California creates $3,500 rebate for new electric vehicle buyers
There's a separate $1,750 rebate for used EVs, but both rebates have a price cap.
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There's a separate $1,750 rebate for used EVs, but both rebates have a price cap.
Startle the snake by striking the grass. — The 36 Stratagems, Stomp the Grass to Scare the...
Why build something? And what if nobody ends up using it? There are good answers to the first one. You build because you need a thing that doesn't exist yet. You build to see if you can, the technical challenge, the "is this even possible?" You build to impress someone, or just because you think it'll make people's day a little less annoying. All of those are real reasons, and at different points, I told myself most of them. Then, a few days ago, late in the day, at the end of a coding session, five months into the project, I asked myself those two questions back-to-back. And for the first time, I couldn't answer the second one. Zeri worked. Every feature did what it was supposed to do. Both processes handshake cleanly, a variable set in one context showing up in another a second later, the TUI rendering exactly as I'd pictured it. And I sat there and couldn't come up with one honest sentence explaining why anyone would actually download it. That gap, between something built well and something that has a reason to exist, turned out to be the most useful thing this whole project taught me. So I'm shipping it anyway, and I'll tell you why. What I built Zeri is a TUI multi-language REPL. You launch it, pick a language, Python , JavaScript (with Bun ), Ruby , or LuaJIT , and you get an interactive session in your terminal. You can switch languages mid-session, share variables across them, save and reload your work, manage snippets, and talk to a local LLM through a command running on Ollama . The feature list isn't the interesting part, though. The interesting part is what's underneath. Two processes, one app Zeri is split into two processes: a headless engine written in C++23 and a TUI frontend built in Go using Bubble Tea and Lip Gloss . The engine does all the evaluation, state, and runtime coordination. The frontend does rendering, input, and everything the user actually sees and touches. They talk to each other over a custom binary IPC protocol that I built from sc
As the US war on Iran sent gas prices soaring, American car buyers flocked to electric vehicles - and in particular hybrids. After a sluggish winter and fall, EV sales rebounded in the second quarter of 2026, with automakers posting some of their best numbers since the elimination of the federal EV tax credit last […]
Today, I’m talking with Xinzhou Wu, who is the head of automotive at Nvidia. Nvidia is obviously in the news constantly because of the AI boom — it’s one of the most valuable companies in the world, because the AI industry can’t get enough of the company’s GPUs. But Nvidia is also a key supplier […]
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Waze is getting an AI makeover. Google is integrating its flagship AI assistant, Gemini, into the driving app with the goal of letting users personalize their trips a little more. Of the four new updates, only two are being described as involving Gemini. Waze says its updating its conversation reporting feature, first introduced in 2024, […]
36 Stratagems Series · Arc 2 (Against Enemy, #7-#12) Wrap-Up This article has 7 sections: I. The Stranger at the Door II. Full Interview Transcript III. The Reveal IV. Data · Character Map · Four Insights V. A Note VI. Arc 3 (#13-#18) Preview VII. Acknowledgments I. The Stranger at the Door On the evening of July 12th, I was staring blankly at the page for #12, Borrow Corpse, Return Soul . Twelve stories done. The 36 Stratagems series had reached the one-third mark, and Arc 2 (#7-#12) had just wrapped. Outside the window, a typhoon was passing through — howling wind, torrential rain. I didn't look outside. My phone buzzed. Not a message — a meeting invitation. The sender was "Ke Yuan," and the invitation note read: Interview invitation from Deep Lane Weekly , 15 minutes. I paused. I didn't remember scheduling any interview. But the tone, the phrasing — it didn't feel like a prank. I clicked "Accept." Three seconds later, an unfamiliar voice came through the speaker: "Hello, Xu Lingfeng. I'm Ke Yuan, a reporter from Deep Lane Weekly . Recently, a reader recommended your 36 Stratagems series to our editorial team — we read through it and found it really interesting. I'd love to talk with you about how this series came together." Before I could respond — the meeting had already begun. II. Full Interview Transcript What follows is the raw chat log pulled from that meeting. Nothing has been altered except formatting. Reporter: Xu Lingfeng, you've just finished the second arc of the 36 Stratagems series — #7 through #12, six stories in six days, posted back to back. Before we talk numbers, let me ask you something simple: over those six days, was there ever a moment you felt like stopping? Xu: Honestly, no — sometimes I even thought about posting two a day, since I do have a backlog. But I worried they'd cannibalize each other's numbers, so I stuck to one a day. Reporter: You've even considered posting two a day — so you actually do have a backlog. Let me rephrase: instea
The first time a client said yes to a quote without hesitating, I felt sick. This was early on. I'd sent over a rate for a batch of articles, my palms were actually sweaty over the email, and the reply came back in under an hour. "Sounds great, when can you start?" No pushback, no negotiation, nothing. I should have been thrilled. Instead, I sat there doing the math on how much more I could have charged, and I knew, the way you just know sometimes, that I'd priced it too low. His enthusiasm was the tell. That queasy feeling taught me more than any pricing guide ever did. If a client says yes instantly and happily, you were cheap. I've been freelancing for about eight years now, all of it writing and content work, most of it solo from a spare room in my house. I've priced my work a dozen different ways over that stretch, and I've gotten most of them wrong at some point. So here's what I actually believe about pricing, after enough scars to have earned an opinion. Per-word pricing quietly punishes you for getting better I started out charging by the word, like a lot of writers do. Five cents a word, sometimes six if I was feeling brave. It felt safe because it was easy to explain and easy for a client to say yes to. A 1,500-word article costs this much. Clean. Predictable. The problem showed up slowly. The better I got, the worse that model treated me. Early on I'd pad a piece to hit a word count because more words meant more money, which is a genuinely insane thing to be incentivized toward as a writer. Then I spent years learning to cut. Learning that the sharpest version of an article is usually the shortest one that still does the job. And every ounce of that hard-won skill made me poorer, because a tight 900-word piece that took real judgment to shape paid less than a bloated 1,400-word one I could have written half-asleep. Think about how backwards that is. I was being paid the least for the writing I was proudest of. The stuff that took a decade to be able to d
Tokens and DAOs are often presented as simple ideas: issue a token, distribute ownership, let the community vote, and build a decentralized organization. In reality, the technical problems behind tokens and DAOs are much deeper. A token is not only an asset, and a DAO is not only a voting system. Together, they create an economic, governance, security, and coordination layer that must work reliably in a hostile, open environment. The first major problem is token design. Many projects treat token creation as a deployment task, but the real challenge is defining what the token actually controls. Does it represent governance power, protocol revenue, access rights, reputation, staking weight, or all of these at once? When one token is used for too many purposes, the system becomes fragile. For example, a token designed for liquidity may not be suitable for governance, because the most active traders may not be the most aligned decision-makers. Good token architecture should separate economic utility, governance authority, and long-term reputation where possible. The second problem is distribution. A DAO can be decentralized in branding but centralized in practice if token ownership is concentrated among founders, investors, or early insiders. On-chain governance depends heavily on voting power, so distribution directly affects decision quality. Poor distribution creates governance capture, where a small group can control treasury spending, protocol upgrades, or parameter changes. This is not only a social issue; it is a technical design issue. Vesting contracts, delegation systems, quorum rules, voting delay, and proposal thresholds all influence whether governance is resilient or easily manipulated. Another core issue is governance security. DAO voting is not automatically safe just because it happens on-chain. Token voting can be attacked through flash loans, bribery markets, vote buying, low-participation proposals, and governance fatigue. If a malicious proposal pas
You have seen the posts. AI is coming for the junior engineer first. Why hire someone to write code a model can write for free? The career ladder's bottom rung is gone, so start saving your pity for anyone about to graduate into this market. I think the premise is wrong, and it is wrong in a specific, fixable way. Look closely at what these predictions actually describe. Not a junior engineer. A person whose entire job is turning a finished spec into working code. That role is real, and it is shrinking fast, but it was never the same thing as "junior engineer." We just let the two collapse into one job title for forty years because, until recently, spec-to-code translation was the canonical, critical thing a junior had the skill to do. The task and the title are not the same thing. AI is eating the task. It does not follow that it eats the title too, unless we insist on keeping them welded together. So the real question is not "does the junior engineer survive." It is "what do we train a junior engineer to do now that the translation work is cheap." And the honest answer is: not much of what we have been doing. I think we landed on "junior engineers are doomed" for a reason that has nothing to do with whether it is true. It is the easy conclusion. It requires nothing from us. Training a junior into a senior was never straightforward, even in the old world, and figuring out how to do it without the years of tickets we used to lean on is genuinely hard. "They're doomed" lets everyone off the hook. "How do we train juniors into seniors now" does not, but it is the question with a future in it. The first one just has a shrug. The apprenticeship we built no longer exists For as long as I have been in this field, the plan was the same. Hire someone who can code. Hand them small, well-specified tickets. Let them grind through years of execution: bugs, edge cases, code review, the slow accumulation of pattern recognition that eventually turns into judgment. Somewhere around
Take something that is dead and give it new life. — The 36 Stratagems, Borrow a Corpse to Return the Soul Previously on this series: #1: Mark Johnson Walked Into an AI Audit. The Benchmark Had Everything Figured Out — Except the Truth. — Mark was the first protagonist to open the 36 Stratagems series. A former Client Engineering lead laid off after his 12 years of experience were packaged into an AI Skill, he walked into a benchmark audit, found a benchmark that looked clean on paper but was built on fabricated samples, and walked out without arguing — just the data, neatly collected, left on the table. 11 stories later, Mark is back. Mark Johnson walked into the client's Network Operations Center. The first thing he saw was the big screen on the wall. AI monitoring dashboard. Real-time metrics flowing, color gradients smoothing over, a UI design that cost real money. The client's tech lead walked ahead of him, pride in his voice: "Just upgraded last month — all active channels are unified on this platform now." Mark nodded. His eyes went past the screen, to the cable management trays behind the racks. He never stood in front of dashboards for long. Standard infrastructure audit — mid-sized client, decent security rating, not a high-value contract. He took whatever came his way. Couldn't afford to be picky. The audit started at the network layer. He needed the channel inventory, historical logs, configuration change records. A laptop on a temporary desk, a cup of coffee he'd brought himself — pour-over, gone cold, but he wouldn't throw it out. Flipping through the channel inventory, he found one line that didn't look right. #alert-legacy-infra — a Slack channel. Status: muted . Last active config: 14 months ago. "What's this channel for?" he asked. The tech lead glanced at it. "Oh — that's from the last SRE we had. He set it up before the new platform went in. Nobody's maintained it since. We kept it around, just muted it." Mark didn't reply. He wrote the channel ID
Week 5 of my Google Summer of Code journey with CircuitVerse ( June 22nd to June 28th ) is officially in the books. After dealing with a rough sickness last week, I’m happy to say this week was incredibly positive . 🔄 Reconnecting with the Community Since I had to miss last week's sync because I was under the weather, I had to attend the CircuitVerse GSoC Contributors' Meeting this week. It felt so good to reconnect with everyone ! I shared the progress I'd managed to scrape together over the last couple of weeks, and the mentors were incredibly understanding and kind about my slower pace due to being sick. The CircuitVerse community is genuinely unmatched! Everyone is so encouraging, and having that layer of support makes a world of difference. It was also super motivating to hear what the other contributors have been up to. Seeing how much progress everyone has made gave me a massive burst of inspiration to jump right back into development! 🛠️ importCanonical.ts is Completed! Once the meeting was over, I officially finished implementing the entire import pipeline in importCanonical.ts! 🥳 This file does the heavy lifting of taking our clean, deterministic canonical JSON and reconstructing the circuit right back onto the user's canvas. Here is what's packed inside: 🔀 Full Multi-Circuit Support: The import pipeline seamlessly handles projects containing multiple individual circuits. 📐 Smart Subcircuit Dependency Resolution: Just like the export pipeline, the import engine now uses Kahn's Algorithm to figure out the exact sequence the circuits need to be loaded in so that nested dependencies never break. 🛑 What's Missing? (For Now): The import pipeline doesn't validate the incoming JSON file . I am waiting until the canonical format is finalised. Once that's locked in, I will add JSON schema validation in the file. 🚀 The PR Status On the GitHub side of things, the three foundational Pull Requests I opened earlier are still actively under review . One of my mentors gav
When an international recruiter recently asked for my CV, I instinctively started writing it the way many developers do: A chronological list of companies, Programming languages, frameworks, Technical achievements. Then it hit me. I wasn't writing this document for a senior engineer. I was writing it for the recruiter sitting between me and the interview. If the first person reading my CV couldn't immediately understand the value I brought, I might never reach the technical interview at all. Knowing the Receivers So I rewrote it from a different perspective. Instead of simply listing technologies, I described the business context behind my work. 10,000+ emails sent a day (in addition to "Using AWS SES/SQS") 800+ restaurants / POS everyday (in additional "optimised SQL speed"). Cut down waste to 1.3% from 10 ~ 15% Critical updates often in 24 hours. Increased revenue, reduced costs, improved reliability Helped onboarded new clients I still included the languages and frameworks I used, so the CTO can understand, but they became supporting evidence rather than the headline. I also highlighted the moments that demonstrated trust: Delivering critical business updates under tight deadlines, Resolving high-priority production issues, Taking responsibility for systems the business depended on, and Taking initiatives to write a mobile app using my own time. That small shift completely changed how I viewed a CV. It's not a journal of everything I've done, and it's not a technical specification. Its job is to communicate your value clearly to the person reading it, and that person is often a recruiter before it's ever seen by an engineering manager. One lesson I keep coming back to is this: Write for my audience. Outcome (for now) After reviewing the rewritten CV, the recruiter was confident enough to forward it to Tata Consultancy Services for a role. Whether or not that particular opportunity works out, it reinforced an important lesson for me: recruiters need to understand
The café was crowded that evening, but to me, the world had fallen completely silent. An open...
I’m VikingRob—Full-Stack Dev, SaaS Builder, and Solo Survivor. Hello I Just wanted to introduce myself. I’m Robert, but most people know me as VikingRob (thanks to a long red beard and a habit of grinding through hard Jobs with a foul mouth. Down to earth guy I'm a No B.S Person. I’ve been surviving in the trenches of solo entrepreneurship and freelancing for a while now. Lately, the market feels incredibly flooded, and landing solid, consistent work has become a massive mountain to climb. I’ve managed to keep things moving with some passive income from selling front-end and back-end sites I've built, but as anyone with a family knows, "passive" rarely means "enough" when consistency drops. I’m supporting a family of five—including a wife dealing with severe mental health challenges—so the pressure to secure steady, reliable income is incredibly real right now. To adapt, I am shifting my core focus toward offering full-scale services: Custom Website Architecture (End-to-end development) Front-End & Advanced Back-End Integration SaaS Product Development A lot of my heaviest back-end work is locked away under strict NDAs, which makes traditional portfolio-sharing tough, and I don't maintain standard social media accounts. But I know how to build clean, functional, scalable software that drives results. If you're looking to collaborate, need an engineering heavy-lifter for a SaaS project, or just want to swap freelance survival stories, let’s connect! What is everyone else doing to beat the market noise right now?
Better to sacrifice a part to preserve the whole. — The 36 Stratagems, Sacrifice the Plum Tree to...
Note: Google Cloud credits are provided for this project. In this blog post, I want to demonstrate how I use Antigravity CLI to build an image analysis demo using Angular, Firebase Hybrid & On-device Inference Web SDK, and Gemini models. Users upload an image and use a Gemini model to analyze it to generate a few alternative texts, tags, recommendations, and CSS tips to enhance the image quality. When the demo is running on Chrome 148+, the Hybrid & On-device SDK leverages the Prompt API of the on-device Gemini Nano model to perform the image-to-text tasks, and the token usage is 0. When other browsers such as Safari or Firefox executes the same tasks on the demo, the SDK falls back to Cloud AI (Gemini 3.5 Flash model), and the token usage is greater than 0. Next, I will describe how I installed the skills in my Angular project, and registered the Stitch MCP server in the Antigravity CLI to develop the infrastructure, services, and UI design of my demo. 1. Skills I installed grill-with-docs , angular , and firebase skills in my project for the following reasons: grill-with-docs: Conduct a rigid Q&A session to generate a specification for a feature, refactor or a critical fix. AI is responsible for performing a thorough analysis and putting in more effort to generate code to achieve the task. Angular: Provide the best practices of Modern Angular architecture, such as using signals and signal forms. Firebase: Provide the skill for Firebase AI Logic, Firebase Remote, etc. Resources Firebase Hybrid & On-device Image Analysis App Firebase Hybrid & On-device Inference Chrome Built-in Prompt API Stitch Stitch MCP Server grill-with-docs Angular skill Firebase skill
VW's plan calls for half as many models but didn't mention closures or job cuts.
Now it's an arms race between OEMs locking down chips and tuners trying to crack them.