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In November, Apple laid off dozens of sales employees in a rather unexpected move for the tech giant. Apple is the rare tech company that has steered clear of mass layoffs, particularly among its peers in the trillion-dollar club. The layoffs came as a surprise for those who lost their jobs, according to a Bloomberg reportand they impacted some employees who had been with the company for decades. The post-pandemic job market has come to be defined by layoffs, in tech and beyond: A Glassdoor analysis finds that there was a peak in 2023, but layoffs have since continued at a more frequent cadence relative to the years prior. A variety of sectors have been hit hardand prominent employers like Verizon, Starbucks, and UPS have gone through multiple rounds of cuts this year alone, slashing thousands of jobs. But the tech industry has been uniquely reliant on layoffs as companies have gone through periods of overhiring and fluctuating priorities, with the rapid emergence of artificial intelligence now upending the sector. Since 2022, tech employers have laid off upwards of 700,000 workers, according to the tracker Layoffs.fyi. With the exception of Apple, which has conducted a handful of more targeted cuts in recent years, the Big Tech companiesnamely Amazon, Meta, Google, and Microsofthave laid off tens of thousands of employees over the last three years. There are just so many new grads coming out, trying to enter the tech industry, and they feel like the promise of a high-paying job in tech is just not really being fulfilled, says Daniel Zhao, Glassdoors chief economist and director of economic research. All this has led to a challenging environment for tech workers who are seeking new jobs and new graduates who are trying to find their footing. In the last two decades, Big Tech jobs held a certain cachet for millennial knowledge workers who were starting their careers. The sprawling campuses and free food were appealing, of course, but companies like Google also imbued their work with purpose and appeared to guarantee professional success. But as layoffs have roiled the industry, it seems as though the tech jobs that were once hailed as stable and desirable may no longer be a sure bet for workers. Unfortunately, layoffs aren’t really a last resort response anymore, says Brett Coakley, the principal executive coach at career consulting firm Close Cohen. Theyve become more of an annual planning tool. These workers that thought they were insulated are realizing that prestige doesn’t really provide the protection that they’re used to. The dream job has changed For years, these tech companies have promised both generous salaries and job security alongside lavish perks. Between recurring layoffs and strict return to office policies, however, something seems to have shiftedand its not just that the perks have dried up. Many large tech employers hired aggressively during the pandemic, only to turn around and lay off workers not long after. Companies like Amazon forced employees to return to the office five days a weekin some cases requiring that they relocate. The rise of generative AI is also radically reshaping tech companies, with many of them making multi-billion-dollar investments and courting top talent. Computer science graduates are finding it more difficult to land entry level jobsin part because those roles are steadily being automated. Some companies, like Salesforce, have already replaced certain workers with AI, while others have warned that job losses are on the way and that employees need to meet the moment and adopt AI technology. Mark Zuckerberg noted earlier this year that AI could supplant mid-level engineers at Meta, while Amazon CEO Andy Jassy has said employees who become conversant in AI will have high impact and help us reinvent the company. (Whether AI will actually cull jobs at a rapid clip is almost beside the point, though it seems like companies are reticent to name the other issues driving their business woesamong them immigration policy and tariffs.) The result is workers have become more hesitant to stake their careers on a Big Tech job, Coakley says. We see that folks that are coming into their early career have that same symptom, he says. Why would I go into this thing that isn’t stable? I can do a gig role, or I can do something that’s a little more skills-based. Or: Why do I need to go to a four-year college to get this degree if I’m not going to get a job? We’re getting a lot of that sentiment. Some workers who are early in their careers are looking at smaller companies or trying to bolster their AI skills for when the pendulum inevitably swings back and Big Tech starts hiring again, according to Coakley. Zhao argues that the high-paying job in tech still has its allure, though it feels increasingly out of reach for some new entrants to the industry. The number of workers who have been unemployed for over six months has ticked up as hiring has slowedand college-educated workers now comprise a greater share of them. These Big Tech companies are still very attractive jobs, Zhao says. If you ask any new grad, Do you want to go work at Google? I think most of them would still say yes. It’s just a question of how you actually get your foot in the door. What this means for tech workers old and new Its not just people early in their career who are reevaluating where they want to work. The current climate has revealed that tenure and seniority wont necessarily preserve your job, particularly when companies are chasing AI talent. For older employees who built their careers at Big Tech companies, the unease permeating the tech sector has sparked questions about how long they can expect to remain in their jobs. We had a lot of folks atthe beginning of the year coming to us after a layoff, Coakley says. So they didn’t see it coming, or they weren’t expecting it. [Now] I’ve started to see a lot of that other end of the spectrum, where people are being proactive and saying, I don’t know if this is going to be here for me in six months. Experts often say layoffs have a clear effect on company culture, and Glassdoors analysis supports this idea: The volume of Glassdoor reviews surge by over 40% in the week following a layoff, and they continue to be referenced in reviews months later. Zhao points out that some companies seek to avoid the negative attention and press coverage that accompanies a mass layoff by making smaller, more frequent cuts. But tech workers can still see whats happening, and Coakley says some of them are taking preemptive steps to carve out a new path. The mid- to senior-level [employee] has really sort of built their identities inside of one corporation, he says. They’ve lived inside that bubble of Big Tech, but now that the bubble is sort of thinning, they’re asking themselves: Who am I outside this company? Coakley has found that some senior employees are now interested in fractional roles, or startups that offer more work-life balance. People are realizing that they’ve been relying on corporations for stability, he says, and that’s no longer viable. Amid a tough hiring market, even workers who have soured on their Big Tech jobs may be scared to make any drastic moves. But that could change when the market eventually turns aroundto the detriment of these employers. If we see the balance of power shift back towards employees and away from employers, then a lot of this can change, Zhao says. And to some extent that’s a risk that employers should be paying attention to as well. The culture of Big Tech may have changed, but workers have also changed accordingly, growing more emboldened by the upheaval of the last five yearsand the realization that their employers are no different than their peers across corporate America. I think the fact that workers feel so stuck right now, Zhao says, means that once the job market opens up again, all of those workers are going to hit the door.
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Youve landed. You leave the chaos of the airport behind and drop into the chaos of a new city. Its big, loud, and full of opportunities . . . and tourists. If you want to experience this new city like someone who actually lives there, you need tools that help you skip the lines, ditch the tourist traps, and navigate the local landscape with insider confidence. Forget the default maps and review sites everyone uses. Here are three genuinely free, under-the-radar apps that will transform you from a wide-eyed visitor into a savvy urban explorer. Atlas Obscura The biggest mistake a traveler makes is sticking to the big red arrow on the generic tourist map. If you want to find a citys overlooked history, oddball museums, and secret public gardens, you need a guide for the curious. Atlas Obscura is exactly that guide. The free app is a comprehensive, community-generated catalog of the world’s most wondrous and peculiar places. The crucial feature is the map view, which instantly pulls up hundreds of fascinating and unique points of interest near your current location, turning a simple walk into a genuine treasure hunt. Citymapper Once youre in a dense city, a car is often a liability. And while public transportation is an obvious strategy, navigating a new subway, bus, or ferry network can feel like trying to decipher ancient hieroglyphics. Citymapper is a public transit solution built by people who actually ride the subway. If youre visiting New York, London, Chicago, or any of the supported major cities, this app will not only calculate the fastest route, but it will tell you hyper-specific details that Google Maps often misses. The standout feature is its granularity: It gives you the best subway car to board so you exit closest to your destination, provides real-time train and bus arrival times, and blends every mode of transportfrom shared bikes to ferriesinto one comprehensive itinerary. Roasters If youre a serious coffee drinker, you know the despair of being stuck in a new city with only generic chain coffee shops. Finding a true, quality local experience often requires hours of tedious searching and review-sifting. Roasters is a free app built by coffee enthusiasts for coffee enthusiasts, specifically curating over 21,000 specialty coffee shops worldwide and cutting out the chains to focus only on independent businesses known for quality beans and preparation. The community-driven discovery map highlights shops that are often off the beaten path and lets you check reviews from fellow coffee lovers who share your high standards.
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This article is republished with permission from Wonder Tools, a newsletter that helps you discover the most useful sites and apps. Subscribe here. Short on time? Read this 30-second summary of todays post. Download a free, private AI program to run on your computer. Use it offline without any subscription cost and avoid the risk of having sensitive info ingested into a large language model like ChatGPT, Claude, or Gemini. The newest versions of private AI tools like Jan run easily on my 2021 Mac laptop, cost nothing, and are easy to use. Theyre a good alternative to costlier AI platforms. Quick start guide Download and install Jan for free. Other good free alternatives to consider include Msty, AnythingLLM, or LM Studio. Open Jan and pick an open-source large language model. The model you use impacts the AIs response style. You can switch anytime. I use the v1 model. Try your first query. Here are a few quick mini prompts to start with:Summarize the pros and cons of using AI for [specific task].Turn my rough notes below into a short summary and bullet points.”“Turn this angry email draft to my service provider into a constructive message more likely to generate a helpful response. Adjust the apps appearance settings, including font size and shortcuts. Close other processor-intensive apps on your computer, like video editing tools, to reduce the likelihood of your computer slowing down. 5 reasons to use private AI Save money: Avoid subscription fees by running AI models on your own computer. Generate unlimited responses without monthly charges. Keep your data private: Using private AI on your computer ensures no data is sent to or stored on big tech firms servers. No conversations leave your device. You can even run these tools offline. For sensitive legal, medical, financial or personal issues, ask questions without worrying about your data ending up in a large language models training data. Work offline: Having full offline access is handy whether youre traveling without Wi-Fi, working in a remote area, or hesitant to trust a random public network. Experiment with hundreds of open-source models: Choose an open-source large language model that suits you. Each is trained differently. Some are stronger at certain languages, others specialize in coding. New ones emerge regularly. Switch as often as youd like. By contrast, ChatGPT, Claude, Copilot, and Gemini limit you to the platforms own models. Tip: Use LM Arena to compare two models responses side by side. Reduce your environmental impact: If you run hundreds of daily prompts, a local AI app may mean less use of internet infrastructure and remote data servers. Private AI tools allow you to keep your data on your laptop, though they may not be as powerful as top AI platforms like ChatGPT, Claude, and Gemini. [Image: generated with ChatGPT] Jan is an excellent, free, private AI tool Platforms: Mac, PC, Linux What I like about it Fast and easy to set up and use: Jan takes a minute to download and install. Using Jan is as easy as using ChatGPT, Claude, or any other chatbot, though you do have to make an initial decision about which model to use. Assistants: Create customized AI helpers for various purposes. One for translating Chinese, another for coding. Task it to Act as a software engineering mentor focused on Python and JavaScript. Provide detailed explanations with code examples. Use markdown formatting for code blocks. Projects: Organize queries into distinct folders for easy access to subjects of interest without searching through hundreds of threads. Integrations: Link Jan to Canva, Todoist, Linear, or other tools using MCP (model context protocol) connections. Documentation and resources: Lots of useful documentation, including a handbook and blog. Whats Next: Jan AI is developing mobile versions for iOS and Android and adding integrations to link Jan to other services. A Jan case study Becki Lee, a senior technical writer, uses Jan to explore health questions she wants to keep private. I have a chronic illness Im struggling to get diagnosed, she emailed me. So I created an assistant to help interpret test results and brainstorm possible explanations for my symptoms. Obviously, its super important to take this with a grain of salt (a chatbot is absolutely no substitute for a doctor). However, this helps bubble up conditions I can research further on my own, and it also generates questions I can ask my actual doctor. More free AI optios for Mac, PC, or Linux Msty The free version of this well-designed app has multiple unique features. Unlike Jan, which is completely free, Msty also has paid advanced features. Its best free features include: A built-in prompt library with hundreds of options. Special focus and zen modes that strip away side menus. Create multiple personas, which are assistants with distinct personalities. Each can adopt a different style or approach in answering your queries. Knowledge Stacks let you import document collections for analysis. These can include PDFs, Word documents, PowerPoints, spreadsheets, lists of YouTube links, or even an Obsidian vault. Advanced features, like multistep automations, require a paid subscription. Ive only used the free version. Its easy to use, powerful, and well designed. I chose the Gemma 3. AnythingLLM Like Jan, this is a straightforward open-source AI app thats a good option for novice AI users. How its different from Jan You can upload files for AnythingLLM to summarize. Enable it to make simple charts. Turn on Web search, which requires a free API key from Google or Serpa. Theres also a new beta Android version. Caveat: Its not quite as nicely designed as Jan, and isnt updated as often. LM Studio This more developer-friendly option is less simple for beginners. Whats notable: Florent Daudens, an AI expert and educator who used to oversee daily editorial coverage at CBC/Radio-Canada, relies on LM Studio for private AI use. I asked him why and he said, Its practical, with a user/developer-friendly interface, quick updates when new models drop, a server option, and helpful model compatibility info. In a LinkedIn post, Florent shared an example of using LM Studio on his laptop. He used Googles Gemma 3 model to analyze plane photos for extracting registration numbers as an investigative journalist might, without sending data to external servers. Limitations of private AI tools Feature limits: Many special features on other AI platforms wont work on these private AI platforms. ChatGPTs new plug-ins for Canva or Figma, for instance, wont work with private AI. You may not be able to export results directly to Google Sheets or Slack, as you can with other AI tools. No interactives or advanced visuals: You cant create infographics and visual illustrations like ChatGPTs. No coding and hosting interactive applications, as you can with Claude or Gemini. No advanced searches with detailed citations like those from Perplexity. Quality variation: Some open-source models have limited or older training data, so results for certain queries may be worse. For ordinary queries and text summarization, this quality difference may not be noticeable. Slower speed: Depending on your query, you might wait longer with some open-source models than with ChatGPT, Copilot, or other private AI platforms. Speed hasnt been a big concern for me so far. Cant handle as much text at once: A smaller context window means that private AI tools may not be able to analyze text blocks as large as those ChatGPT or Claude can handle. Some small language models may resort to skimming longer text. They may also be more likely to hallucinate details if asked for summaries of long, complex documents. Additional resources Free, open-source AI tools for journalists curated on Hugging Face by Florent Daudens. Read more about why I like Hugging Face as an open-source AI hub. Local LLM Group on Reddit, with 546,000 members. Keep up on notable research on AI and private AI tool development. Helpful write-up about local large language models by Stephen Turner. LinkedIn Learning Course on private large language models and Jan AI. This article is republished with permission from Wonder Tools, a newsletter that helps you discover the most useful sites and apps. Subscribe here.
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