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A Chef's Air Fryer Delights: 13 Essential Recipes for Every Meal

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This article explores a professional chef's deep admiration for the air fryer, detailing a diverse collection of 13 beloved recipes that span all meals, from breakfast to dessert. The chef, initially a skeptic, now champions the air fryer for its ease of use and ability to produce consistently delicious results, offering creative applications for various ingredients.

Unlock Culinary Creativity: Your Air Fryer, Your Kitchen, Endless Possibilities

The Chef's Journey to Air Fryer Advocacy

Initially hesitant to embrace the air fryer trend, the author, a seasoned chef, eventually acquired a Gourmia 7-quart digital model. This initial foray quickly transformed skepticism into profound appreciation, leading to the purchase of a second unit. The air fryer's remarkable efficiency and simplicity revolutionized their cooking process, making it an indispensable tool for a wide array of dishes.

Savory Stuffed Portobello Mushrooms for Effortless Dinners

Portobello mushrooms offer a versatile canvas for air frying. The chef enjoys experimenting with various fillings, from classic cheddar and bacon to more adventurous combinations like spinach and cream cheese or garlic and Parmesan. A particular favorite blends feta, cheddar, spinach, artichokes, breadcrumbs, and lemon, with a key technique involving pre-frying the mushroom caps gill-side down to release moisture before adding toppings.

Perfectly Crispy Breaded Shrimp, Every Time

Air-fried breaded shrimp consistently delivers exceptional results. The chef enjoys a spicy "bang bang" rendition, often paired with a vibrant lemon aioli. The preparation simplifies with a three-bowl dredging station for flour, egg (sometimes enhanced with mustard or mayo), and panko. For a quicker alternative, lightly oiled shrimp can be directly coated in panko for a delightful crisp.

Nut-Crusted Chicken: A Moist and Flavorful Favorite

Nut-crusted chicken, prepared in the air fryer, yields a perfectly moist interior and a crisp exterior in approximately 20 minutes. The cooking time can vary slightly between basket and convection-oven air fryers. The chef adapts a panko-breaded chicken recipe by incorporating crushed nuts, smoked paprika, and Parmesan, elevating the flavor profile.

Gourmet Crab Cakes with a Zesty Kick

Among the air fryer's most delicious creations are crab cakes. Following a Food Network recipe, the chef substitutes chipotle chiles and adobo sauce with fire-roasted green chiles and chipotle powder for convenience. These are ideally served with a creamy, tangy chipotle sauce, which is a highlight of the dish.

Crispy Tofu: A Versatile Vegetarian Option

Achieving perfectly crispy tofu in the air fryer is straightforward, with or without cornstarch. The chef emphasizes the importance of pressing excess moisture from the tofu for optimal texture. A favorite preparation involves a ginger, tamari, and garlic marinade, finished with sesame seeds, serving as a flavorful substitute for bacon or a delightful addition to Buddha bowls.

Corn "Ribs": A Creative Vegetarian Delight

Air-fried corn "ribs" are a fantastic vegetarian choice, offering various seasoning options like elote-style, barbecue sauce, or Indian-inspired masala spice. A practical tip is to microwave the corn cobs for seven to nine minutes before quartering them, making the cutting process much easier.

Buffalo Cauliflower "Wings": A Flavorful and Quick Snack

Buffalo cauliflower "wings" are a household favorite, ready in just 15 minutes. The process involves coating cauliflower florets in a mixture of hot sauce, oil, garlic powder, and salt, then air frying them in a single layer until crispy. These are best enjoyed with blue cheese or another creamy dipping sauce.

Quick and Simple Air-Fried Grilled Cheese

Grilled cheese sandwiches are an ideal quick lunch in the air fryer. Larger models can accommodate multiple sandwiches, while smaller units work well with halved sandwiches. The chef's preferred version features goat cheese, apple slices, and cranberry sauce, with a pro tip to cook at a lower temperature initially for melting cheese, then increasing heat to toast the bread.

Roasted Garlic: An Aromatic Addition to Any Meal

Roasting garlic in the air fryer significantly reduces cooking time compared to conventional ovens. The chef suggests preparing large batches of sliced garlic heads, freezing the extras, and roasting them alongside vegetables like honeyed parsnips or carrots. The soft, sweet cloves are perfect for making garlic bread.

Homemade Apple Hand Pies: A Rewarding Culinary Project

While store-bought dough and apple filling can simplify the process, crafting apple hand pies from scratch allows for customization of sweetness and spice. The air fryer ensures a crisp and delicious result, whether using pre-made or homemade components. These pies can be stored in the fridge for up to three days or frozen for up to two months.

Surprising Air-Fried Cakes: A Sweet Revelation

The chef initially doubted the possibility of baking cakes in an air fryer but was pleasantly surprised by the success of cheesecakes and a favorite simple coffee cake with cinnamon and pecans. The air fryer proves to be an effective tool for various baked goods, including banana-walnut pound cake and banana-nut bread.

French Toast: A Consistently Delicious Breakfast Staple

Air-fried French toast consistently produces a delicious, crispy exterior. The chef enhances the batter with ground cardamom pods, cinnamon, and nutmeg. A practical tip for basket fryers with curved corners is to cut the bread into fingers to maximize space, and preheating the air fryer is recommended for optimal results.

Indulgent Molten Lava Cakes: A Gooey Dessert Perfection

Molten lava cakes, with their irresistible liquid chocolate centers, are a delightful air fryer dessert. The chef favors a small-batch recipe, often incorporating orange-flavored chocolate for added depth. A crucial tip is to fill ramekins only two-thirds full to prevent overflow during cooking, ensuring a perfect gooey middle.

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Workplace Data: Your Employer's Asset, Not Yours

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In an evolving digital landscape, the information employees generate at work, ranging from emails to chat messages, is increasingly recognized as a valuable corporate asset. This reality was sharply brought into focus when Google successfully acquired a substantial archive of Spirit Airlines' operational data, including emails, messaging records, and codebase, for $10 million following the airline's bankruptcy. This acquisition underscores a critical shift: the digital footprints left by employees are not their own, but rather a resource that companies can utilize, particularly for developing and refining artificial intelligence technologies.

This trend highlights the imperative for individuals to exercise caution regarding the content they produce within corporate digital environments. As AI's role in business operations expands, the data generated through daily tasks can serve as a crucial foundation for training intelligent systems designed to improve customer service, streamline development processes, and enhance overall efficiency. Consequently, understanding and navigating the nuances of workplace data ownership and privacy has become more important than ever for employees across all sectors.

Understanding Your Digital Footprint at Work

The digital activities undertaken by employees, from crafting detailed reports to exchanging quick messages with colleagues, fundamentally belong to their employer. This encompasses a broad spectrum of digital output, including meticulously composed emails to leadership and casual conversations conducted through internal communication platforms. The growing demand for data to train sophisticated AI models has significantly amplified the perceived value of these digital traces. Industry experts, such as employment attorneys, are observing a notable increase in inquiries from companies eager to purchase workplace data archives, recognizing their potential to bolster bottom lines by fueling AI innovation. This shift necessitates a proactive approach from employees to comprehend how their digital contributions are managed and utilized, especially in light of their increasing commercial worth to organizations.

As companies increasingly recognize the strategic value of internally generated data for advancements in artificial intelligence, the contractual boundaries governing employee-created content are becoming more pronounced. This corporate ownership extends to virtually all digital interactions and documents produced on company systems, making it crucial for employees to be aware that their digital communications are not private. The acquisition of Spirit Airlines' operational data by Google for AI training purposes serves as a potent illustration of this principle in action. While the immediate benefits for businesses can be substantial, leveraging this data for training AI assistants to manage customer queries or assist developers in debugging software, it underscores the need for clear corporate policies. Employees are encouraged to actively seek information about their company's data retention and privacy policies, as these frameworks dictate the terms under which their digital work lives on and is potentially repurposed. This vigilance is particularly important in an era where the lines between personal and professional digital conduct can easily blur, with significant implications for individual privacy.

Safeguarding Personal Information in a Corporate Landscape

In the contemporary workplace, the distinction between personal and professional digital content is increasingly blurred, presenting challenges for employee privacy. While companies assert ownership over work-related communications and data, sensitive personal details such as Social Security numbers and private health information are typically afforded robust protection under various state and federal laws. Even in the event of a company's financial distress or bankruptcy, these legal protections generally prevent the unauthorized disclosure or sale of highly sensitive personal data. This legal safeguard offers a degree of reassurance to employees regarding their most confidential information, irrespective of their employer's operational fate. Nonetheless, this protection primarily pertains to explicitly sensitive data, leaving a vast array of other work-generated content open to corporate utilization.

Despite the legal safeguards in place for sensitive personal data, employees are strongly advised to adopt a proactive and defensive stance regarding their digital practices at work. The pervasive nature of corporate data collection, driven by the escalating demand for information to train artificial intelligence, means that virtually any content created on company devices or platforms could be retained and utilized. This situation underscores the importance of treating all work-related digital communication as non-private and potentially enduring beyond one's tenure with the company. The counsel from legal experts emphasizes that a work email or chat should never be considered a personal diary, as the content is subject to corporate oversight and potential repurposing. Therefore, maintaining strict boundaries between personal and professional digital activities, and exercising prudence in all work-related communications, remains the most effective strategy for employees to mitigate privacy risks and navigate the complexities of corporate data ownership.

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Harvey's Tenet: Revolutionizing Legal AI with a Proprietary LLM

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Harvey, a prominent legal-software company, has launched its inaugural proprietary large language model (LLM), named Tenet. This move marks a significant shift for the company, which previously built its $11 billion business primarily on the AI models of other firms. Tenet is designed to automate and streamline a broader range of legal tasks, traditionally performed by lawyers over extended periods, with increased cost-efficiency compared to its previous reliance on external models. This development comes at a crucial time as major general-purpose AI model developers, such as Anthropic and OpenAI, are increasingly targeting the legal sector, prompting Harvey to enhance its own technological autonomy.

This strategic pivot by Harvey not only aims to optimize its operational costs but also to fortify its market position amidst intensifying competition. By developing Tenet, Harvey seeks to mitigate the financial burden associated with using third-party AI models, which can accumulate rapidly with increasing usage. Furthermore, Tenet represents an opportunity for Harvey to offer a more tailored and refined AI solution to its legal clients, integrating domain-specific knowledge and workflows into the model's core design. The company envisions Tenet as a foundational tool that law firms can further customize, transforming their accumulated legal expertise into actionable blueprints for AI-driven processes and potentially reshaping the landscape of legal services.

Harvey's Strategic Leap into Proprietary AI Development

Harvey, a well-established entity in the legal software domain, has made a decisive move by introducing Tenet, its first proprietary large language model. This initiative is a strategic response to the evolving competitive landscape, where major AI developers are increasingly encroaching on the legal technology market. By developing an in-house model, Harvey aims to gain more control over its product capabilities and cost structure, reducing its dependence on external providers like OpenAI and Anthropic. This shift is crucial for maintaining its market leadership and offering more specialized AI solutions tailored to the intricate demands of legal practice, thereby enhancing efficiency and potentially lowering operational expenses for its clientele.

The creation of Tenet represents a pivotal moment for Harvey, allowing the company to transcend its previous role as a user of third-party AI frameworks to become an innovator in its own right. This proprietary model is envisioned to tackle complex legal tasks that typically demand extensive lawyer involvement, offering a cost-effective alternative. The strategic rationale behind Tenet is twofold: firstly, to reduce the substantial fees paid to external model providers, thereby improving profit margins without burdening clients with higher charges; and secondly, to enhance the quality and relevance of AI applications by tailoring the model specifically to legal reasoning and workflows. By investing in its own AI development, Harvey is not only securing its future competitiveness but also aiming to set new benchmarks for AI integration in the legal profession.

Innovating Legal Workflows with Tenet's Advanced Capabilities

The development of Harvey Tenet involved a rigorous process of data curation and model training, emphasizing the nuances of legal thinking. Harvey engaged legal professionals, both internal staff and external contractors, to craft mock legal disputes and case files. These simulated scenarios were then used to evaluate and refine the model's reasoning abilities, ensuring its output was aligned with professional legal standards. This meticulous approach to data generation and feedback is critical for training an AI model that can genuinely understand and perform complex legal tasks, moving beyond generic language processing to specialized legal intelligence.

Tenet is part of a broader initiative, Harvey II, which also introduces a "Memory" feature to personalize user experiences by retaining workflow preferences. The model itself was trained using a customized version of Kimi K3, an open-source model from Moonshot, known for its efficiency and affordability. Harvey is confident that Tenet will demonstrate superior performance in legal tasks, with forthcoming research to substantiate its claims. Beyond immediate application, Harvey harbors ambitions for Tenet to serve as a foundational platform, enabling law firms to develop their own bespoke AI models. This vision positions Harvey not merely as a software vendor, but as a strategic partner, assisting legal organizations in leveraging their unique expertise and historical data to create highly specialized AI agents that can transform the delivery of legal services.

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