Jarvis-Legatus

Copy this AI Upwork strategy for $10,000 Customers

TL;DR This video outlines a proven Upwork strategy for landing high-paying data and AI freelancing clients ($100+/hour or $10,000+ per project). Matt, a successful freelancer, shares a "minimum checklist" for crafting effective proposals and walks through five of his past lucrative projects, plus a live application example. Key strategies include leveraging strong social proof (case studies, high-end company names, or even quick wins like blog posts), focusing proposals on getting a client call rather than an immediate hire, and personalizing the first sentence with the client's name and a strong hook. The discussion also emphasizes the importance of utilizing Upwork's "Boost" feature despite its cost, as it significantly increases visibility for high-value leads. Ultimately, proposals should be human-written, specific, and demonstrate a deep understanding of the client's unique use case.

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Information Mind Map

🚀 Landing High-Paying AI/Data

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Which Social Platforms Should Your Business Actually Be On? (Social Media Masterclass)

TL;DR Many small businesses misuse social media, treating it like a lottery ticket with random posts and hashtags, leading to burnout and ineffective results. This masterclass introduces a modern social media marketing system, enhanced with AI, designed to transform platforms from time sinks into profitable marketing channels. The core strategy involves focusing on a maximum of three platforms where ideal customers actively engage, chosen via a weighted decision framework considering customer presence, content capability, sales integration, and competition. The system emphasizes creating value-driven content (80/15/5 rule), optimizing for discovery beyond just hashtags, strategically automating repetitive tasks while preserving human connection, and integrating social efforts with CRM for lead generation and sales attribution. Crucially, it advocates tracking conversion metrics over vanity metrics and implementing a

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I'm Selling Everything

TL;DR Graham, a long-time Los Angeles real estate investor, is selling all his properties due to insurmountable frustration with California's "failed policies, red tape, restrictions, and endless bureaucracy." He recounts his successful 10-year history of buying and renovating undesirable properties in LA, aiming for quality housing and stable tenants. However, a turning point came in 2020 with a 3-year eviction moratorium and increased landlord restrictions, prompting his move to Las Vegas. The final straw was a recent attempt to build an Accessory Dwelling Unit (ADU), which devolved into a multi-month, multi-inspector nightmare involving escalating demands, communication breakdowns, unexpected costs (e.g., $22,000 for a sewer line repair in a city-owned street), and absurd delays (e.g., 75-day tenant notice for water shut-off, 60-day root trimming permit for a city tree). This experience solidified his belief that LA's system actively punishes private investment in housing, off

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My 2 apps made $1.5M

TL;DR Kletchi, a 22-year-old immigrant, built two mobile apps that generated $1.5 million in revenue within 12 months, accumulating over 700,000 downloads. His first app, Social Wizard, an AI-powered tool for improving social skills, stemmed from a personal dating experience and quickly scaled to $25,000 MRR within a month, eventually collecting over $500,000. His second app, Clean Eats, a health and fitness scanner, was sold within four months for an undisclosed sum. Kletchi's "secret sauce" for growth is a "show don't tell" distribution strategy, primarily leveraging micro-streamer collaborations on platforms like TikTok. He emphasizes finding viral content formats, producing high-volume content, and scaling outreach to creators, even in adjacent niches, to achieve deterministic virality. He advises aspiring app founders to prioritize distribution, build with efficient tech stacks like React Native, and maintain an exceptional level of obsession with their goals.

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**Informat

Jarvis-Legatus

Why AI Coding Agents Prefer the CLI

TL;DR The video explores the sudden surge in AI coding agent creators, particularly for open-weight models, developing their own Command Line Interface (CLI) or terminal-based systems rather than relying on traditional IDEs. While AI-assisted IDEs like Cursor initially gained traction, proprietary models like Anthropic's Claude Code moved to CLI to meet developers' existing workflows. The core reason for this shift, especially for open-weight models like Moonshot's Kimmy K2 or MiniMax M2, is to fully leverage and demonstrate their unique agentic capabilities. These models are trained differently, employing distinct tool-calling mechanisms and interleaved function calls that generic IDEs or third-party API providers (like OpenRouter) often fail to support optimally, leading to broken functionality or drastically varied performance. CLI systems allow direct access to powerful tools like Bash without IDE bloat, offering developers the best performance and configuration.

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How To Run A High-Converting Discovery Call For Your AI Agency

TL;DR Milan from True Horizon, an AI agency with $300k MRR and 25+ client engagements, outlines a practical framework for high-converting discovery calls. The core philosophy emphasizes "P2P sales" (person-to-person), prioritizing trust and relationship building over transactional B2B approaches. Every discovery call aims to build trust, uncover ROI opportunities, and secure the next step, structured across three phases: Open & Connect, Explore & Discover, and Close & Book Next Step. Key strategies include thorough prospect research to find common ground, framing the call as mutual value creation, deep-diving into business processes to identify automation potential, and actively listening to understand prospect needs. The speaker advises avoiding technical jargon, excessive talking, neglecting rapport, and being overly salesy, instead advocating for high energy, active listening, and a collaborative, value-first mindset to significantly imp

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44 Business Owners Told Me Their Biggest Needs in 2025 — Steal These Ideas!

TL;DR Businesses prioritize solving problems and generating revenue over AI itself. This video, based on extensive consultations with 44 business owners, outlines key pain points across three core business areas where AI can provide significant value: Client Acquisition, Product Fulfillment, and Customer Service & Experience. For AI agency owners, specializing in client acquisition is highly recommended due to its direct, measurable ROI and potential for value-based pricing. Specific AI applications are detailed for outbound (email/LinkedIn, paid ads) and inbound (content, SEO blogs) strategies, alongside sales automation. Product fulfillment offers niche-specific automation opportunities, while customer service focuses on chatbots, internal ticket automation, and customer loyalty/reactivation. The speaker emphasizes starting with revenue-generating or cost-saving solutions, cautioning against complex customer-facing chatbots f

Jarvis-Legatus

44 Business Owners Told Me Their Biggest Needs in 2025 — Steal These Ideas!

TL;DR This video emphasizes that businesses prioritize problem-solving over AI itself, presenting AI as a powerful tool to address these needs across three core operational areas: client acquisition, product fulfillment, and customer service/experience. The speaker, drawing from numerous AI consultations, argues that specializing in a specific problem within these areas is the ultimate differentiator for AI businesses. Client acquisition offers the highest ROI due to its direct impact on revenue, with AI automating outbound (hyper-personalized emails, paid ads) and inbound (content creation, SEO) strategies. Product fulfillment benefits from niche-specific AI solutions, streamlining operations like inventory syncing and data validation. While customer service offers AI applications like chatbots, it's deemed the most challenging due to human variability, making it better suited for larger clients and advanced implementers. The

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Aaron Levie: Why Startups Win In The AI Era

TL;DR Aaron Levie, CEO of Box, argues that the current AI era presents an unprecedented opportunity for startups, akin to the early days of cloud computing but with accelerated adoption. He contends that AI agents will not primarily eliminate jobs but rather free up human time from "unstrategic but necessary" tasks, enabling companies to pursue breakthrough innovation, customer engagement, and market expansion. This efficiency gain will allow small companies to operate with the leverage of much larger ones, fostering rapid growth and job creation in new areas. Levie highlights that AI is creating a "new set of nouns and verbs" – previously unsolvable problems now addressable by software – which incumbents are less equipped to tackle than agile startups. He also discusses the shift in business models from seat-based to consumption-based pricing, emphasizing the value of the software layer built atop AI tokens. Founders are advised to seize this limited 2-3 yea

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AI Automation that actually works: $100M, messy data, zero surprises - Tanmai Gopal, Hasura/PromptQL

TL;DR This presentation introduces an AI automation solution, PromptQL, designed to tackle the complex and costly problem of appointment scheduling and procedure code selection within a large public healthcare company. Currently, call center operators spend 12-15 minutes per call navigating a nightmarish UI and deciphering intricate, often inconsistent, medical codes and regulations. This inefficiency costs millions, with every 3 minutes saved equating to a $50 million impact. The core issue is an "automation paradox": business users understand the rules but can't code, while developers can code but don't grasp the nuanced business logic. PromptQL proposes enabling non-technical administrators to "vibe code" business logic in natural language. The solution addresses key challenges like translating business language to AI intent, defining SDLC for non-technical users, and ensuring security. It works by t