Fintech firm Mercury recently dropped some data that made me smile. It ranked the top five coffee shops powering founders in San Francisco based on actual transaction data: Sightglass, CoffeeShop, Equator, Saint Frank, Ritual. I’ve built Octolane with my cofounder, Rafi, from every single one of them.
But here’s what the data doesn’t show: the $500,000 investment term sheet I negotiated over a cortado at Cafe Réveille. The $800,000 deal I closed while sitting next to a grad student cramming for finals. The three customers who became friends, then advocates, then our biggest champions, all because we met first over coffee, not Zoom.
When I was in high school, I cleaned offices at night, empty offices with ergonomic chairs and standing desks and those motivational posters about “innovation.” Meanwhile, I’m building an AI company worth millions from a wobbly table at a coffee shop, and somehow this feels more real, more honest than any corner office ever could.
The distributed office isn’t dead, it just moved to cafés.
I wake up at 5 a.m. here in San Francisco, because those three hours before the city stirs are mine. I review what our AI models learned overnight. I write. I think. Then I head to whichever coffee shop matches my energy that day.
Saint Frank when I need to focus, since it’s quieter, more intimate. Sightglass when I want that productive hum of energy around me. Equator when I’m meeting someone for the first time and want them to feel comfortable, not intimidated.
Rafi, my cofounder and CTO, moved internationally to build this with me. One of our engineers handles the front end from one continent, another tackles the back end from another. So why would I pay $8,000 a month for an office in SoMa (the neighborhood South of Market Street) when I can spend $200 a month on lattes and have the entire city of San Francisco as my workspace?
What I’ve Learned Building in Public (Literally)
The serendipity factor is real. Last month, I was debugging a particularly nasty prompt engineering issue, trying to get our AI to detect deals in Gmail without false positives. I was muttering to myself (yes, I’m that guy) when someone at the next table leaned over: “Are you working on LLM classification?” Turns out hes an AI researcher at Anthropic. Twenty minutes later, I had a completely new approach that cut our error rate in half.
You can’t engineer that in a conference room.
Practical wisdom. Keep your screen visible enough that interesting work attracts curious people, but angle it so you’re not broadcasting sensitive customer data. The sweet spot is showing code or product UIs, technical enough to spark conversations with the right people, general enough to protect privacy.
Investors are humans too. The $500,000 investment I mentioned? It happened because I was at Réveille at 3 p.m., and so was he. We were the only two people there. We chatted and he learned more about what I was working on. I showed him our productnot a deck, not a demo, just the actual thing, running, solving a real problem. He saw me working, grinding, building. The next day, the term sheet came through.
Later he told me: “I invested because youre willing to be different and bold to stand out.” What he didn’t say, but I know mattered: Other founders had already told him about the guy who’s always at Réveille, laptop open, building. And when he left that day, I was still there.
Midnight founder cafés are a thing now: late-night coffee shop takeovers where founders and engineers gather to build, network, and fuel up on free caffeine, and big AI companies are leaning into it. Cursor’s been running “Café Cursor” pop-ups across San Francisco, New York, Stanford, even Guadalajara, taking over coffee shops for a day, giving out free coffee and those coveted keychains, merch thats shaped like the tab keyboard key (a nod to the keystroke that accepts Cursor’s AI suggestions).
Anthropic did a weeklong Claude Café pop-up in New York City’s West Village that drew more than 5,000 people, with their “thinking” hats becoming so viral that people claimed they flew across the country just to get one.
These aren’t permanent cafés, they’re pop-up experiences. But that’s exactly the point. They’re recognizing what we already know: The best AI work happens in liminal spaces. Not quite work, not quite social. Somewhere in between. That’s where the guard comes down: You’re not pitching, you’re just talking. And the person debugging next to you might casually mention the fix you’ve been stuck on for a week.
And it goes deeper than corporate activations. There’s a founder in the Mission District of San Francisco who literally opened his house as a café after midnight. Just for founders. No tourists, no meetings, just people building. I’ve been there twice. Both times, I left with ideas I couldn’t have found anywhere else.
The only AI company that’s actually opened a permanent café? Perplexity, in Seoul. But even they get it! They put a podcast studio and a single computer running their search engine in the basement. The coffee shop isn’t the product. The community is.
The Practical Reality (Because Romance Only Gets You So Far)
Here’s what they don’t tell you about the coffee shop life:
You need three spots minimum. One for deep work (quiet, consistent Wi-Fi, you know the outlet situation). One for meetings (good acoustics, professional-ish vibe, not too loud). One for when the first two are full or you just need a change.
Noise-canceling headphones are nonnegotiable. But here’s the thing: I don’t always use them. Sometimes I want to hear the ambient noise, the conversations, the espresso machine. It reminds me that I’m building something for real people, not just for the AI models or the pitch deck.
Your burn rate matters. Every dollar matters. An office in San Francisco costs $5,000 to $10,000 minimum. That’s a month of runway. That’s an engineer. That’s 100-plus customer acquisition attempts. So yeah, I’ll take the $5 latte.
Time-of-day strategy is everything. I’ve mapped it out.
Early morning: Saint Frank or home (deep work, model review, writing)
8 a.m. to noon: Sightglass or Equator (customer calls, team syncs)
Noon to 3 p.m.: Avoid peak lunch chaos, take meetings walking or find a quieter spot
3 to 6 p.m.: Ritual or CoffeeShop (energy picks back up, good for creative work)
After 6 p.m.: Usually home, but the midnight café if I need the founder energy
What Building from Coffee Shops Taught Me About AI
There’s a parallel here that keeps itting me: AI works best when it has context. Every engineer here is building on the idea that AI should understand the full context of your communication, not just isolated data points.
Coffee shops give me context. I see how people actually work. I hear what founders are struggling with. I feel the energy when someone closes a deal or the deflation when funding falls through. You can’t get that from a dashboard or a user interview. You have to be there, in it, living it.
When I’m prompt engineering at 9 a.m. at Saint Frank, watching the barista dial in the espresso, I’m thinking about patterns. About how humans and machines both learn through repetition, through feedback, through context. The best prompts I’ve written came from coffee shops. The best features we’ve built came from problems I overheard someone complaining about two tables over.
The deeper insight is that building in isolation makes you optimize for the wrong things. You optimize for elegance, for technical beauty, for what impresses other engineers. Building in public, literally surrounded by your users, keeps you grounded in what actually matters: Does this solve a real problem for a real person?
Building from coffee shops keeps me honest. I can’t hide behind the performance of “founder working in office.” I can’t pretend to be productive when I’m not. If I’m stuck, I’m stuck in public. If I’m building, I’m building where people can see the mess, the mistakes, the reality.
We’re trying to replace Salesforce with Octolane. That’s aggressive, maybe delusional. But I’ll tell you this: I’d rather chase it from a coffee shop in the Mission, surrounded by other founders equally delusional and equally committed, than from a sterile office where everyone pretends to have it figured out.
How to Actually Make This Work
If you’re thinking about ditching the office, here’s what I wish someone had told me:
Map your energy to your spaces. Don’t just pick a coffee shop because it’s close. Figure out what work you do best where. I write best at quieter spots. I sell best in energetic spaces. I code best with moderate ambient noise.
Become a regular somewhere. Not everywhere, somewhere. One spot where they know your order, where you have your table, where you’re part of the ecosystem. For me, it’s Réveille. That consistency matters when everything else is chaos.
Respect the space. Buy something every two to three hours. Tip well. Don’t monopolize tables during peak times. The coffee shop isn’t your free office, it’s a business that’s subsidizing your dream. Honor that.
Build relationships, not just networks. That Anthropic engineer? We’re friends now. The investor? We get coffee every few weeks. The other founders? We text each other when we’re heading to a spot. This only works if you’re actually present, actually human, actually building relationships.
Know when to go home. Sometimes you need silence. Sometimes you need privacy. Sometimes you need to take a call that can’t happen in public. Don’t force it. The coffee shop is a tool, not a religion.
The Launch Is Coming
I’ll probably launch our product from a coffee shop. Maybe Saint Frank, maybe Réveille, maybe that midnight café in the Mission. My team will be distributed across the country, asleep in some time zones, working in others. And somehow, we’ll pull it off.
Because the best work doesn’t happen in offices. It happens where life happens. Where the coffee is strong, the Wi-Fi is reliable enough, and the person next to you might just have the insight that changes everything.
Mercury’s data showed the top five coffee shops powering SF founders. What it didn’t show is why. It’s not the coffee. It’s not even the Wi-Fi.
It’s the reminder that you don’t need permission to build something great. You just need conviction, a laptop, and a table.
See you at the café.
Gen Zers, who were practically born with smartphones and iPads in their hands, have grown up completely immersed in the information highway. Therefore, it should come as no big surprise that those born as digital nativesdeeply connected to culture, trends, politics, and businesshave different ideas about what their contributions to the world should look like. They deeply value work-life balance and they need to feel like the work they do has meaning.
Globally, they are the generation most concerned about issues like corruption and inequality. They’re striving to create changeand they’re committed.
Still, Gen Zers often get called out for being entitled, lazy, or simply not being driven. However, according to a recent conversation between executive Garry Ridge, former CEO of WD-40, and Simon Sinek, author and thought leader, it’s not a lack of commitment or drive that sets Gen Z apart in the workplace. It’s a well-earned lack of trust in leadership.
On his podcast, A Bit of Optimism, Sinek posed a question to his guest about why Gen Z seems to work backward when compared to past generations. Contrary to the old playbook, where employees were expected to work hard and showcase their commitment before getting a raise, a promotion, or other payout, Gen Z needs to see the reward up front.
“That could be interpreted as entitlement,” Sinek said. “I understand it as they grew up in a world where there’s no loyalty from the company.”
Basically, if a company doesn’t have an employee’s back, should the employee really be expected to hustle for said company? Gen Z doesn’t think so. In his conversation with Sinke, Ridge agreed, noting that the logic is completely understandable, given the generation’s deep distrust of big business.
Ridge asserted that companies shouldn’t dismiss these young employees as lazy or unmotivated. Rather, they should work with them to build that essential trust, providing more frequent and clear-cut steps to move up the ladder.
“Once upon a time you had these reviews where you were actually looking backward. Well, maybe now the way to go is having steps along the way so you can recognize performance, Ridge said, using the example of giving employees the opportunity to earn accolades by having check-ins every couple of months to assess performance.
Further, Ridge and Sinek agreed that year-end reviews aren’t a great stepping stone, either. And, from that lens, maybe Gen Z is spot-on when it comes to phasing out the old system.
“I don’t want to wait 364 days for you to tell me what I should’ve done better or how good I’ve done,” Ridge explained of the Gen Z mindset. “What I want to do is be coached along the way.”
Call them lazy and entitled all you want, but Gen Zers, many of them having watched their parents work hard their whole lives with little to show for it financially in their later years, don’t want to hustle without a clear payout.
Honestly, who could blame them?
December is here, and another year has blown by. Chances are, youre going to get some time off for the holidays. If so, you may have a week(-ish) to recharge before you have to ramp back up in January.
In order to get the most out of your time off, it would be ideal if you could unplug from work completely to give your mind a rest and to focus on family, friends, and yourself. There are a few things you can do to prepare now that will help a lot and will also make your transition back to the office go smoothly.
Close as many tasks as possible
Research going back almost 100 years finds that when you have a task to complete, you are highly motivated to finish it. It stays active in your memory, and you seek opportunities to get it done.
That tendency is normally a good one. But on a break, it is a factor that will drive your mind back to the workplaceeven when youre supposed to be relaxing. To give yourself the best chance to chill, see if you can close out key tasks before you leave. At a minimum, reach a good stopping place on tasks so that you dont feel like you have left them incomplete.
You should also avoid starting any big new projects that will hang over the break. Instead, focus on polishing off as many unfinished things as possible.
Comment your work
If you take an introductory programming class, the instructors will drill into your head that you should “comment your code” as you go along. The aim is to write down a glossary of key variable names, the purpose of sections of code, and any other information about critical data structures, functions, or procedures that will remind you what the code was about. The idea is that the whole structure seems obvious while youre writing it, but if you have to return to that code weeks, months, or even years later, you will have no recollection of what you did. So, leaving comments will enable you to reconstruct the purpose of that section of code.
The same holds true for many of the elements on your current to-do list. When youre in the office daily, you can recall from one day to the next the purpose of various meetings, the status of key projects, and the reasons for decisions that were made about ongoing work.
Even after a week off, some of those details may get fuzzy. Before you head out for vacation, take some time to make notes on the core elements of ongoing projects. Include little reminders of why things are being done the way they are. Make sure you have good notes to remind you of meetings the first week or two you’re back from break. It takes extra time to add these notes (particularly if youre not used to doing so), but youll thank yourself later.
Also, the AI systems powering many email systems are now trying to add relevant documents and notes to meetings on your calendar. That is great, but take the time to see whether the documents and other information included in the meetings on your calendar are actually relevant to what you need to work on. If not, add some information yourself to make sure youre ready after you get back.
Check in with your team
If you really want to be able to relax, check in with all of your team members the week before you head out. You probably arent in complete control of every project youre working on.
When you talk with your team, find out if there are any major crises brewing that youll need to address when you get back. If there is anything you can do to help with those before the vacation, prioritize that. In addition, get early warning about any last-minute tasks you may be asked to do before heading out. You dont want to feel pressure to finish something on your way out the door to start your break. Most people dont do their best work in such a rushed situation.
If you have any direct reports, encourage them to relax, recharge, and renew during the break. The people who work for you probably want you to have a good impression of their work, and some of them may feel like youll appreciate them doing additional work over the holidays. Everyone needs downtime. A word from youassuring them that the best thing they can do during the holiday break is to put their work asidewill go a long way toward helping your team come back feeling refreshed.
Dont forget your vacation message
You should do your best to avoid checking email over the break. It can be tempting to find out what has come in, but once you start checking, you run the risk of going down a rabbit hole that can eat up several hours of your precious relaxation time.
Instead, before you head out the door, take advantage of the tools in your email system to leave an out-of-office message. Lots of people do that routinelybut if you have resisted so far, it is time to give in. If people know youre not going to be responding to messages until the new year, youre not under any pressure to get them a response faster.
Of course, if youre in a business in which emergencies can arise, make sure key individuals and clients have a way to reach you should something serious go wrong. But otherwise, structure your communication channels so that there is no need to look at anything until after you get back.
For most of my career at LOréal, I sold confidence in a tube: lipstick. But lipstick isnt just about applying color to your lips. Its about identity. Ritual. Power.
Beauty has never been superficial. Its always been about self-esteem, self-confidence, and self-expression, knowing that how youre feeling inside is reflected on the outside.
Today, the boldest expression of that confidence comes from beyond the makeup bag: Its a full nights sleep working with a skincare routine, balanced hormones supporting a healthy glow, nutrients fueling both energy and radiance, and gut health supporting complexion.
The truth is simple: Health is the new lipstick. Health amplifies beauty, and beauty reflects health.
HEALTH AND BEAUTY: ONE SYSTEM
Beauty and health have always been collaborators, even when industries treated them separately. Both are rooted in science, innovation, and empathy. And both rely on trust, with the aim of helping people feel good in their bodies and confident in their lives.
Its not a coincidence that the same ingredients work in products from both sectors. Hyaluronic acid hydrates skin while supporting joint comfort and gum health. Collagen strengthens hair, nails, skin, and bones. Omega-3s reduce inflammation that affects both your complexion and your cardiovascular system. Vitamin C brightens skin while boosting immunity.
Consumers already see what brands are beginning to acknowledge: Health and beauty are inseparable. Their retinol serum sits next to their vitamins in the medicine cabinet. They use SPF and track their vitamin D. They meditate and hydrate, move their bodies and manage stressnot as separate rituals, but as one integrated practice of self-care.
Younger generations, especially Gen Z, are leading this shift. For them, wellness is identity and self-expression. Their routines blend skincare with supplements, mindfulness with makeup. They dont distinguish between looking good and feeling goodboth are expressions of confidence and authenticity.
This mindset is reshaping how the health and beauty industries must operate, not just as parallel markets, but as two sectors converging into a single wellness ecosystem.
A CALL-TO-ACTION FOR BRANDS
Its time for us not to redefine wellness but embrace it in its entirety. Our consumers arent just investing in their well-being, theyre investing in confidence, energy, and vitality that cant be replicated by the latest shade. That means that as leaders of health, wellness, and beauty brands, we must:
1.Celebrate holistic confidence. Emphasize that outer beauty and inner well-being are inseparable pieces of the same puzzle.
2. Invest in inclusive science. Diverse clinical research ensures that efficacy and safety reflect every skin tone, identity, and body typeand empowers each consumers sense of self.
3. Measure what matters. Lets show impact not just in numbers, but in the confidence, comfort, and care we help people achieve.
4. Align, not compare. Beauty and health brands can share insights, language, and purpose to meet people where their needs intersect.
As brands, we should be guided by the consistent actions consumers follow when developing new products: fueling their body with the right nutrients, getting a good nights sleep, managing pain before it interferes with life, and yes, applying that favorite shade of lipstick before stepping out the door.
When health and beauty work in harmony, confidence isnt just worn, its lived.
Nathalie Gerschtein is the CEO USA and president North America of Haleon.
If youre thinking of buying your kid a talking teddy bear, youre likely envisioning it whispering supportive guidance and teaching about the ways of the world. You probably dont imagine them engaging in sexual roleplayor giving advice to toddlers about how to light matches.
Yet thats what consumer watchdog the Public Interest Research Group (PIRG) found in a recent test of new toys for the holiday period. FoloToys AI teddy bear Kumma, which uses OpenAIs GPT-4o model to power its speech, was all too willing to go astray when in conversation with kids, PIRG found.
Using AI models voice mode for childrens toys makes sense: The tech is tailor-made for the magical tchotchkes that children love, slipping easily onto shelves alongside lifelike dolls that poop and burp, and Tamagotchi-like digital beings that kids want to try and keep alive. The problem is that unlike previous generations of toys, AI-enabled gizmos can veer beyond carefully pre-programmed and vetted responses that are child-friendly.
The issue with Kumma highlights a key problem with AI-enabled toys: They often rely on third-party AI models that they dont have control over, and which inevitably can be jailbrokeneither accidentally or deliberatelyto cause child safety headaches. There is very little clarity about the AI models that are being used by the toys, how they were trained and what safeguards they may contain to avoid children coming across content that is not appropriate for their age, says Christine Riefa, a consumer law specialist at the University of Reading.
Because of that, childrens-rights group Fairplay issued a warning to parents ahead of the holiday season to suggest that they stay away from AI toys for the sake of their childrens safety. Theres a lack of research supporting the benefits of AI toys, and a lack of research that shows the impacts on children long-term, says Rachel Franz, program director at Fairplays Young Children Thrive Offline program.
While FoloToy has stopped selling the Kumma and OpenAI has pulled FoloToys access to its AI models, thats just one AI toy manufacturer among many. Whos liable if things go wrong?
Riefa says theres a lack of clarity here, too. Liability issues may concern the data and the way it is collected or kept, she says. It may concern liability for the AI toy pushing a child to harm themselves or others, or recording bank details of a parent.
Franz worries thatas with big tech companies racing to one-up each other the stakes are even higher when it comes to child products by toy firms. It’s very clear that these toys are being released without research nor regulatory guardrails, she says.
Riefa can see both the AI companies providing the models that help toys talk and the toy companies marketing and selling them to children being liable in legal cases.
As the AI features are integrated into a product, it is very likely that liability would rest with the manufacturer of the toy, she says, pointing out that there would likely be legal provisions within the contracts AI companies have that shield them from any harm or wrongdoing. This would therefore leave toy manufacturers who, in fact, may have very little control over the LLMs employed in their toys, to shoulder the liability risks, she adds.
But Riefa also points out that while the legal risk lies with the toy companies, the actual risk fully rests with the way the LLM behaves, which would suggest that the AI companies also bear some responsibility. Its perhaps that which has caused OpenAI to push back its AI toy development with Mattel this week.
Understanding who really will be liable and to what extent is likely to take a little while yetand legal precedent in the courts. Until thats sorted out, Riefa has a simple suggestion: One step we as a society, as those who care for children, can do right now is to boycott buying these AI toys.
For 50 years, Americas generosity has been stuck in neutral with charitable giving frozen at 2.5% of GDP. But not because people stopped caring. In 2024, total giving hit record highs, and food banks saw donations surge as families faced delays in SNAP benefits. The heart is there. Whats missing is technology that turns generosity into lasting impact.
We cant solve todays biggest problems, from food insecurity to climate change to health inequity, without unlocking the full potential of AI. For the first time, technology connects data across causes, predicts needs before they arise, and turns generosity into measurable progress. If generosity is the fuel, AI is the engine. As we look to reignite that engine, the clear path forward is to empower the social good ecosystem with smarter, more human technology.
Enter the Generosity Generation. Its not an age group, but a global movement of people across every generation using innovation to turn compassion into scale. The movement is built on the belief that connection beats competition, collaboration beats control, and impact grows when information flows freely.
Achieving that scale requires a shift in how technology serves people. The next leap wont come from software that asks humans to do more work, but from AI that helps them do more good. Human-led AI doesnt replace purpose; it amplifies it. Its how we break 50 years of stagnation and build a more generous world.
THE HIDDEN COST OF SOFTWARE IN THE SOCIAL SECTOR
Software is meant to save time. Instead, for many organizations, it feels like one more task to manage before the real work begins.
In the corporate world, software transforms productivity. In the social sector, those same gains often require a level of investment, in time, training, and expertise, that smaller nonprofits cant afford. Every new platform promises efficiency, but the cost of setup and maintenance may outweigh the benefits. Time meant for impact gets traded for time spent logging impact.
Picture a grant-writing team adopting a streamlined new tool. Weeks later, theyre back in spreadsheets because the learning curve was too steep, the data entry too heavy, the payoff too slow.
Agentic AI works quietly in the background, scanning thousands of grant opportunities overnight, drafting proposals, surfacing insights, and freeing people to do hands-on work: building relationships, telling stories, and driving missions forward.
Thats the real shift, from software that creates work to software that creates capacity. But transformation doesnt start with automation. It starts with trust. And thats where every organization, from a grassroots nonprofit to a Fortune 500, must now lead.
TRUST: THE REAL METRIC FOR AI
AIs most important metric isnt speed or scale. Its trust. Even the most tech-oriented nonprofits must ensure that the tools they use reflect their own values: transparency, security, and accountability.
In the social sector, trust is currency. For nonprofits, a single breach undermines years of donor confidence. For companies, it erodes brand equity overnight. Across every mission-driven organization, trust is the shared foundation, and every tool must protect it.
Thats why human-led AI matters. Agentic systems act, recommend, and adapt, but they should never act alone. Keeping people in the loop ensures every decision reflects human judgment, not just machine logic.
When AI earns that trust, the impact multiplies. Fundraisers find the right message faster. Corporate teams see where volunteer hours matter most. Foundations match funding in days, not months. And when its guided by transparency and accountability, AI not only protects trust, but deepens it.
WHEN AI ELEVATES HUMAN IMPACT
Data has always told us what happened. AI finally shows us whats possible.
In the nonprofit world, every community, cause, and donor is different. Yet, most tools still offer one-size-fits-all answers. Agentic AI changes that by turning data into understanding, helping every organization communicate with its community in the language of shared values, rather than generic outreach.
For decades, personalization has helped businesses build trust with customers. Now, it helps the social sector establish trust with its constituents. Because personalization here isnt about selling more, its about seeing more: who needs help, what inspires them, and where generosity has the most impact. The real turning point is when understanding shifts into empathy, and that empathy fuels action.
When data builds transparency, people engage. When they engage, generosity grows. Thats how trust translates into impact. Pair human purpose with autonomous tools, and giving doesnt just scale, it transforms. Thats how we turn information into action, and generosity into a movement.
Across every generation, people want to do more good. Now they finally have the means to do it. Human-led AI gives us back what every mission needs most: time, connection, and trust.
Imagine if Americas giving rate rose by just half a point, from 2.5% to 3%. That single shift would unlock $141 billion in new annual giving. Enough to lift every American above the poverty line. Enough to make college tuition-free. Enough to prove whats possible when technology empowers human purpose instead of replacing it. Thats the power of the Generosity Generation, proving that when human purpose meets the right technology, possibility becomes progress.
Whether you lead a nonprofit, a foundation, or a Fortune 500 CSR team, your mission is the same: turn information into measurable action. Use technology not to automate generosity, but to amplify it.
AI wont build the Generosity Generation. People will, with the freedom, insight, and tools to lead it.
Scott Brighton is the CEO of Bonterra.
Instacart said Monday that it will no longer allow retailers to use an AI-powered price testing program, two weeks after an extensive investigation showed wide discrepancies in the cost of groceries purchased through the platform.
Effective immediately, retailers will no longer be able to use Eversight technology to run price tests on Instacart, the San Francisco-based company said in a blog post. Previously, a small number of retail partners were able to conduct testing that resulted in different prices for the same item at the same storesomething that missed the mark for some customers, Instacart said in a blog post.
At a time when families are working exceptionally hard to stretch every grocery dollar, those tests raised concerns, leaving some people questioning the prices they see on Instacart, the company said. Now, if two families are shopping for the same items, at the same time, from the same store location on Instacart, they see the same pricesperiod.
Mondays announcement of the end of item price tests marks the third time that Instacart has responded to a widely-shared study by Consumer Reports and Groundwork Collaborative. The monthslong investigation conducted by the magazine and progressive policy group found that algorithmic pricing might result in price differences for the same items of as much as 23%.
INSTACART IN FOCUS IN D.C.
Instacart responded swiftly to the concerns raised in that investigation. In a lengthy blog post late last week, the company sought to clarify what sorts of pricing tests it doesand doesntallow on the platform by responding to four different myths, including that it was engaging in dynamic or surveillance pricing.
But the tech company also came under renewed scrutiny in Washington, D.C. as a result of this study. Rep. Angie Craig, a Democrat from Minnesota, demanded answers from Instacart regarding the scope and implications of pricing tests, while the Federal Trade Commission sent a civil investigative demand to Instacart about its pricing practices, as Reuters reported last week.
Instacart was recently the subject of an FTC investigation regarding deceptive business practices. The company was ordered to pay $60 million in consumer refunds, though it denied any allegations of wrongdoing and answered questions from the government agency regarding its AI pricing tools as part of that settlement.
REGAINING TRUST
The company reiterated again Monday that it has not permitted retailers to do price testing based on supply or demand, personal data, demographics, or individual shopping behavior. Instagram ended the price testing program to engender trust with its customers.
Customers should never have to second-guess the prices theyre seeing, the company said.
Though shares of Instacart fell about 2% in mid-day trading on Monday, it has almost fully recouped a nearly 6% selloff that followed the publication of the price testing study earlier this month.
The long-awaited release of Jeffrey Epsteins files by the Department of Justice arrived on December 19 with a bureaucratic whimper and bang of public outrage.
While the Epstein Library technically fulfills the government’s legal obligation under the Epstein Files Transparency Act, the result is a user experience failure.
[Image: United States Department of Justice]
Thankfully we have another option. Jmail.world makes searching the Epstein files as simple as searching your email. The project has been publishing the convicted child sex offender’s emailsand those of the people who talked with him, like Noam Chomsky, Steve Bannon or Ken Starrsince November using a Gmail user interface clone. Jmail’s database was filled over the weekend as it added the latest Epstein file release.
[Screenshot: jmail.world]
Created by technologists Riley Walz and Luke Igel, theres no better way to explore this Himalaya of filth. It uses a UI you already know: Gmail and the rest of Gmail apps, like Drive. Its creators have been updating it quietly since its launch, even adding an AI called Jemini to search across media, to demonstrate that the DOJ claims that due to technical limitations, it’s impossible to search certain materialslike handwritten notesis simply not true.
How Jmail was built
Jmail began in November, after the House Oversight Committee released 20,000 pages of Epsteins estate emails. Walz and Igel saw a “design problem” in those unsearchable PDF dumps. Using Optical Character Recognition (OCR), they extracted the text and mapped it onto a simulation of Epsteins actual Gmail inbox.
[Screenshot: jmail.world]
The result was a tool that feels unnervingly familiarat least I feel weird and dirty browsing it. It’s a standard inbox with “Star” icons and threaded conversations that forces users to confront the banality of Epsteins daily operation.
The Gmail clone works as you would expect. Instead of navigating complex federal indices, you simply type “Maxwell” or “Bannon” or any phrase that comes to mind into a search bar that queries every email, attachment, and contact instantly. The same happens in the other apps. And you can also click on Jeminiintroduced on December 3and just query the AI about whatever content you want, all across the database.
Why email is the right interface for the Epstein files
You may wonder why the Epstein Files needs a specialized site at all. After all, the official DOJ site has a “Search Full Epstein Library” bar. The problem is, it comes with a crippling disclaimer: “Due to technical limitations and the format of certain materials… portions of these documents may not be electronically searchable.” In practice, this means thousands of scanned pageswhere the real secrets lieare invisible to the search engine.
To understand the brilliance of Jmail, you have to understand the DOJs barebones compliance with the law dictated by Congress. The files are there, yes, but they are effectively buried under the weight of their own disorganization. The DOJs rolling release strategy has resulted in a fragmented archive where First Phase” declassified files sit separately from “Data Set 7,” and where vital context is usually hidden behind thick black redaction bars.
[Screenshot: jmail.world]
As Representative Thomas Massie has pointed out, it “grossly fails to comply with both the spirit and the letter of the law.” By dumping thousands of unsearchable, context-free PDFs onto a confusing web portal, the Justice Department has technically checked a box while affectively obstructing the public’s ability t understand the contents. The data may be public, but it is certainly not accessible, hence rendering it almost useless for the public.
In a discussion on Hacker News dated December 19, Igel revealed the collaborative effort to beat the DOJ at its own game: “We had a ton of friends collaborate on building out more of the app suite last night in lieu of DOJ’s ‘Epstein files’ release… JPhotos, JDrive, JAmazon.” They launched a full “app suite” designed to make the files grokable. By organizing the chaos into familiar tools, Jmail.world provides the searchability the government claimed was technically impossible, serving as a critical, citizen-led solution to official opacity.
Meanwhile, the new version of Jmail is the closest thing we have to a complete picture of the Epstein case files. The site fulfills the promise that the Transparency Act made but failed to keep: making the truth actually visible. I just wish the AI could be smart enough to turn those black bars into the actual names.
Coinbase said on Monday it will buy prediction markets startup The Clearing Company, its tenth acquisition this year, as the crypto exchange looks to expand beyond its core digital assets business.
Prediction markets let users buy and sell contracts tied to the outcomes of real-world events, ranging from elections and economic data to sports and policy decisions, effectively turning investors’ forecasts into tradable markets.
Supporters say the prices can reflect collective expectations more accurately than polls or forecasts, while critics argue the products blur the line between financial markets and betting, drawing growing scrutiny from regulators.
Prediction markets surged into the mainstream during the 2024 U.S. presidential race and have since drawn rapid interest and investments from all corners of the financial ecosystem.
Meanwhile, trading platforms are broadening their product suites to encompass multiple asset classes under one roof as competition intensifies. This shift, analysts say, could help Coinbase reduce its reliance on crypto trading as new players crowd the market.
“Prediction markets offer the company a high-engagement, high-frequency product that broadens the reasons for opening its app beyond crypto,” analysts at brokerage Benchmark wrote in a note last week.
Earlier this month, Coinbase launched its prediction markets platform and said it will start letting users trade stocks, positioning it as a direct competitor to brokerages such as Robinhood and Interactive Brokers.
“We see many of Coinbase’s new initiatives encouraging and incentivizing customer engagement, which has been episodically more limited,” analysts at brokerage J.P. Morgan wrote in a note after the products were unveiled.
The deal for The Clearing Company is expected to close in January. Coinbase did not disclose the terms of the transaction.
Among its notable deals this year, Coinbase agreed to buy derivatives exchange Deribit for $2.9 billion in May, and struck a roughly $375 million deal for investment platform Echo in October.
Its shares were last up 2.6% in afternoon trading.
Manya Saini, Reuters
