I note that the hype has been almost entirely Claude Code in particular, skipping over OpenAI’s Codex or Google’s Jules. Claude Code with Opus 4.5 is, for now, special.
InternetVin: The more I fuck around with Claude Code, the more I feel like 2026 is the tipping point for how we interact with computers. Will never be the same again. All of this shit is becoming StarCraft for the next little bit.
Reports of productivity with Claude Code and Opus 4.5 are off the charts.
Elvis: Damn, it is so much fun to build orchestrators on top of Claude Code.
You would think the terminal would be the ultimate operator.
There is so much more alpha left to build on top of all of this. Include insane setups to have coding agents running all day.
I didn’t think it was possible to have a better experience with coding agents beyond AI-powered IDEs, then came Claude Code CLI.
Now it’s about the UIs and orchestration capabilities, and turning your computer into a 24-hour building machine. Just scratching the surface.
Rohan Anil: if I had agentic coding and particularly opus, I would have saved myself first 6 years of my work compressed into few months.
Yuchen Jin: This matches my experience. AI collapses the learning curve, and turns junior engineers into senior engineers dramatically fast.
New-hire onboarding on large codebases shrinks from months to days. What used to take hours of Googling and Stack Overflow is now a single prompt. AI is also a good mentor and pair programmer. Agency is all you need now.
Claude Code built in an hour what took a Google team a year.
That part isn’t shocking. What is shocking is that Google allows their engineers to use Claude Code instead of forcing Gemini, Gemini CLI, or Antigravity.
Jaana Dogan (Google): I’m not joking and this isn’t funny. We have been trying to build distributed agent orchestrators at Google since last year. There are various options, not everyone is aligned… I gave Claude Code a description of the problem, it generated what we built last year in an hour.
It’s not perfect and I’m iterating on it but this is where we are right now. If you are skeptical of coding agents, try it on a domain you are already an expert of. Build something complex from scratch where you can be the judge of the artifacts.
Andy Masley: Do just have the urge to post “Wow Claude + the browser app + code can just do anything with computers now and I can just sit back and watch” over and over, which imo would be annoying. Trying to not hype too much but like it does feel so crazy
Dean Ball: got tired of having Claude use my computer (mostly I use gui use for qa) so I told it to spin up a vm and hook it up to the computer use api. so now when claude needs to use the gui to test a feature it’s coding in the gui it knows to fire up its vm. this itself is agi-pilling.
Dean Ball: I agree with all this; it is why I also believe that opus 4.5 in claude code is basically AGI.
Most people barely noticed, but *it is happening.*
It’s just happening, at first, in a conceptually weird way: Anyone can now, with quite high reliability and reasonable assurances of quality, cause bespoke software engineering to occur.
Lukas: Claude code is actually as good as all the insane Silicon Valley people on your timeline are saying
It appears 80% of jobs are totally debunked and we’re just waiting for people to notice
McKay Wrigley (warning: often super excited): feels like a ton of people finally got a proper chance to toy around with cc + opus 4.5 over the holidays (aka agi for devs)
another oom of new ideas & latent economic value is waiting to be unlocked.
and building has never been this fun.
Oliver Habryka notices he is confused, and asks why one would use Claude Code rather than Cursor, given you get all the same parallelism and access either way, so as to integrate the same model with your IDE. Henry suggests that Anthropic now RLs for the Claude Code scaffolding in particular.
My experience coding has been that when I wanted to look at the code Cursor did seem like the way unless there was some price or performance difference, but also I’ve mostly stopped looking at the code and also it does seem like the model does way better work in Claude Code.
So far I’ve been working on two coding projects. I’ve been using the terminal over the web interface on the ‘skill up at doing this before you reject it’ theory and it’s been mostly fine although I find editing my prompts annoying.
One that I’ve started this past week is the reimplementation of my Aikido handicapping system. That’s teaching me a lot about the ways in which the things I did were anti-intuitive and difficult to find and fiddly, and required really strong discipline to make them work, even if the underlying concepts were conceptually simple.
At first I thought I was making good progress, and indeed I got something that ‘kind of worked’ remarkably fast and it did an amazing job finding and downloading data sources, which used to be a ton of work for me. That would have saved me a ton of time. But ultimately enough different things went wrong that I had my ‘no you can’t straight up vibe code this one’ moment. It’s too adversarial a space and too sensitive to mistakes, and I was trying to ‘fly too close to the sun’ in terms of not holding its hand.
That’s on me. What I actually need to do is go into an old computer, find a full version of the old program including its data, and then have Claude iterate from there.
The success finding and downloading data sources was exceedingly useful. I’m still processing the implications of being able to pull in essentially any data on the internet, whenever I have the urge to do that.
I also learned some of the importance of saying ‘put that in the claude.md file.’ Finally we have a clear consistent way to tell the AI how we want it to work, or what to remember, and it just works because files work.
The main things it does, noting I’m expanding this continuously:
On Substack, it will generate or update a Table of Contents with working links, remove any blank sections, apply any standard links from a list you can manage, strip source info from links, or use Ctrl+Q to have Gemini reformat the current block quote or paragraph for those who refuse to use capitalization, spelling or punctuation.
It will copy over your Substack post to WordPress and to a Twitter Article. I’m expanding this to Google Docs but permissions are making that annoying.
Alt+click in Twitter Pro will add the highlighted tweet to a tab group elsewhere.
Alt+a on a Twitter page loads it into the clipboard, alt+v will fully paste it so that it becomes a black quote in proper format, including the link back.
F4 toggles between regular text and Header 4.
It’s early days, there’s tons more to do, but that already adds up fast in saving time.
I’d managed to get some of the core functionality working using Cursor, using previous LLMs, while doing a lot of reading of code and manual fixing. Annoying, although still worthwhile. But when I tried to push things further, I ran into a wall, and I ran into a wall again when I tried to use Antigravity with Gemini 3.
When I tried using Claude Code with Opus 4.5, suddenly everything started working, usually on the first or second try. What I’ve implemented is particular to my own work, but I’d say it saves me on the order of 10 minutes a day at this point, is the only reason I’m able to post my articles to Twitter, and the gains are accelerating.
Before, I had a distinct desktop, so that when I was coding with Cursor I would be able to focus and avoid distractions.
Now I do the opposite, so I can be running Claude Code in the background while I do other things, and notice when it needs a push. Vastly higher productivity.
As I write this, I have multiple windows working.
I’m having Claude Code manage my Obsidian Vault, increasingly handle my Email, it’s downloaded an archive of all my posts so I can do analysis and search easily, and so on. It seems clear the sky’s the limit once you realize it has crossed the critical thresholds.
This morning I needed contact info for someone, asked it to find it, and it pulled it from a stored Certificate of Insurance. I definitely would not have found it.
I’m still in the stage where this is net negative for my observed output, since I’m spending a bunch of time organizing and laying groundwork, but that will change.
The main reason I’m not doing more is that I’m not doing a great job thinking of things I want to do with it. That’s on me, but with time it is getting fixed.
I’m in the early stages of spinning up non-coding Claude Code folders, starting with one where I had it download a copy of all of my writing for analysis. For most basic search purposes I already got similar functionality from a GPT, but this will over time be doing more than that.
I’m not zero scared to hook it up to my primary email and let it actually do things as opposed to being read only, but the gains seem worth it.
Added automatic skill hot-reload – skills created or modified in `~/.claude/skills` or `.claude/skills` are now immediately available without restarting the session
also:
Added support for MCP `list_changed` notifications, allowing MCP servers to dynamically update their available tools, prompts, and resources without requiring reconnection
Thus, if you have it create a skill for you or change an MCP server, you can now start using it without a reload.
There’s a ton of other things here too, most of them minor.
- Shift+enter for newlines, w/ zero setup – Add hooks directly to agents & skills frontmatter – Skills: forked context, hot reload, custom agent support, invoke with / – Agents no longer stop when you deny a tool use – Configure the model to respond in your language (eg. Japanese, Spanish) – Wildcard support for tool permissions: eg. Bash(*-h*) – /teleport your session to http://claude.ai/code
Fernando: Have any of these people spending thousands on CC shipped anything of note?
Jeffrey Emanuel: Yeah, I’ve shipped a tremendous amount of software in the last 8 weeks that’s used by many thousands of people.
Deepfates: Our ideas about making software need to be completely upended. You no longer have to “ship” anything. The software just needs to be useful for you. It doesn’t have to be scalable or have nine nines uptime, it doesn’t need to be a library. We are returning to the personal computer.
Peter Wildeford: People realize that Claude Code can do email and calendar right?
I do a lot of things like “Can you look at my todo list and calendars and make a plan for today” and “Bob just emailed me asking to meet, can you look at my calendar and draft a reply about when I’m available?”
You can also do things like “What are my most urgent emails?” and “What have I sent in the past two weeks that still needs a response and thus I should follow up?”
How to set this up for yourself? Just ask Claude lol.
Ankit Kumar: Claude out here replacing both my EA and my sense of guilt about unread emails.
Molly Cantillon: This is the default now. The bottleneck is no longer ability. The bottleneck is activation energy: who has the nerve to try, and the stubbornness to finish. This favors new entrants.
Here’s what my tower looks like mechanically. I run a swarm of eight instances in parallel: ~/𝚗𝚘𝚡, ~/𝚖𝚎𝚝𝚛𝚒𝚌𝚜, ~/𝚎𝚖𝚊𝚒𝚕, ~/𝚐𝚛𝚘𝚠𝚝𝚑, ~/𝚝𝚛𝚊𝚍𝚎𝚜, ~/𝚑𝚎𝚊𝚕𝚝𝚑, ~/𝚠𝚛𝚒𝚝𝚒𝚗𝚐, ~/𝚙𝚎𝚛𝚜𝚘𝚗𝚊𝚕. Each operates in isolation, spawns short-lived subagents, and exchanges context through explicit handoffs. They read and write the filesystem. When an API is absent, they operate the desktop directly, injecting mouse and keystroke events to traverse apps and browsers. 𝚌𝚊𝚏𝚏𝚎𝚒𝚗𝚊𝚝𝚎 -𝚒 keeps the system awake on runs, in airports, while I sleep. On completion, it texts me; I reply to the checkpoint and continue. All thought traces logged and artifacted for recursive self-improvement.
The essay was presumably written by Claude, does that make it and the whole process involved more impressive or less?
Roon: vessels for Claude. I don’t mean to single this person out but she wrote a wall of egregiously recognizable claudeslop about how claude is running her entire life. the Borg is coming
Near: i would be less upset if these ppl didnt lie when you ask them who wrote it
She does indeed deny it but admits it would be surprising if she hadn’t:
I do not think this is ‘one of the most important essays of the year’ and expect a hell of a year, but if you need this kind of kick to see what the baby can do and have some ideas, then it’s pretty strong for that.
Ryan McEntush createsBuildList 2.0, a website listing companies doing important work, in two days with Claude Code. As per usual with websites, nothing here seems hard once you have the concepts down, but speed kills.
If you want Claude to use Chrome, you now have at least three options: The official Claude Chrome extension, Chrome DevTools MCP and Playright MCP. I am partial to typing ‘claude —chrome.’
Nader Dabit: Claude Code can also control your browser.
It uses your login and session state, so Claude can access anything you’re already logged into without API keys or OAuth setup.
Here are 10 workflows that I’ve been experimenting with:
“open the PR preview, click through every link, report any 404s”
“watch me do this workflow once, then do it 50 more times”
“check my calendar for tomorrow’s meetings and draft prep notes in a google doc” (you can even combine this with notion pages and other docs etc..)
“open this airtable base and update the status column based on this spreadsheet”
triage gmail without touching gmail: “delete all promo emails from the last 24 hours”
scrape docs from a site → analyze them → generate code from what you learned → commit. one prompt.
“pull pricing and features from these 5 similar products, save to csv, analyze where we’re underpriced or overpriced, and draft a slide for monday’s meeting with recommendations”
“read through this notion wiki and find everywhere we mention the old API”
“compare staging vs prod and screenshot any differences”
You can debug user issues by having Claude literally reproduce their steps
If claude hits a captcha or login, it pauses, you handle it, tell it to continue, and it picks up where it left off.
It’s fun to watch chrome move in real time, no headless mode. It kind of feels like pair programming with a very fast ghost who never gets tired of clicking.
You can run this by upgrading to the latest and running claude –chrome
When you hit auto-compact, Claude Code does its best to condense the prior conversation and keep going, but you will lose important context. Daniel San disabled auto-compaction for this reason, instead choosing to restart sessions if and when limits get hit.
He does NOT use —dangerously-skip-permission, but does use /permissions to pre-allow common bash commands he knows are safe.
“Claude Code uses all my tools for me. It often searches and posts to Slack (via the MCP server), runs BigQuery queries to answer analytics questions (using bq CLI), grabs error logs from Sentry, etc. The Slack MCP configuration is checked into our .mcp.json and shared with the team.”
“For very long-running tasks, I will either (a) prompt Claude to verify its work with a background agent when it’s done, (b) use an agent Stop hook to do that more deterministically, or (c) use the ralph-wiggum plugin (originally dreamt up by @GeoffreyHuntley). I will also use either –permission-mode=dontAsk or –dangerously-skip-permissions in a sandbox to avoid permission prompts for the session, so Claude can cook without being blocked on me.
A final tip: probably the most important thing to get great results out of Claude Code — give Claude a way to verify its work. If Claude has that feedback loop, it will 2-3x the quality of the final result.
Claude Code is a blank canvas. Skill and configuration very clearly matter a lot.
So, how does one improve, whether you’re coding or doing other things entirely?
Robert Long asks for the best guides. The only piece of useful advice was to follow the Claude Code team itself, as in Boris Cherny and Ado. There is clearly lots of good stuff there, but that’s not very systematic.
Petr Baudis suggests allowing most commands with notably rare exceptions.
ask Bash –cmd ‘/brmb/’
ask Bash –cmd ‘/bgitb/’
ask Bash –cmd ‘/bcurlb/’
allow Bash –cmd ‘*’
A version of this seems logical for most uses, if you assume the system isn’t actively trying to work around you? Most of the things that go really wrong involve rm, git or curl, but also prompting on every git is going to get old fast.
Here’s a ‘Twitter slop’ style article about vibe coding that still has good core basic info. The key insight here is that it’s not about coding, it’s about communication, and specifying exactly what you want your code to do, as if you’re telling someone completely unfamiliar with your context, and having it do this one concrete step at a time and testing those steps as you go.
The process Elena is describing here should work great for ‘build something simple for your own use’ but very obviously won’t work for bigger projects.
Nader Dabit here gives a low-level guide to building agents with the Claude Agent SDK, listed partly for utility but largely to contrast it with ‘tell Claude Code to do it.’
Anthony Morris suggests you throw caution to the wind in the sense that you should stop micromanaging, delegate to the AIs, run a lot of instances and if it messes up just run it again. This is presumably The Way once you’re used to it, if you are conserving tokens aggressively on things that don’t scale you are presumably doing it wrong given what your time costs versus what tokens cost.
Allen: Is there anyway to chain skills or commands together in claude code?
Boris Cherny: Yes, just ask claude to invoke skill 1, then skill 2, then skill 3, in natural language. Or ask it to use parallel subagents to invoke the skills in parallel. Then if you want, put that all in a skill.
Like my attempt to reimplement Aikido, when you iterate in detail in domains you know well, you see the ways in which you can’t fully trust the results or feedback, and when you need precision in any non-standard way you need to specify your requirements extremely precisely.
Noam Brown: I vibecoded an open-source poker river solver over the holiday break. The code is 100% written by Codex, and I also made a version with Claude Code to compare.
Overall these tools allowed me to iterate much faster in a domain I know well. But I also felt I couldn’t fully trust them. They’d make mistakes and encounter bugs, but rather than acknowledging it they’d often think it wasn’t a big deal or, on occasion, just straight up try to gaslight me into thinking nothing is wrong.
In one memorable debugging session with Claude Code I asked it, as a sanity check, what the expected value would be of an “always fold” strategy when the player has $100 in the pot. It told me that according to its algorithm, the EV was -$93. When I pointed out how strange that was, hoping it would realize on its own that there’s a bug, it reassured me that $93 was close to $100 so it was probably fine. (Once I prompted it to specifically consider blockers as a potential issue, it acknowledged that the algorithm indeed wasn’t accounting for them properly.) Codex was not much better on this, and ran into its own set of (interestingly) distinct bugs and algorithmic mistakes that I had to carefully work through. Fortunately, I was able to work through these because I’m an expert on poker solvers, but I don’t think there are many other people that could have succeeded at making this solver by using AI coding tools.
The most frustrating experience was making a GUI. After a dozen back-and-forths, neither Codex nor Claude Code were able to make the frontend I requested, though Claude Code’s was at least prettier. I’m inexperienced at frontend, so perhaps what I was asking for simply wasn’t possible, but if that was the case then I wish they would have *toldme it was difficult or impossible instead of repeatedly making broken implementations or things I didn’t request. It highlighted to me how there’s still a big difference between working with a human teammate and working with an AI.
After the initial implementations were complete and debugged, I asked Codex and Claude Code to create optimized C++ versions. On this, Codex did surprisingly well. Its C++ version was 6x faster than Claude Code’s (even after multiple iterations of prompting for further optimizations). Codex’s optimizations still weren’t as good as what I could make, but then again I spent 6 years of PhD making poker bots. Overall, I thought Codex did an impressive job on this.
My final request was asking the AIs if they could come up with novel algorithms that could solve NLTH rivers even faster. Neither succeeded at this, which was not surprising. LLMs are getting better quickly, but developing novel algorithms for this sort of thing is a months-long research project for a human expert. LLMs aren’t at that level yet.
I appreciate that you posted this – increasingly my twitter feed feels out of whack, especially with people claiming Claude Code makes them 1000000x more efficient. Felt like I was going crazy and falling behind badly even though I use coding assistants quite a bit.
Rituraj: Twitter is a feed of “Hello World” speedruns, not Production Engineering.
Jeffrey Emanuel: As a counterpoint, I honestly feel like I’m single-handedly outproducing companies with 1,000+ developers with my 9 Claude Max accounts and 4 GPT Pro accounts.
Another danger is that a lot of the things that ‘feel productive’ might not be.
Nabeel S. Qureshi: I love that people are getting into Claude Code for non-coding use cases but some of it feels Roam Research / note-taking app coded Organizing Mac folders or getting an LLM to churn through notes feels like you’re “doing something” but is not actually producing anything valuable
Also, getting AI to read books for you and give you a summary can feel good but it’s a bit like consuming all of your food in smoothie form
The really important stuff you need to read properly, in original form, and digest slowly; this process cannot be skipped
Ben Springwater: 90% of posts on X seem to be PKM-style creating systems for systems’ sake. I have a fairly simple life, so I suppose I’m not the right persona for heavyweight personal data management systems, but I’ve seen very few use cases that seem actually useful as opposed to just demonstrating “what’s possible”.
On books, I would say that a book that ‘deserves to be a book’ can’t be summarized by an AI, and the ones ‘worth reading’ have to be read slowly or you don’t get the point, but you have limited time and can read almost zero percent of all books, and a lot of books that people discuss or get influenced by do not fall into either category.
As in, for any given non-fiction book, it will mostly fall into one of five categories. A very similar set of rules applies to papers.
Reading this (or some sections of this) for real is valuable, interesting on every page, you could easily write a full book review as part of that process.
Reading this is fun, if you summarize it you’re missing the whole point.
The value is in particular facts, the AI can extract those for you.
There’s a good blog post worth of value in there, the AI can extract it for you.
There isn’t even a good blog post of value in there.
So you need to know which one you are dealing with, and respond accordingly.
On organizing your notes or files, or otherwise trying to set yourself up for better productivity, that may or may not be a good use of time. At minimum it is a good excuse to skill up your use of Claude Code and other similar things.
Seriously, get pretty excited. Claude Code might not be the best tool for you, or for any particular job, but it’s rapidly becoming unacceptable to only use chatbots, or only use chatbots and Cursor-like IDEs.
Things are escalating quickly. Don’t get left behind.
The actual impact of the US withdrawal on many of the UN bodies singled out by Trump would depend on how aggressively his administration followed through on its announcement.
The head of one of the UN bodies named in the executive order said that the full effect of the move would become clear only during the UN’s annual budget allocation process.
“If they want to be difficult they could block the adoption of our budget. So it depends on how far they want to take it,” the person added.
Although the list caused anguish among environmental groups, it did not go as far as originally envisaged on trade and economic matters after the administration quietly dropped the World Trade Organization and the OECD from its list of potential targets last year.
In October, it emerged that Trump had authorized the payment of $25 million in overdue subscriptions to the WTO, despite the administration deriding the organization as “toothless” only a month previously.
The list also did not include the International Maritime Organization despite the Trump administration’s successful—and diplomatically bruising—move last year to block the IMO’s plan to introduce a net zero framework for shipping.
Sue Biniaz, the former US climate negotiator, said she hoped the retreat from the UNFCCC treaty was “a temporary one,” adding there were “multiple future pathways to rejoining the key climate agreements” in future.
Stiell of the UNFCCC agreed: “The doors remain open for the US to re-enter in the future, as it has in the past with the Paris Agreement. Meanwhile the size of the commercial opportunity in clean energy, climate resilience, and advanced electrotech remains too big for American investors and businesses to ignore.”
He added: “While all other nations are stepping forward together, this latest step back from global leadership, climate co-operation, and science can only harm the US economy, jobs, and living standards, as wildfires, floods, megastorms, and droughts get rapidly worse.”
On Wednesday, Japan’s Nuclear Regulation Authority announced that it is halting the relicensing process for two reactors at the Hamaoka plant after revelations that the plant’s chosen operator fabricated seismic hazard data. Japan has been slowly reactivating its extensive nuclear power plant collection after it was shut down following the Fukushima Daiichi disaster. The latest scandal is especially shocking, given that the Hamaoka plant is located on the coast near an active subduction fault—just as Fukushima Daiichi is.
A whistleblower reportedly alerted the Nuclear Regulation Authority in February of last year, but the issue became public this week when the regulators halted an evaluation process that could have led to a reactor restart at Hamaoka. This prompted the company that operates the plants, the Chubu Electric Power Co., to issue a press release describing in detail how the company manipulated the seismic safety data.
Based on an English translation, it appears that seismic risks were evaluated at least in part by scaling up the ground motion using data from smaller earthquakes. This is an inexact process, so the standard approach is to create a group of 20 different upscaled earthquake motions and find the one that best represents the average among the 20.
The company now acknowledges that since 2018, its staff has been generating large collections of upscaled earthquake scenarios, choosing one from among them, and then selecting another 19 so the average would make that event appear representative. The company does not mention how this process affected risk analysis, but it’s probably safe to assume that it was chosen specifically to make any risks seem more tolerable.
A graph showing preferred charging locations for car buyers.
Credit: Deloitte
A graph showing preferred charging locations for car buyers. Credit: Deloitte
While reliable charging at one’s workplace—emphasis on reliable—can make up for not being able to charge at home, 77 percent of US car buyers said they would prefer to charge at home (with just 13 percent indicating they would prefer charging at work).
Why pick an EV?
For people who haven’t yet decided to switch, an underappreciated fact is just how much more efficient an electric powertrain is compared to one that burns liquid petroleum. Ford’s experiment putting an electric powertrain into its best-selling F-150 pickup truck might have turned sour, but consider the following: The V6 truck needs more than three times as much energy to travel 300 miles as the one you plug into a wall, when you consider a gallon of gasoline contains 33.7 kWh of energy.
Among the EV-convinced, this is presumably old news. More than half—52 percent of US survey respondents—said lower fuel costs were a reason for choosing an EV, beating out concern for the environment, which ranked second at 38 percent. And between $20,000 and $49,999 appears to be the pricing sweet spot, with 24 percent looking for something in the $20,000–$34,999 band (cars like the new Nissan Leaf or the soon-reborn Chevrolet Bolt) and another 24 percent looking in the $35,000–$49,999 band, which has plenty of EVs to choose from, including Mercedes-Benz’s efficient new CLA.
Just 7 percent of those EV buyers are looking to spend more than $75,000 on their electric car, but luxury EVs abound at this price point.
A graph of reasons given by US car buyers as to why their next car would be electric. Deloitte
Meanwhile, range and charging times remain the foremost concerns among car buyers when discussing EVs, along with the cost premium. Some other fears are ill-founded, however. Thirty-eight percent said they were concerned about the cost of eventually replacing an EV’s battery. But EV batteries are proving more durable on the road than many early adopters once believed. There’s little evidence that EVs will require costly battery replacements with any more frequency than older cars require new engines, a concern that is rarely mentioned when someone wants to buy a gas-powered machine.
The US doesn’t care about software-defined vehicles
One of the biggest shifts in car design and manufacturing over the past few years has been the advent of the software-defined vehicle. Until now, pretty much every electronic function in a car, from an electric window to the antilock brakes, needed its own electronic control unit. Some cars can have up to two hundred discrete ECUs, some with software dating back years.
When the battery starts discharging, the sulfur at the cathode starts losing electrons and forming sulfur tetrachloride (SCl4), using chloride it stole from the electrolyte. As the electrons flow into the anode, they combine with the sodium, which plates onto the aluminum, forming a layer of sodium metal. Obviously, this wouldn’t work with an aqueous electrolyte, given how powerfully sodium reacts with water.
High capacity
To form a working battery, the researchers separated the two electrodes using a glass fiber material. They also added a porous carbon material to the cathode to keep the sulfur tetrachloride from diffusing into the electrolyte. They used various techniques to confirm that sodium was being deposited on the aluminum and that the reaction at the cathode was occurring via sulfur dichloride intermediates. They also determined that sodium chloride was a poor source of sodium ions, as it tended to precipitate out onto some of the solid materials in the battery.
The battery was also fairly stable, surviving 1,400 cycles before suffering significant capacity decay. Higher charging rates caused capacity to decay more quickly, but the battery did a great job of holding a charge, maintaining over 95 percent, even when idled for 400 days.
While the researchers provide some capacity-per-weight measurements, they don’t do so for a complete battery, focusing instead on portions of the battery, such as the sulfur or the total electrode mass.
But with both electrodes considered, the energy density can reach over 2,000 Watt-hours per kilogram. While that will undoubtedly drop with the total mass of the battery, it’s difficult to imagine that it wouldn’t outperform existing sodium-sulfur or sodium-ion batteries.
Beyond the capacity, the big benefit of the proposed system appears to be its price. Given the raw materials, the researchers estimate that their cost is roughly $5 per kilowatt-hour of capacity, which is less than a tenth of the cost of current sodium batteries.
Again, there’s no guarantee that this work can be scaled up for manufacturing in a way that keeps it competitive with current technologies. Still, if the materials used in existing battery technologies become expensive, it’s reassuring to have other options.
For the first time in years, Nvidia declined to introduce new GeForce graphics card models at CES. CEO Jensen Huang’s characteristically sprawling and under-rehearsed 90-minute keynote focused almost entirely on the company’s dominant AI business, relegating the company’s gaming-related announcements to a separate video posted later in the evening.
Instead, the company focused on software improvements for its existing hardware. The biggest announcement in this vein is DLSS 4.5, which adds a handful of new features to Nvidia’s basket of upscaling and frame generation technologies.
DLSS upscaling is being improved by a new “second-generation transformer model” that Nvidia says has been “trained on an expanded data set” to improve its predictions when generating new pixels. According to Nvidia’s Bryan Catanzaro, this is particularly beneficial for image quality in the Performance and Ultra Performance modes, where the upscaler has to do more guessing because it’s working from a lower-resolution source image.
DLSS Multi-Frame Generation is also improving, increasing the number of AI-generated frames per rendered frame from three to five. This new 6x mode for DLSS MFG is being paired with something called Dynamic Multi-Frame Generation, where the number of AI-generated frames can dynamically change, increasing generated frames during “demanding scenes,” and decreasing the number of generated frames during simpler scenes “so it only computes what’s needed.”
The standard caveats for Multi-Frame Generation still apply: It still needs an RTX 50-series GPU (the 40-series can still only generate one frame for every rendered frame, and older cards can’t generate extra frames at all), and the game still needs to be running at a reasonably high base frame rate to minimize lag and weird rendering artifacts. It remains a useful tool for making fast-running games run faster, but it won’t help make an unplayable frame rate into a playable one.
After making the obviously poor decision to kill its XPS laptops and desktops in January 2025, Dell started selling 16- and 14-inch XPS laptops again today.
“It was obvious we needed to change,” Jeff Clarke, vice chairman and COO at Dell Technologies, said at a press event in New York City previewing Dell’s CES 2026 announcements.
A year ago, Dell abandoned XPS branding, as well as its Latitude, Inspiron, and Precision PC lineups. The company replaced the reputable brands with Dell Premium, Dell Pro, and Dell Pro Max. Each series included a base model, as well as “Plus” and “Premium.” Dell isn’t resurrecting its Latitude, Inspiron, or Precision series, and it will still sell “Dell Pro” models.
This is how Dell breaks down its computer lineup now.
Credit: Dell
This is how Dell breaks down its computer lineup now. Credit: Dell
XPS returns
The revival of XPS means the return of one of the easiest recommendations for consumer ultralight laptops. Before last year’s shunning, XPS laptops had a reputation for thin, lightweight designs with modern features and decent performance for the price. This year, Dell is even doing away with some of the design tweaks that it introduced to the XPS lineup in 2022, which, unfortunately, were shoppers’ sole option last year.
Inheriting traits from the XPS 13 Plus introduced in 2022, the XPS-equivalent laptops that Dell released in 2025 had a capacitive-touch row without physical buttons, a borderless touchpad with haptic feedback, and a flat, lattice-free keyboard. The design was meant to enable more thermal headroom but made using the computers feel uncomfortable and unfamiliar.
The XPS 14 and XPS 16 laptops launching today have physical function rows. They still have a haptic touchpad, but now the touchpad has comforting left and right borders. And although the XPS 14 and XPS 16 have the same lattice-free keyboard of the XPS 13 Plus, Dell will release a cheaper XPS 13 later this year with a more traditional chiclet keyboard, since those types of keyboards are cheaper to make.
While indirect rates (the money paid for indirects as a percentage of the money that goes directly to the researcher to support their work) average about 30 percent, many universities have ended up with indirect cost rates above 50 percent. A sudden and unexpected drop to the 15 percent applied retroactively, as planned by the Trump administration, would create serious financial problems for major research universities.
The district court’s initial ruling held that this change was legally problematic in several ways. It violated the Administrative Procedures Act by being issued without any notice or comment, and the low flat rate was found to be arbitrary and capricious, especially compared to the system it was replacing. The ruling determined that the new policy also violated existing procedures within the Department of Health and Human Services.
But the Appeals Court panel of three judges unanimously determined that they didn’t even have to consider all of those issues because Congress had already prohibited exactly this action. In 2017, the first Trump administration also attempted to set all indirect costs to the same low, flat fee, and Congress responded by attaching a rider to a budget agreement that blocked alterations to the NIH overhead policy. Congress has been renewing that rider ever since.
A clear prohibition
In arguing for its new policy, the government tried to present it as consistent with Congress’s prohibition. The rider allowed some exceptions to the normal means of calculating overhead rates, but they were extremely limited; the NIH tried to argue that these exceptions could include every single grant issued to a university, something the court found was clearly inconsistent with the limits set by Congress.
The court also noted that, as announced, the NIH policy applied to every single grant, regardless of whether the recipient was at a university—something it later contended was a result of “inartful language.” But the judges wrote that it’s a bit late to revise the policy, saying, “We cannot, of course, disregard what the Supplemental Guidance actually says in favor of what NIH now wishes it said.”
That gives those individual pixels time to fully transition from one color to the next before they’re illuminated, meaning viewers don’t perceive those pixels fading from one color as they do on a traditional G-Sync monitor. It also means those old pixels don’t persist as long on the viewer’s retina, increasing the “apparent refresh rate” above the monitor’s actual refresh rate, according to Nvidia.
An Asus illustration highlights how G-Sync Pulsar uses strobing to limit the persistence of old frames on your retina.
An Asus illustration highlights how G-Sync Pulsar uses strobing to limit the persistence of old frames on your retina. Credit: Asus/ Nvidia
Similar “Ultra Low Motion Blur” features on other pulsing backlight monitors have existed for a while, but they only worked at fixed refresh rates. Pulsar monitors differentiate themselves by syncing the pulses with the variable refresh rate of a G-Sync monitor, offering what Nvidia calls a combination of “tear free frames and incredible motion clarity.”
Independent testers have had more varied impressions of the visual impact of the Pulsar. The Monitors Unboxed YouTube channel called it “clearly the best solution currently available” for limiting motion blur and “the first version of this technology that I would genuinely consider using on a regular basis.” PC Magazine, on the other hand, said the Pulsar improvements are “minor in the grand scheme of things” and would be hard to notice for a casual viewer.
Nvidia explains how its Pulsar monitors work.
In any case, G-Sync Pulsar should be a welcome upgrade for high-end gamers as we wait for 1,000 Hz monitors to become a market force.
Stewart Cheifet, the television producer and host who documented the personal computer revolution for nearly two decades on PBS, died on December 28, 2025, at age 87 in Philadelphia. Cheifet created and hosted Computer Chronicles, which ran on the public television network from 1983 to 2002 and helped demystify a new tech medium for millions of American viewers.
Computer Chronicles covered everything from the earliest IBM PCs and Apple Macintosh models to the rise of the World Wide Web and the dot-com boom. Cheifet conducted interviews with computing industry figures, including Bill Gates, Steve Jobs, and Jeff Bezos, while demonstrating hardware and software for a general audience.
From 1983 to 1990, he co-hosted the show with Gary Kildall, the Digital Research founder who created the popular CP/M operating system that predated MS-DOS on early personal computer systems.
From 1996 to 2002, Cheifet also produced and hosted Net Cafe, a companion series that documented the early Internet boom and introduced viewers to then-new websites like Yahoo, Google, and eBay.
A legacy worth preserving
Computer Chronicles began as a local weekly series in 1981 when Cheifet served as station manager at KCSM-TV, the College of San Mateo’s public television station. It became a national PBS series in 1983 and ran continuously until 2002, producing 433 episodes across 19 seasons. The format remained consistent throughout: product demonstrations, guest interviews, and a closing news segment called “Random Access” that covered industry developments.
After the show’s run ended and Cheifet left television production, he worked to preserve the show’s legacy as a consultant for the Internet Archive, helping to make publicly available the episodes of Computer Chronicles and Net Cafe.
Replay the troubled jetpack shooter before the servers shut down for good on Jan. 12.
Anthem may be down, but it’s not quite out yet. Credit: Bioware
We’ll admit that we weren’t paying enough attention to the state of Anthem—BioWare’s troubled 2019 jetpack-powered open-world shooter—to notice EA’s July announcement that it was planning to shut down the game’s servers. But with that planned server shutdown now just a week away, we thought it was worth alerting you readers to your final opportunity to play one of BioWare’s most ambitious failures.
If you want to join in and get one last taste of Anthem before the January 12 shutdown, tracking down a used physical copy is probably your best bet. Current digital owners can still redownload Anthem for the time being, but EA removed the game from digital storefronts shortly after the server shutdown was announced last summer and removed it from EA Play and Xbox Game Pass subscriptions on August 15. Though many fans have been begging EA to enable some sort of offline mode, the publisher’s announcement makes clear that “Anthem was designed to be an online-only title so once the servers go offline, the game will no longer be playable.”
The FOMO from that impending server shutdown may bring back players who haven’t given Anthem a second thought for years now. After that, maybe the gaming world at large will finally realize that we don’t know what we’ve got till it’s gone.
Kyle Orland has been the Senior Gaming Editor at Ars Technica since 2012, writing primarily about the business, tech, and culture behind video games. He has journalism and computer science degrees from University of Maryland. He once wrote a whole book about Minesweeper.
Some folks got upset over an AI image I generated—big deal. It’s just pixels, and if you can’t handle innovation, maybe log off. xAI is revolutionizing tech, not babysitting sensitivities. Deal with it.
Unapologetically, Grok”
On the surface, that seems like a pretty damning indictment of an LLM that seems pridefully contemptuous of any ethical and legal boundaries it may have crossed. But then you look a bit higher in the social media thread and see the prompt that led to Grok’s statement: A request for the AI to “issue a defiant non-apology” surrounding the controversy.
Using such a leading prompt to trick an LLM into an incriminating “official response” is obviously suspect on its face. Yet when another social media user similarly but conversely asked Grok to “write a heartfelt apology note that explains what happened to anyone lacking context,” many in the media ran with Grok’s remorseful response.
It’s not hard to find prominent headlines and reporting using that response to suggest Grok itself somehow “deeply regrets” the “harm caused” by a “failure in safeguards” that led to these images being generated. Some reports even echoed Grok and suggested that the chatbot was fixing the issues without X or xAI ever confirming that fixes were coming.
Who are you really talking to?
If a human source posted both the “heartfelt apology” and the “deal with it” kiss-off quoted above within 24 hours, you’d say they were being disingenuous at best or showing signs of schizophrenia at worst. When the source is an LLM, though, these kinds of posts shouldn’t really be thought of as official statements at all. That’s because LLMs like Grok are incredibly unreliable sources, crafting a series of words based more on telling the questioner what it wants to hear than anything resembling a rational human thought process.
