doesn’t claim that. Every case study pairs Claude with human scientists who design the experiments and verify the results in the lab.
How far along are these treatments?
Mostly preclinical, meaning they’ve been tested in lab settings or animal models, not yet in human clinical trials. The furthest along, Mithril Medicine’s muscular dystrophy candidate, is targeting human trials around late 2028 if results continue to hold up.
Why does this matter outside of medicine?
The same pattern (AI handling large-scale analysis and paperwork so humans can focus on judgment calls) applies to research, engineering, and plenty of other technical fields, which is why it’s worth understanding even if you’re not in life sciences.
Final Takeaway
This isn’t a story about AI replacing scientists. It’s a story about AI removing the parts of scientific work that were never the interesting part to begin with: the repetitive testing, the paperwork, the thousands of variations nobody could check manually. If that holds up outside these six partnerships, it’s one of the more genuinely useful applications of AI we’ve seen so far, and one worth watching as these programs move from lab results toward real patients. You can read Anthropic’s full case studies directly at its research page on early progress in drug development.
by admin | Oct 28, 2026 | Future Jobs
If you have a quiet feeling that your job is changing shape even though your job title hasn’t, a new report just confirmed you’re not imagining it. Workday, the HR and finance software company, released its 2026 Global Workforce Report on October 5, and its headline finding is refreshingly specific: most business leaders don’t expect AI to shrink their workforce. They expect it to rewrite the jobs people already have.
That’s a different story than the “robots are coming for your job” headlines we’ve covered before, like our look at McKinsey’s occupation-transition forecast. This report is less about people losing jobs and more about people needing to grow into the job they already have. Here’s what it actually found, and what to do with it.
AI Isn’t Replacing Jobs So Much As Reshaping Them
Workday surveyed over 6,000 employees and business leaders, plus a separate pulse survey of nearly 6,000 workers, and pulled real hiring data from roughly 550 enterprise employers. The pattern was consistent: 40% of leaders expect AI to help them get more out of current employees, while only 28% expect it to cut headcount outright.
But “your job isn’t disappearing” doesn’t mean “your job is staying the same.” Internal career moves actually slowed down at 57% of employers year over year, and nearly 4 in 10 employees said their company went through a reorganization in the past year. As Workday’s VP of People Systems, Phil Willburn, put it: “Employees may not be changing jobs, but their jobs are changing around them.”
The Skills Employers Want Have Flipped, Fast
This is the part worth paying attention to. Job postings asking for basic AI skills, things like simple prompting, rose through late 2025, peaked in January 2026, and then fell 25% in the months after. Meanwhile, demand for hands-on AI skills, like building AI tools, automating workflows, and AI engineering, rose 51% between September 2025 and July 2026.
- Knowing how to “talk to ChatGPT” is no longer a standout skill on its own.
- Employers increasingly want people who can build with AI, automate a process, or troubleshoot when it breaks.
- Postings mentioning management and leadership skills fell 7%, and training-related skills fell 13%, over the same stretch.
This tracks with what we found when we looked at which skills matter most for future jobs: the bar keeps moving up from “can you use the tool” to “can you make the tool do something useful for your specific job.”
Quick tip: if your current AI skill set stops at writing good prompts, that’s a good place to start, not finish. Spend a weekend learning how to connect an AI tool to a real workflow you use at work, even a small one, like auto-sorting your inbox or drafting first-pass reports from raw data.
There’s a Real Gap Between What Workers Need and What They’re Getting
Here’s the uncomfortable number: in a September 2026 survey, 79% of employees said they know which skills they need to learn, but only 66% said their employer actually helps them develop those skills. That’s a 13-point gap between knowing and being supported.
Interestingly, confidence isn’t the problem. 65% of employees said they’re confident they could learn new skills if asked to. And among heavy AI users, the picture is a little split: 62% think AI will make their current skills less valuable, yet 76% still expect it to open new career opportunities. People aren’t in denial about this. They’re waiting for someone to hand them a ladder.
From years of working around websites, online tools, and cybersecurity projects, I’ve seen this exact gap play out one-on-one: people are genuinely willing to learn new tools, but they rarely get a clear, structured path to do it at work, so they end up learning in scattered bits on weekends, exactly when it’s most likely to be dropped.
Hiring Is Getting More Competitive, Not Less
If you’re job hunting right now, this part explains why it feels harder: the median number of applicants per open role climbed to 69, up from 58 the year before. In financial services and tech specifically, applications per role rose 27% and 40%, and more than half of applicants in both sectors said AI helped them apply to more roles than they otherwise would have.
In other words, AI is making it easier to apply everywhere, which means everyone is applying everywhere, which means a generic application gets lost faster than it used to. Standing out now leans more on showing you can actually do something with AI tools, not just that you own a ChatGPT account.
Common Questions
Does this mean AI is mostly safe for jobs?
It means mass layoffs aren’t the main story at most companies right now. But roles are genuinely changing shape, and people who don’t adapt their skills risk becoming a worse fit for the job they already hold.
What AI skill should I build first?
Start past basic prompting. Learn to connect an AI tool to one real task you already do, whether that’s data cleanup, drafting, or scheduling, so you have a concrete example to point to.
My employer isn’t offering AI training. What now?
You’re in the 34% majority, according to this report. Free structured options exist, including our own guide to learning AI for free, which doesn’t require waiting on a company training budget.
Is this only a tech-industry trend?
No. The report’s hiring data covers enterprise employers broadly, and the skills shift shows up in management, training, and general operations job postings too, not just engineering roles.
Final Takeaway
The honest summary of this report is that AI isn’t quietly erasing jobs for most companies right now, it’s quietly rewriting them, and the rewrite rewards people who move past basic AI use into actually building and troubleshooting with these tools. If you want a head start, revisit our breakdown of how AI is changing future jobs and treat your current role less like a fixed job description and more like a skill set you keep updating, on your own terms, before someone else decides it needs updating for you.
by admin | Oct 27, 2026 | AI Guides
With the 2026 US midterms just days away, a lot of people are turning to AI chatbots for quick answers about candidates, voting locations, and what’s actually true in their news feed. That raises an honest question about AI election safeguards: can an AI model be used to mislead voters, and what is actually being done to stop it?
Anthropic, the company behind Claude, which just filed to go public, published a detailed update on exactly this, covering how it is preparing Claude for the 2026 midterm elections. It is worth reading in plain English, because the findings say a lot about how people are actually using AI around elections right now, not just what companies promise in a press release.
What Anthropic Found When It Looked at Real Conversations
Anthropic reviewed a random sample of 250,000 US Claude.ai conversations from late September 2026, using a privacy-preserving method that does not expose anyone’s actual chats to a human reviewer. A few numbers stood out.
- About 5.75% of US conversations touch on politics, public policy, or social issues.
- About 0.51% are specifically about elections or voting.
- Only about 0.01% ask Claude who or what to vote for.
- Roughly 0.002% of conversations break the election integrity policy outright.
In other words, most people are not trying to get AI to pick a side for them. They mostly want logistics: where to vote, what the deadlines are, and what a candidate actually said. That is a pretty reassuring starting point, but Anthropic expects political and election questions to climb as election day gets closer, which is exactly why the extra safeguards matter now.
How Claude Tries to Keep You Informed Instead of Misled
A few practical things changed ahead of this election cycle. When you ask Claude.ai about voter registration, polling places, or election dates, it shows a banner linking to TurboVote, a nonpartisan voter resource. Later in October, Claude started pulling official state and local voting details directly from that source, so answers about where to vote or what ID to bring are meant to match your actual state’s rules, not a generic guess. On election night and the days after, it is also set up to surface official vote counts rather than unverified claims.
Anthropic also tests its models for political bias before every release. The newest Claude models (Opus 5.5, Sonnet 5.5, and Haiku 5.5) scored 99% on its internal evenhandedness evaluation, which three outside groups, including researchers at Vanderbilt University, independently reviewed. That testing did surface some real weak spots too, like Claude sometimes tacking an unsolicited counterargument onto a one-sided request, or softening certain arguments more than others. Anthropic says it is actively working on both.
What Claude Will Help With, and What It Flatly Won’t
This is the part that actually matters if you work in or around a campaign, or you just want to know where the line is.
Claude is allowed to help with following election news, researching a candidate’s actual record, understanding where different candidates stand on an issue, navigating government services, and standard campaign work like drafting press statements, fundraising emails, debate prep, or analyzing turnout data.
It is not allowed to be used for creating fake social media profiles that pose as real people, mass-producing comments to fake engagement, writing content for a fake “independent” news site, impersonating election officials, or spreading false information about candidates, voting dates, or voting requirements. Anthropic’s threat intelligence team has already caught and banned real accounts doing some of this, including a foreign-linked fake news operation that used Claude to write US midterm coverage favoring foreign state narratives, the same family of covert tactics we broke down in our look at AI false front operations.
Quick tip: if an AI-generated answer about a candidate, a poll, or a voting deadline sounds oddly specific or oddly certain, check it against an official state election website before you trust it or share it. That one habit catches most AI-generated misinformation on its own.
Why AI Election Safeguards Are Everyone’s Problem to Solve
This connects to a wider pattern. The World Economic Forum’s Global Risks Report 2026 ranks misinformation and disinformation as the second biggest global risk over the next two years, behind only geoeconomic confrontation. AI did not invent misinformation, but it does make it faster and cheaper to produce at scale, which is exactly why every major AI company is now being pushed to publish its own safeguards rather than quietly hoping no one notices.
From working with websites, online tools, and cybersecurity projects for years, I can tell you the pattern is familiar: a safeguard that looks solid in testing can still get bypassed by someone splitting a bad request into several small, individually harmless-looking steps. Anthropic actually found exactly that during independent red-team testing with the Institute for Strategic Dialogue, where Claude reliably refused a single harmful request but could miss a campaign that was broken into smaller pieces. That is worth remembering any time a company tells you a system is “safe.” Safe against what, and tested by whom, are the two follow-up questions that actually matter.
Common Questions
Can I ask Claude or ChatGPT who to vote for?
You can ask, but these tools are built to avoid telling you who to vote for. Expect them to explain candidate positions and let you decide instead.
Is it safe to use AI to find my polling place?
Generally yes, especially when the AI points you to an official source like TurboVote or your state’s election website rather than just answering from memory. Always double-check logistics like deadlines directly on your state’s official site.
What happens if someone uses AI to spread false election information?
Under Anthropic’s usage policy, accounts confirmed to be doing this get banned, and the company says it publishes examples of unintended or abusive model behavior when it finds them.
Does this only apply to US elections?
No. Anthropic mentions extra, more targeted safeguards for localized election risks in the US, Israel, and Brazil, and similar work is ongoing at other AI labs for elections elsewhere.
Final Takeaway
AI chatbots are already part of how people get information during elections, whether that makes anyone comfortable or not. The honest takeaway is simple: use them for logistics and research, lean on official state sources for anything that actually decides your vote, and treat any AI-generated claim about a candidate with the same healthy skepticism you’d give a random social media post. The tools are getting better at policing themselves, but your own habit of double-checking is still the strongest safeguard in the room.
by admin | Oct 26, 2026 | AI Guides
Anthropic, the company behind Claude, just did something it has never done before. On October 26, 2026, it filed paperwork with the U.S. Securities and Exchange Commission to go public. If you use Claude for work, school, or your own projects, this might feel like distant financial news that has nothing to do with you. It’s not. It tells you a lot about how big this company has actually gotten, and how it plans to run itself once millions of outside shareholders are watching.
Here’s what the filing says in plain English, and why it’s worth five minutes of your attention even if you’ve never bought a share of anything in your life.
What Anthropic Actually Filed
An “S-1” is the main registration document a company files with the SEC before it can sell shares to the public for the first time. You can read Anthropic’s actual S-1 filing on the SEC’s own site if you want the source document rather than someone’s summary of it. Anthropic’s own announcement confirms the company plans to list on the Nasdaq Global Select Market under the ticker “ANT.” Goldman Sachs and Morgan Stanley are named as the banks handling the offering.
A few things are still unknown. The company hasn’t said how many shares it will sell, what price range it’s targeting, or an exact listing date. Filing an S-1 starts the clock on a process that usually takes several weeks, not a same-day stock sale. So nothing changes for Claude users today. What changes is how much Anthropic now has to tell the public about its own business, because that’s the price of going public.
The Numbers Behind the Filing
This is the part that’s actually interesting, because it’s the first time Anthropic has had to show its real numbers instead of letting reporters guess. Based on the filing, as reported by TechCrunch’s coverage of the filing, for the first half of 2026 alone:
- Revenue reached $16.3 billion, up from $1.2 billion in the same period the year before.
- Operating loss fell to $693 million, down from $2.1 billion a year earlier, which suggests the business is getting more efficient even while it keeps spending heavily on research and compute.
- More than 11,900 business customers now spend $100,000 or more a year with Anthropic. About 1,900 of those spend $1 million or more, and roughly 250 spend $10 million or more.
The filing also lists a net loss of $80.7 billion, a number that looks alarming on its own. Anthropic attributes most of it to noncash accounting adjustments tied to convertible debt, not everyday operating costs, which is why the much smaller operating loss figure above is the more useful one for judging how the actual business is doing. Even so, the company is direct about the risk involved, stating plainly that it “may not achieve or sustain profitability in the future.”
Important tip: this post explains what the filing says. It is not investment advice, and nothing here is a suggestion to buy or sell anything. If you’re genuinely considering investing once ANT lists, talk to a licensed financial advisor who can look at your own situation.
Who Actually Controls Anthropic After It Goes Public
This is the detail I think deserves more attention than it’s getting. Anthropic’s seven co-founders, including Dario Amodei and Daniela Amodei, are forming what the filing calls a “Founder LLC” that will hold 50.1% of shareholder voting power. On top of that, a Long-Term Benefit Trust set up back in 2023 keeps the authority to appoint most of the board.
In plain terms, outside shareholders will own a meaningful piece of the company, but the founders and the trust keep the steering wheel. For a company that has built its public identity around safety and careful AI rollout, that’s not an accident. It’s a structural promise that quarterly earnings pressure won’t quietly override the safety commitments Anthropic has made. Whether that promise holds up over the next few years is something worth watching, not something this filing can prove on its own.
From my own time working on websites, online tools, and smaller digital projects, I’ve seen how much a company’s priorities can shift once it answers to outside shareholders every quarter. Anthropic building in a governance structure meant to resist that pressure, before it even starts trading, says something about how seriously it’s taking the tradeoff. It fits a pattern we’ve been tracking all month, from Anthropic’s new Cyber Mission for defending critical infrastructure to its decision to donate the Agent Skills standard to a neutral foundation instead of keeping it locked to Claude alone.
What This Means If You Use Claude for Work, Study, or Business
For most everyday users, nothing changes this week. But a few practical takeaways are worth keeping in mind.
First, nearly 12,000 businesses paying over $100,000 a year is a serious customer base, and it hints at continued investment in the tools millions of people already rely on for work and research, not a side project getting cut.
Second, a public listing usually means more scrutiny, not less. Once Anthropic starts filing quarterly reports, journalists and researchers will have far more detail to pick apart than they do today, which is generally a good thing for anyone who wants AI companies to be more transparent about how their models perform and cost.
Third, if you’re a student or early-career professional tracking where the AI job market is heading, a company this size preparing to go public usually signals continued hiring, not a slowdown. Anthropic has also been opening its research tools to outside scientists lately, including a new guest investigator program for life sciences researchers and the recent Claude Haiku 5.5 release aimed at cheaper models at scale, both signs of a company still building.
Common Questions
Does this mean Claude will change or get more expensive?
Nothing in the filing says pricing is changing. Public companies do face more pressure to show steady revenue growth, so it’s reasonable to watch pricing over time, but there’s no announcement of a change right now.
When will ANT actually start trading?
Anthropic hasn’t given an exact date. Filing an S-1 is an early step in the IPO process, and the SEC still has to review it before shares can legally be sold to the public.
Can I invest in Anthropic right now?
No. The filing states clearly that the securities described cannot be sold or bought until the registration takes effect. Anything you see online offering shares before that point should be treated with real caution.
Is a net loss of this size a bad sign?
Not necessarily on its own. The filing attributes most of the loss to noncash accounting items tied to convertible debt rather than day-to-day operating costs, and the operating loss actually shrank year over year even as revenue grew more than tenfold.
Final Takeaway
Anthropic’s IPO filing is less about the stock ticker and more about what it reveals: a company that has grown from roughly a billion dollars in revenue to over sixteen billion in a single year, built a governance structure designed to protect its safety mission from shareholder pressure, and is now required to show its work in public. You don’t need to own a single share to find that worth understanding, especially if Claude is already part of how you work, study, or build.
