This week, juries in California and New Mexico dealt a pair of landmark verdicts against America’s social media giants.
Tech
‘Observational memory’ cuts AI agent costs 10x and outscores RAG on long-context benchmarks
RAG isn’t always fast enough or intelligent enough for modern agentic AI workflows. As teams move from short-lived chatbots to long-running, tool-heavy agents embedded in production systems, those limitations are becoming harder to work around.
In response, teams are experimenting with alternative memory architectures — sometimes called contextual memory or agentic memory — that prioritize persistence and stability over dynamic retrieval.
One of the more recent implementations of this approach is “observational memory,” an open-source technology developed by Mastra, which was founded by the engineers who previously built and sold the Gatsby framework to Netlify.
Unlike RAG systems that retrieve context dynamically, observational memory uses two background agents (Observer and Reflector) to compress conversation history into a dated observation log. The compressed observations stay in context, eliminating retrieval entirely. For text content, the system achieves 3-6x compression. For tool-heavy agent workloads generating large outputs, compression ratios hit 5-40x.
The tradeoff is that observational memory prioritizes what the agent has already seen and decided over searching a broader external corpus, making it less suitable for open-ended knowledge discovery or compliance-heavy recall use cases.
The system scored 94.87% on LongMemEval using GPT-5-mini, while maintaining a completely stable, cacheable context window. On the standard GPT-4o model, observational memory scored 84.23% compared to Mastra’s own RAG implementation at 80.05%.
“It has this great characteristic of being both simpler and it is more powerful, like it scores better on the benchmarks,” Sam Bhagwat, co-founder and CEO of Mastra, told VentureBeat.
How it works: Two agents compress history into observations
The architecture is simpler than traditional memory systems but delivers better results.
Observational memory divides the context window into two blocks. The first contains observations — compressed, dated notes extracted from previous conversations. The second holds raw message history from the current session.
Two background agents manage the compression process. When unobserved messages hit 30,000 tokens (configurable), the Observer agent compresses them into new observations and appends them to the first block. The original messages get dropped. When observations reach 40,000 tokens (also configurable), the Reflector agent restructures and condenses the observation log, combining related items and removing superseded information.
“The way that you’re sort of compressing these messages over time is you’re actually just sort of getting messages, and then you have an agent sort of say, ‘OK, so what are the key things to remember from this set of messages?’” Bhagwat said. “You kind of compress it, and then you get in another 30,000 tokens, and you compress that.”
The format is text-based, not structured objects. No vector databases or graph databases required.
Stable context windows cut token costs up to 10x
The economics of observational memory come from prompt caching. Anthropic, OpenAI, and other providers reduce token costs by 4-10x for cached prompts versus those that are uncached. Most memory systems can’t take advantage of this because they change the prompt every turn by injecting dynamically retrieved context, which invalidates the cache. For production teams, that instability translates directly into unpredictable cost curves and harder-to-budget agent workloads.
Observational memory keeps the context stable. The observation block is append-only until reflection runs, which means the system prompt and existing observations form a consistent prefix that can be cached across many turns. Messages keep getting appended to the raw history block until the 30,000 token threshold hits. Every turn before that is a full cache hit.
When observation runs, messages are replaced with new observations appended to the existing observation block. The observation prefix stays consistent, so the system still gets a partial cache hit. Only during reflection (which runs infrequently) is the entire cache invalidated.
The average context window size for Mastra’s LongMemEval benchmark run was around 30,000 tokens, far smaller than the full conversation history would require.
Why this differs from traditional compaction
Most coding agents use compaction to manage long context. Compaction lets the context window fill all the way up, then compresses the entire history into a summary when it’s about to overflow. The agent continues, the window fills again, and the process repeats.
Compaction produces documentation-style summaries. It captures the gist of what happened but loses specific events, decisions and details. The compression happens in large batches, which makes each pass computationally expensive. That works for human readability, but it often strips out the specific decisions and tool interactions agents need to act consistently over time.
The Observer, on the other hand, runs more frequently, processing smaller chunks. Instead of summarizing the conversation, it produces an event-based decision log — a structured list of dated, prioritized observations about what specifically happened. Each observation cycle handles less context and compresses it more efficiently.
The log never gets summarized into a blob. Even during reflection, the Reflector reorganizes and condenses the observations to find connections and drop redundant data. But the event-based structure persists. The result reads like a log of decisions and actions, not documentation.
Enterprise use cases: Long-running agent conversations
Mastra’s customers span several categories. Some build in-app chatbots for CMS platforms like Sanity or Contentful. Others create AI SRE systems that help engineering teams triage alerts. Document processing agents handle paperwork for traditional businesses moving toward automation.
What these use cases share is the need for long-running conversations that maintain context across weeks or months. An agent embedded in a content management system needs to remember that three weeks ago the user asked for a specific report format. An SRE agent needs to track which alerts were investigated and what decisions were made.
“One of the big goals for 2025 and 2026 has been building an agent inside their web app,” Bhagwat said about B2B SaaS companies. “That agent needs to be able to remember that, like, three weeks ago, you asked me about this thing, or you said you wanted a report on this kind of content type, or views segmented by this metric.”
In those scenarios, memory stops being an optimization and becomes a product requirement — users notice immediately when agents forget prior decisions or preferences.
Observational memory keeps months of conversation history present and accessible. The agent can respond while remembering the full context, without requiring the user to re-explain preferences or previous decisions.
The system shipped as part of Mastra 1.0 and is available now. The team released plug-ins this week for LangChain, Vercel’s AI SDK, and other frameworks, enabling developers to use observational memory outside the Mastra ecosystem.
What it means for production AI systems
Observational memory offers a different architectural approach than the vector database and RAG pipelines that dominate current implementations. The simpler architecture (text-based, no specialized databases) makes it easier to debug and maintain. The stable context window enables aggressive caching that cuts costs. The benchmark performance suggests that the approach can work at scale.
For enterprise teams evaluating memory approaches, the key questions are:
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How much context do your agents need to maintain across sessions?
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What’s your tolerance for lossy compression versus full-corpus search?
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Do you need the dynamic retrieval that RAG provides, or would stable context work better?
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Are your agents tool-heavy, generating large amounts of output that needs compression?
The answers determine whether observational memory fits your use case. Bhagwat positions memory as one of the top primitives needed for high-performing agents, alongside tool use, workflow orchestration, observability, and guardrails. For enterprise agents embedded in products, forgetting context between sessions is unacceptable. Users expect agents to remember their preferences, previous decisions and ongoing work.
“The hardest thing for teams building agents is the production, which can take time,” Bhagwat said. “Memory is a really important bit in that, because it’s just jarring if you use any sort of agentic tool and you sort of told it something and then it just kind of forgot it.”
As agents move from experiments to embedded systems of record, how teams design memory may matter as much as which model they choose.
Tech
South Dakota GOP, Governor Get Their Voter Suppression On
from the getting-the-fix-in dept
Because South Dakota governor Larry Rhoden is forever obligated to serve Kristi Noem and Kristi Noem is forever obligated to serve Donald Trump, he and his GOP buddies are making America MAGA again, starting with his home turf.
Non-citizens have never really disrupted voting. But they’re the convenient scapegoat for a party that’s justifiably worried it’s going to lose its majority during the mid-terms. Multiple efforts are being made all over the nation to disenfranchise anyone that’s not part of Trump’s most rabid voting base. Pretending people not allowed to legally vote are somehow flipping elections for the Democratic Party is more than merely obnoxious. It’s actually harming the democratic process.
Here in South Dakota, two laws have been passed in recent weeks with the express purpose of keeping non-white people from showing up to vote. The first, passed at the beginning of this month, allows any rando to claim a person they saw voting shouldn’t be allowed to vote.
Voters in South Dakota will soon be able to challenge other voters’ citizenship.
Republican Gov. Larry Rhoden signed legislation into law last week that authorizes challenges by individuals and election officials.
[…]
State law already allows challenges to a voter’s registration up to the 90th day before an election, if a person is suspected of lacking South Dakota residency, voting in another state or being registered to vote in another state. The new law adds citizenship as a justification for a challenge.
Challenges may be filed by the South Dakota Secretary of State’s Office, the auditor in the county where the voter is registered, or a voter in the same county. The challenge must be in the form of a signed, sworn statement and must include what the law describes as “documented evidence.”
Now, we can all see what the law is. But we all know how it will be applied. State employees with access to voter rolls will raise challenges against anyone with a foreign-sounding last name. While it’s unlikely few citizens will actually file challenges, they’ll certainly feel comfortable accosting anyone standing in line to vote whose skin is darker than their own. Given the inevitability of these responses, it’s easy to see the law accomplishing exactly what it’s supposed to: limit the number of non-white voters at the polls during the mid-terms and beyond.
But that’s not the only suppression effort signed into law this month. There’s also this one, which raises the bar for participating in the democratic process with the obvious intention of limiting participation to the sort of voters the GOP thinks with vote for it:
New voters in South Dakota will have to prove that they are United States citizens in order to cast a ballot in state and local races under a bill signed on Thursday by Gov. Larry Rhoden.
The new law, which does not apply to South Dakotans already on the voter rolls, comes amid a national push by Republicans to tighten voting rules and root out voting by noncitizens, which is already illegal and believed to be rare.
“This bill ensures only citizens vote in state elections, keeping our elections safe and secure,” said Mr. Rhoden, who is seeking election to a full term this year and is facing a crowded Republican primary field.
It’s already illegal in South Dakota to vote if you’re not a citizen. This bill addresses a completely imaginary “problem.” And it forces voters to provide a passport, birth certificate, and other documents proving citizenship before they’re allowed to vote. While it may be easy for many people to present these documents, the simple fact is that they’ve never been asked to do this before, and anyone who’s not aware this law has been passed will be denied the opportunity to vote because the GOP decided to move the goalposts during an election year.
Non-citizens voting in South Dakota has never been an issue. The fact that 273 non-citizens were recently removed from the state’s voting rolls may seem a bit sketchy but there’s a good reason there might be a few hundred non-citizens with voter registrations:
Noncitizens can obtain a driver’s license or state ID if they are lawful permanent residents or have temporary legal status. There’s a part of the driver’s license form that allows an applicant to register to vote. That part says voters must be citizens.
The problem is that this is all on the same form. The voter registration part of the form has a signature line, which many applicants will fill out and sign even if their intention is only to get a drivers license or ID card, especially since it appears before the final signature block for the entire application.

If applicants are not asked to affirmatively state their intention to register to vote (as the Department of Public Safety employees ask now, along with asking applicants to write “vote” on the form to signal their affirmation), their applications might be processed, along with the voter registration applicants didn’t realize they enabling.
The Secretary of State’s office (the office that’s supposed to be reviewing voter registrations for eligibility) threw the Department of Public Safety under the bus:
Rachel Soulek, director of the Division of Elections in the Secretary of State’s Office, placed blame on the department in her response to South Dakota Searchlight questions about the situation.
“These non U.S. citizens had marked ‘no’ to the citizenship question on their driver’s license application but were incorrectly processed as U.S. citizens due to human error by the Department of Public Safety,” Soulek wrote.
That’s not what happened. Their ID applications were processed and the Soulek’s department failed to catch the inadvertent errors. And it doesn’t really even matter who’s at fault because despite the errors, this is still a non-issue.
Soulek said only one of the 273 noncitizens had ever cast a ballot. That was during the 2016 general election.
A handful of clerical errors that resulted in a single illegal vote in the past decade cannot be a rational basis for a new law. And there’s a good chance the sole vote was made in error, rather than maliciously. After all, if the state told this person they could vote, who were they to question that determination?
This is nothing more than state governments stepping up to do what Trump can’t. His SAVE Act is stalled and lots of last-minute gerrymandering at the behest of the president is tied up in court. His loyalists are doing what they can to make his perverted dreams a reality in states that are most likely to lean Republican in the first place, which makes all of this as pointless as it is stupid. But the underlying threat to democracy remains, ever propelled forward by the people who claim to love America the most.
Filed Under: immigration, larry rhoden, racism, south dakota, trump administration, voter fraud, voter suppression
Tech
Meta and YouTube lost landmark social media trials. That’s bad for free speech.
In Los Angeles, jurors awarded $6 million to a young woman who alleged that Instagram and YouTube had damaged her mental health. A day earlier, a jury in Santa Fe ruled that Meta had designed its social media platforms in a manner that harmed minors — and ordered the company to pay $375 million in recompense.
These decisions constituted a breakthrough for a legal movement that sees social media companies as the new “Big Tobacco” — an industry that knowingly peddles harmful and addictive products. And it was a triumph for advocates of “child online safety,” who believe that social media is corrosive to minors’ psychological well-being. With thousands of similar lawsuits pending, the California and New Mexico verdicts could prove to be transformative precedents.
Yet the decisions have also raised alarm bells for many free speech advocates. To organizations like FIRE — and civil libertarian writers like Reason’s Elizabeth Nolan Brown — these decisions will do more to undermine free expression online than to safeguard young people’s mental well-being.
To better understand — and interrogate — this perspective, I spoke with Nolan Brown. We discussed how the recent verdicts could open the door to broader censorship, the evidence for social media’s psychological harms, and whether parents can sufficiently protect their kids from problematic internet use without the government’s help. Our conversation has been edited for clarity and concision.
You’ve written that these verdicts are “a very bad omen for the open internet and free speech.” How so?
One key protection for online speech is Section 230 of the Federal Communications Decency Act, which prevents online platforms from being held liable for speech they host but don’t create.
What we’re seeing in these cases is an attempt to get around Section 230 by recharacterizing speech issues as “product liability” issues. Instead of saying, “We’re going after platforms for hosting harmful speech,” the plaintiffs are saying, “We’re going after them for negligent product design.”
In other words, the choices that social media companies make about how to curate their feeds or encourage engagement.
Right. Some of the things they complained about were “endless scroll” (where you keep going down and the feed doesn’t stop at the end of a page), recommendation algorithms that promote content that a user is more likely to engage with, and beauty filters.
But ultimately, if you look at what they’re actually going after, it comes down to speech. When you talk about TikTok or YouTube being so engaging that it’s “addictive,” you’re talking about content: No matter how TikTok’s algorithm is designed, it wouldn’t be compelling to people if the content wasn’t compelling.
Similarly, in the California case, the plaintiff argued that Meta allowing beauty filters on images was a negligent product design, since they promote unrealistic beauty standards, which caused her to develop body image issues.
But that really just comes back to speech: The choice to use a filter is something that individual users do to express themselves. Providing those tools for users is a form of speech.
But aren’t many of these product design choices content-neutral? A defender of these verdicts might argue: Social media companies are manipulating minors into compulsively using their platforms, in a manner that’s bad for their mental health. And they’re doing this, in part, through push notifications, autoplaying videos, and endlessly scrolling feeds. So, why can’t we legally restrict their use of those features — without constraining the kinds of speech they’re allowed to platform?
Some people will say, “Why don’t we limit notifications — or kick people off after an hour — if they’re minors?” But in order to implement any set of rules or product design choices just for young people, these platforms would need to have a foolproof way of knowing who is a minor and who is an adult.
And that means age verification procedures, where they’re either checking everyone’s government-issued ID, or they’re using biometric data — or something else that requires everyone to submit identification before they can speak anywhere on the internet.
And that creates a lot of problems. It makes people’s data more vulnerable to identity theft, hackers, and scammers. It also means that your identity is tied to everything you do online. And that can be dangerous, especially for people who are talking about sensitive issues or protesting the government. The ability to speak and organize online anonymously is very important.
What if the product design restrictions applied to adults and minors alike? If we barred social media companies from issuing push notifications for everyone, that would avoid the age verification issue, right?
Many platforms give people the tools to do these things already. You can turn autoplay off. You can have a chronological feed. You can tailor your settings so that you don’t have these features.
If we’re saying, “Why can’t the government mandate these options?” I think that’s a very slippery slope. You might think, “Okay, who cares about push notifications? Why can’t the government just mandate that they not do push notifications?” But the rationale for that gets us into much broader territory.
It’s effectively saying: Since some people will have a problem with this, the government must micromanage the way that the product is made. Yet people can use all sorts of products in a problematic way: Fitness regimes, streaming services, food. And we’re not saying like, okay, the government gets to step in and tell these companies exactly how to do business in the way that would be least harmful to people. And that attitude is particularly dangerous when we’re talking about products involving speech.
A skeptic might argue that the slope here isn’t actually that slippery. After all, the government has already shown that it can enact targeted, content-neutral restrictions on speech without triggering a cascade of censorship.
For example, since 1990, there have been limits on the amount of advertising that can air during children’s programming in a given hour — and also a requirement that ads and content be clearly separated. Those measures are arguably more intrusive on speech than, say, banning autoplay of videos on a social media platform. And yet, the Children’s Television Act of 1990 didn’t lead to any really sweeping constraints on First Amendment rights.
I just think it makes a big difference if you’re talking about restricting speech for minors and restricting it for adults. And what you were just mentioning were restrictions that would apply to everybody.
Beyond the First Amendment issues, you’ve expressed some skepticism about the specific causal claims made by plaintiffs in these cases: Specifically, that social media caused their mental health difficulties. Yet many social psychologists — most prominently Jonathan Haidt — have argued that these platforms are corrosive to children’s psychological being. So, why do you think the allegations here are overstated?
In the California case specifically, this young woman is alleging that, because she was on social media since she was very young, she developed mental health issues. But there was a lot of testimony showing that there were many other things going wrong in her life. She was exposed to domestic violence. She had troubles with her parents, troubles at school.
So the idea that social media directly caused her difficulties — rather than these life stressors that are well-known to cause harm — I think that’s kind of suspect.
And I think you see this problem in the broader research on social media’s mental health impacts. There’s often a correlation between depressive symptoms and heavy social media use because people who are having a difficult time at home and at school — people who are socially isolated — tend to use social media more than people in better circumstances.
How much do your views on the regulation of social media hinge on skepticism about the actual harms of these platforms? If we acquired evidence that there really were major impacts here — that autoplay and beauty filters were dramatically worsening kids’ mental health — would you support legal restrictions on these features? Or would First Amendment considerations override public health concerns, irrespective of the evidence?
The strength of the evidence is important for guiding the decision-making of individuals, parents, families, communities, and school districts. But even if we knew that beauty filters caused a lot of harm, the government still would not be justified in banning them, since they are avenues for speech. Plenty of people are not harmed by them.
There are so many things that harm some people, but that are useful to others. And I don’t think the existence of problematic use justifies banning those things for everyone.
I think talk of social media “addiction” can be unhelpful on this front. That language suggests that this is something that’s automatically harmful for everyone. And that just isn’t the case. Plenty of people use social media in a healthy way, in the same way that countless people can drink alcohol without it harming them, or eat a bag of chips without bingeing on them.
I think it’s the same way with social media. This is a technology that can harm some people, particularly those who already have psychological issues.
But it isn’t this addictive substance or a poison where you can’t even be exposed to it, or else. I think that view imbues smartphones with an almost mystical quality.
There are many cases, though, where we choose to heavily regulate a substance or practice — not because it harms everyone who engages with it — but rather, because it imposes massive harms on a minority of problem users. Gambling and alcohol are two examples. But even with opioids, many people can pop some pills and never develop a dependency. Yet some end up addicted and dying of overdoses. And for that reason, we heavily restrict access to opioids.
So, I feel like the question here might be less about whether social media is bad for everyone than whether it has truly large harms for problem users.
I think there are people who talk about it the way you do. But others describe social media as if it’s something that people are powerless against. But yes, I don’t think we have strong evidence that this is harmful in the way that addictive substances are. In fact, I think the evidence is really mixed. Some studies suggest that moderate smartphone use is actually correlated with better mental health outcomes.
You argue that, instead of seeking government restrictions on social media, parents should exercise more responsibility over their kids’ use of smartphones and apps.
Many parents argue that their capacity to monitor their children’s social media use is really limited and that they lack the tools to protect their kids from the harmful effects of these platforms. What would you say to them?
I think this is straightforward with very young children. Like, why is a 6-year-old having unfettered alone time on a digital device? In the California case, the plaintiff was using social media as a very young child. And at that age, parents definitely have control over what their kids do and see online; you can control whether your kid has access to a smartphone. With adolescents, there are areas where tech companies are working with parents. We’ve seen more parental controls being introduced in recent years. We’ve seen Meta roll out specific accounts for minors that have some restrictions on them. We’ve seen things like the introduction of phones that allow basic texting but not certain apps. So, I think private solutions are possible here. I think we can address people’s legitimate concerns without having the government infringe on free expression.
Tech
Apple expands iOS 18 updates to more iPhones to block DarkSword attacks
Apple has now made it possible for more iPhones still running iOS 18 to receive security updates that protect against the actively exploited DarkSword exploit kit.
“We enabled the availability of iOS 18.7.7 for more devices on April 1, 2026, so users with Automatic Updates turned on can automatically receive important security protections from web attacks called DarkSword,” reads a note in today’s iOS 18.7.7 security update changelog.
“The fixes associated with the DarkSword exploit first shipped in 2025.”
In March, researchers at Lookout, iVerify, and Google Threat Intelligence revealed a new “DarkSword” exploit kit that targeted iPhones running iOS 18.4 through 18.7.
The six vulnerabilities used by the DarkSword exploit kit are tracked as CVE-2025-31277, CVE-2025-43529, CVE-2026-20700, CVE-2025-14174, CVE-2025-43510, and CVE-2025-43520.
While iOS exploits have typically been used in highly targeted spyware campaigns, this iOS exploit kit was used much more widely, including by Turkish commercial surveillance vendor PARS Defense, a threat actor tracked as UNC6748, and a suspected Russian espionage group tracked as UNC6353.
In these attacks, GTIG observed three separate information-stealing malware families deployed on victims’ devices: a highly aggressive JavaScript infostealer named GhostBlade, the GhostKnife backdoor, and the GhostSaber JavaScript malware, which can execute code and steal data.
Since July 2025, with the release of iOS 18.6, Apple has been steadily fixing the flaws as they are disclosed in security updates pushed out to compatible devices.

Source: GTIG
However, by late 2025, Apple stopped offering iOS 18 updates to newer devices capable of running the newer iOS 26.
For those who decided not to upgrade and stay on iOS 18, availability to the security updates became limited, with newer devices no longer receiving patches for DarkSword vulnerabilities released in 2026.
Since then, only a small number of devices remained able to receive iOS 18 updates, and the last 18.7.6 update was offered only to iPhone XS, iPhone XS Max, and iPhone XR devices.
To make matters worse, a researcher released the DarkSword exploit kit on GitHub last month, making it accessible to other threat actors who wanted to target older iPhones.
Today, Apple has released iOS 18.7.7 to make it available to more devices that want to stay on the older operating system while remaining protected from the latest threats.
Devices eligible to receive the new update now include iPhone XR, iPhone XS, iPhone XS Max, iPhone 11 (all models), iPhone SE (2nd generation), iPhone 12 (all models), iPhone 13 (all models), iPhone SE (3rd generation), iPhone 14 (all models), iPhone 15 (all models), iPhone 16 (all models), iPhone 16e, iPad mini (5th generation – A17 Pro), iPad (7th generation – A16), iPad Air (3rd – 5th generation), iPad Air 11-inch (M2 – M3), iPad Air 13-inch (M2 – M3), iPad Pro 11-inch (1st generation – M4), iPad Pro 12.9-inch (3rd – 6th generation), and iPad Pro 13-inch (M4).
iPhone users still running iOS 18 with Automatic Updates enabled will now receive the latest version and protections against the DarkSword exploit kit.
Tech
Yeo’s lays off 25 staff in S’pore, moves can manufacturing operations to M’sia
It will consolidate production in its Johor and Selangor plants
Yeo Hiap Seng (Yeo’s) announced today (Mar 31) that it will retrench 25 employees at its Senoko facility in Singapore as it shifts its can manufacturing operations to Malaysia.
The company explained that consolidating production in its Johor and Selangor plants will help “optimise capacity utilisation and strengthen overall manufacturing efficiency” across its network.
Despite the move, Yeo’s Senoko site will remain its headquarters, as well as a hub for cross-border logistics and limited-scale production.
Yeo’s added that it will support affected staff through job placement services, career guidance, and counselling, and may offer them opportunities in Malaysia where suitable roles are available.
The company said it worked closely with the Food, Drinks and Allied Workers Union to ensure that the retrenchment package and transition support “reflect appreciation for the contributions of affected staff”.
The compensation packages will follow guidelines from Singapore’s Ministry of Manpower and will be based on each worker’s salary and length of service.
“These benefits will be commensurate with each employee’s salary and years of service.”
This is not the first round of layoffs for Yeo’s.
In Dec 2024, it cut 25 jobs after Oatly shut its Singapore plant—roles that had been created specifically for that production. Earlier, in 2022, the company retrenched 32 employees, citing shifts in consumer behaviour, retail challenges, and rising costs.
Financially, the SGX-listed firm reported a net profit of S$21.1 million for the year ending Dec 31, 2025, a significant increase from S$6.9 million the year before.
However, both overall revenue and core food and beverage revenue declined, which the company attributed to softer consumer spending and stronger competition in key markets.
- Read other articles we’ve written on Singaporean businesses here.
Featured Image Credit: Google Street View/ Yeo’s via Facebook
Tech
UFC-Que Choisir Takes Ubisoft To French Court Over the Crew Shutdown
Longtime Slashdot reader Elektroschock writes: When Ubisoft pulled the plug on The Crew’s servers without warning, players were left with a worthless game they’d already paid for. Now, consumer watchdog UFC-Que Choisir is fighting back, demanding gamers’ right to play regardless of publisher whims. Supported by the “Stop Killing Games” movement, this landmark case challenges unfair terms before the Creteil Judicial Court (Val-de-Marne near Paris), and aims to protect players from disappearing games. The lawsuit that UFC-Que Choisir filed against Ubisoft on Tuesday alleges that the video game publisher “misled consumers about the permanence of their purchase and imposed abusive contractual clauses stripping players of ownership rights,” reports Reuters.
Tech
Intuit’s AI agents hit 85% repeat usage. The secret was keeping humans involved
When Intuit shipped AI agents to 3 million customers, 85% came back. The reason, according to the company’s EVP and GM: combining AI with human expertise turned out to matter more than anyone expected — not less.
Marianna Tessel, the financial software company’s EVP and GM, calls this AI-HI combination a “massive ask” from its customers, noting that it provides another level of confidence and trust.
“One of the things we learned that has been fascinating is really the combination of human intelligence and artificial intelligence,” Tessel said in a new VB Beyond the Pilot podcast. “Sometimes it’s the combination of AI and HI that gives you better results.”
Chatbots alone aren’t the answer
Intuit — the parent company of QuickBooks, TurboTax, MailChimp and other widely-used financial products — was one of the first major enterprises to go all in on generative AI with its GenOS platform last June (long before fears of the “SaaSpocalypse” had SaaS companies scrambling to rethink their strategies).
Quickly, though, the company recognized that chatbots alone weren’t the answer in enterprise environments, and pivoted to what it now calls Intuit Intelligence. The dashboard-like platform features specialized AI agents for sales, tax, payroll, accounting and project management that users can interact with using natural language to gain insights on their data, automate tasks, and generate reports.
Customers report invoices are being paid 90% in full and five days faster, and that manual work has been reduced by 30%. AI agents help close books, categorize transactions, run payroll, automate invoice reminders and surface discrepancies.
For instance, one Intuit customer uncovered fraud after interacting with AI agents and asking questions about amounts that didn’t add up. “In the beginning it was like, ‘Is that an error? And as he dug in, he discovered very significant fraud,” Tessel said.
Why humans are still in the loop
Still, Intuit operates on the principle that humans are “always accessible,” Tessel said. Platforms are built in a way that users can ask questions of a human expert when they’re not getting what they need from the AI agent, or want a human to bounce ideas off of.
“I’m not talking about product experts,” Tessel said. “I’m talking about an actual accounting expert or tax expert or payroll expert.”
The platform has also been built to suggest human involvement in “high stakes” decision-making scenarios. AI goes to a certain level, then human experts review and categorize the rest. This provides a level of confidence, according to Tessel.
“We actually believe it becomes more needed and more powerful at the right moments,” she said. “The expert still provides things that are unique.”
The next step is giving customers the tools to perform next-gen tasks like vibe coding — but with simple architectures to reduce the burden for customers. “What we’re testing is this idea of, you can actually do coding without realizing that that’s what you are doing,” Tessel said.
For example, a merchant running a flower shop wants to ensure that they have the right amount of inventory in stock for Mother’s Day. They can vibe code an agent that analyzes previous years’ sales and creates purchase orders where stock is low. That agent could then be instructed to automatically perform that task for future Mother’s Days and other big holidays.
Some users will be more sophisticated and want the ability to dive deeper into the technology. “But some just want to express what they want to have happen,” Tessel said. “Because all they want to do is run their business.”
Listen to the full podcast to hear about:
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Why first-party data can create a “moat” for SaaS companies.
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Why showing AI’s logic matters more than a polished interface.
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Why 600,000 data points per customer changes what AI can tell you about your business.
You can also listen and subscribe to Beyond the Pilot on Spotify, Apple or wherever you get your podcasts.
Tech
I Tell My Students Writing Is Hard. I Still Ask Them to Do It Anyway.
My life has changed so much since my time as a Voices of Change fellow during the 2023 school year. As I wrote in my final essay of the fellowship, the beautiful, imperfect school I loved and helped build had closed. With the support of my fellowship editor, Cobretti Williams, I applied and was admitted to the Creative Writing Workshop at the University of New Orleans, where I am taking graduate classes and teaching a freshman English composition course.
In deciding what to write as a reflection on my time since the fellowship, I started three different essays and hated all of them. I did a lot of cursing, went on a couple of brooding walks and wondered why I agreed to write this in the first place. During the similarly maddening process of designing the syllabus for the first college course I taught, I took a break to write my students a letter. Here is an excerpt:
Before we start this course together, it’s important for me to name something foundational to how I approach teaching it: Writing is hard for everyone. I love writing and I believe that, if I keep practicing, I can become great at it… and I still hate doing it a lot of the time. This is why writing is so important. Almost everything we want is on the other side of making ourselves do things we don’t want to do. When we sit down to write, whether we want to or not, and we keep writing when we hit that initial point where we want to stop, and continue when those moments arise again and again like waves, we are getting vital practice. This skill, ignoring the complacent you, the you that would rather do the thing tomorrow, or tomorrow’s tomorrow, and doing the thing now instead is an act of becoming the you that has the things you want. Like anything else, this becomes easier the more you do it.
This excerpt reminds me that writing is much more difficult than most of the things we do in a world that commodifies ease and comfort, upholds them as desirable and makes us feel we are entitled to them while simultaneously less and less able to tolerate their lack.
There is a common misconception that my students come to me with that manifests most often in the statement “I don’t know what to write.” They think this means they are not ready to begin, because they believe that writing is putting what you already know onto paper. I understand why this misconception exists. So often in life, we only see finished products. The published novel, the final cut, the social media post depicting the outcome and not the process and the struggle. It’s easy to think that everyone else has things figured out, that what you see is how something was from the beginning. This can trick us into believing that if something isn’t good right away, we should abandon it. Drafting insists that we try before we feel sure, finish something even if it is not yet “good.” Revision insists that what we have can be something different, something better, and teaches us to hold multiple things in our heads at the same time. Throughout this process, we gain clarity.
Each time we give or receive feedback and assess whether it moves us closer to or further from our vision, we get better at articulating what we want and closer to achieving it. When teachers and students do this work together and commit to improvement, even when we both have moments of uncertainty about what to do next, we are practicing true collaboration. We both grow. What a way to become more skillful at building the world we want.
It is a strange time to be devoting so much of my life to writing, to be telling students that they should care about writing too. Just this week, an article came out detailing pervasive, undisclosed AI use to grade and give feedback to student writing in some New Orleans schools. A study conducted in May of 2025 showed that 84 percent of high school students used generative AI to complete their school work. I understand intimately the overwhelm of educators and students, and the temporary relief that cognitive offloading with AI can provide.
However, what we lose in the long term by not engaging deeply in the writing process, the practice of giving and receiving feedback, of watching revision unfold, is so much greater than the gains we feel in accepting AI’s “help” in our moments of overwhelm. What world are we building when we delegate the human work of communication through writing to machines? We would do better to engage in a process of re-evaluating our priorities, taking on fewer assignments for longer and working collaboratively as educators and administrators to redesign curricula and systems so that teachers have the capacity to get to know their students through repeated contact with their written work.
Sometimes, it feels like we are already living in a completely different world from the one in which I grew up and was educated. Luckily, these times, despite how often folks like to say they are not, are precedented. In these times, I have been turning to Black women writers like Toni Morrison, Toni Cade Bambara, Audre Lorde and June Jordan for guidance, and they all insist writing only becomes more urgent the more dire the times. In facing what Toni Morrison described in 2004 as “a burgeoning ménage a trois of political interests, corporate interests and military interests” working to “literally annihilate an inhabitable, humane future,” I have been especially steeled by Audre Lorde’s words, “In this way alone we can survive, by taking part in a process of life that is creative and continuing, that is growth.”
In the face of a world that would automate us right out of existence, I intend for us to survive, and so I insist we write.
Tech
Textise is the internet’s cleanest secret, and it makes everything readable
Let’s be honest, the modern web is… a mess. Pop-ups, autoplay videos, cookie banners, ads everywhere. In fact, sometimes it feels like actually reading something online is the hardest part. And that’s exactly where Textise comes in.

Think of it as a “strip everything away” button for the internet. Textise is a simple web tool that converts any webpage into a clean, text-only version, removing ads, images, scripts, and all the extra clutter. What you’re left with is just the content: no distractions, no loading bloat, no nonsense. It’s fast, lightweight, and honestly feels like going back to a simpler version of the web.
Why does it feel so refreshing?
Modern websites are built for engagement, not readability. That means heavy layouts, tracking scripts, and design choices that often get in the way of just consuming information. Tools like Textise flip that on its head by streamlining content into plain text, making it easier to read and more accessible. In fact, for long articles or research-heavy pieces, it can genuinely feel like a productivity boost: less scrolling, fewer distractions, and quicker load times.

You can even tweak how Textise looks and behaves, from fonts and text size to background colors and link styles. It’s a surprisingly flexible tool, letting you tailor the reading experience exactly the way you like it. Of course, you lose things along the way. Images, videos, interactive elements — all gone. But that’s also what makes it work. Textise isn’t trying to enhance the web; it’s trying to simplify it to the bare minimum. And weirdly enough, that’s exactly why it feels so useful in 2026.
So… who is this for? Well, pretty much anyone who reads a lot online. Whether it’s articles, blogs, or even cluttered news pages, Textise makes everything feel cleaner and easier to digest. It’s especially handy for people who just want to focus on content without distractions.
Same idea, very different vibe
If this all sounds familiar, that’s because most modern browsers already have a built-in Reader Mode, like the one in Safari or Chrome. These features clean up a webpage by removing ads, menus, and distractions, and reformat the article into a more readable layout with better fonts and spacing.

But here’s where Textise feels different. Reader modes are still design-aware, meaning they keep images and basic formatting and rely on the browser to figure out what the “main article” is. Textise, on the other hand, goes full savage mode. It strips everything down to raw text, no images, no styling, no fluff. In a way, Reader Mode is like switching to a clean reading theme… while Textise is like opening the internet in Notepad. And honestly, depending on the day (or how chaotic the webpage is), both have their moment.
And maybe that’s the best part about it. In a web that’s constantly trying to grab attention, Textise just quietly steps back and lets you focus. Sometimes, all it takes to make the internet better… is less internet.
Tech
Battery Tester Outperforms Cheaper Options
Batteries are notoriously difficult pieces of technology to deal with reliably. They often need specific temperatures, charge rates, can’t tolerate physical shocks or damage, and can fail catastrophically if all of their finicky needs aren’t met. And, adding insult to injury, for many chemistries, the voltage does not correlate to state of charge in meaningful ways. Battery testers take many efforts to mitigate these challenges, but often miss the mark for those who need high fidelity in their measurements. For that reason, [LiamTronix] built their own.
The main problem with the cheaper battery testers, at least for [LiamTronix]’s use cases, is that he has plenty of batteries that are too large to practically test on the low-current devices, or which have internal battery management systems (BMS) which can’t connect to these testers. The first circuit he built to help solve these issues is based on a shunt resistor, which lets a smaller IC chip monitor a much larger current by looking at voltage drop across a resistor with a small resistance value. The Pi uses a Python script which monitors the current draw over the course of the test and outputs the result on a handy graph.
This circuit worked well enough for smaller batteries, but for his larger batteries like the 72V one he built for his electric tractor, these methods could draw far too much power to be safe. So from there he built a much more robust circuit which uses four MOSFETs as part of four constant current sources to sink and measure the current from the battery. A Pi Zero monitors the voltage and current from the battery, and also turns on some fans pointed at the MOSFETs’ heat sink to keep them from overheating. The system can be configured to work for different batteries and different current draw rates, making it much more capable than anything off the shelf.
Tech
AI has a different kind of bias problem, but it’s an often repeated one
AI bias is usually talked about in terms of algorithms: skewed datasets, flawed outputs, and stereotypes baked into models. But new research suggests there’s another, more subtle problem about who gets to use AI in the first place. According to a recent report by Lean In, women are less likely than men to use AI tools at work, and even when they do, they’re less likely to get recognition or support for it.

The numbers paint a clear picture. Men are more likely to use AI regularly (33% vs 27%), more likely to have ever used it at work, and significantly more likely to be encouraged by managers to adopt it. And it’s not just about access, but also about perception. Women are more likely to worry about the risks of AI, question its accuracy, and even fear being judged for using it, including concerns that it might be seen as “cheating.”
Why this matters more than it seems
Chances are, this gap could compound fast. AI is quickly becoming a core workplace skill, and early adoption often translates into better opportunities. If one group is consistently using it less, or getting less credit for it, that gap can grow into real career disadvantages over time. And this isn’t happening in isolation. Broader research already shows women are underrepresented in tech and AI roles, meaning they’re not just using these tools less, but they’re also less involved in building them.

What makes this interesting is how familiar it feels. This isn’t a new kind of bias; it’s an old one, just showing up in a new space. The same patterns seen in workplaces for decades, with less recognition, less encouragement, and more scrutiny, are now playing out in how AI is adopted and used.
Same bias, new tech?
As AI becomes a core workplace skill, even small gaps like this can snowball into missed opportunities, slower career growth, and less representation in shaping the tech itself. Because if the people using AI aren’t equally represented… the future it builds won’t be either.
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