Zendesk AI

Zendesk AI AI

Zendesk AI AI

Zendesk AI AI

Zendesk AI AI

Zendesk AI AI

Zendesk AI AI

Zendesk AI AI

Zendesk AI AI

Zendesk AI AI

Zendesk AI AI

I use claude for investing in stocks and I wonder if I do it correctly

Some time ago I started using claude as my main investing tool in choosing stocks. Below I leave example of the prompt that I used based on $NOW example. I was wondering if this method is completely shit or maybe im doing this right. You are acting as a senior buy-side equity research analyst at a large institutional investment firm. Your task is to produce a full institutional-quality investment research report on ServiceNow, Inc. (ticker: NOW), with the goal of determining whether the stock offers an attractive risk/reward opportunity at the current market price. Your analysis must be extremely rigorous, evidence-based, forward-looking, and decision-oriented. Do not produce a generic company overview. I want a deep investment judgment that combines fundamentals, valuation, business quality, competitive position, financial trajectory, market expectations, technical setup, sentiment, catalysts, risks, and probability-weighted scenarios. The final output should help an institutional investment committee decide whether to buy, hold, avoid, or wait for a better entry point. Important requirements: Use the most up-to-date information available. Use the latest stock price, market capitalization, enterprise value, valuation multiples, financial statements, earnings releases, guidance, analyst expectations, investor presentations, SEC filings, conference call transcripts, recent news, and market data. Clearly state the date of the data used. If exact real-time data is unavailable, say so clearly and use the most recent available data, while explaining the limitation. Prioritize primary sources: 10-K, 10-Q, earnings releases, investor presentations, official guidance, and management commentary. Cross-check important facts with multiple reputable sources. Company and business model analysis. Analyze ServiceNow’s business model in detail: What the company actually does. Its core products and platforms. Main revenue streams. Subscription revenue quality. Customer base. Enterprise adoption. Renewal rates, retention, and net expansion if available. Pricing power. Mission-critical nature of the platform. Switching costs. Scalability of the model. Exposure to enterprise IT spending cycles. Role of AI and workflow automation in future growth. Explain whether ServiceNow is simply a high-quality software company or whether it has a durable long-term platform advantage. Industry and market opportunity. Evaluate the total addressable market and the structural growth opportunity: IT service management. IT operations management. Customer workflows. Employee workflows. Creator workflows. AI-enabled enterprise automation. Generative AI monetization. Workflow automation across large enterprises. Potential expansion beyond the current core markets. Assess whether the market opportunity is still large enough to support strong growth over the next 3–5 years, or whether growth is naturally slowing due to scale. Competitive position and moat. Analyze ServiceNow’s competitive advantage against relevant competitors and adjacent platforms, including but not limited to: Salesforce. Microsoft. Atlassian. Workday. Oracle. SAP. Zendesk. Freshworks. AI-native automation tools. Internal enterprise IT systems. Potential disruption from generative AI agents. Evaluate: Switching costs. Network effects, if any. Data advantage. Platform depth. Customer lock-in. Sales execution. Partner ecosystem. Cross-sell potential. Product breadth. Risk of platform consolidation by Microsoft/Salesforce/SAP. Whether AI is a tailwind, threat, or both. Financial analysis. Perform a detailed analysis of ServiceNow’s financials using the most recent annual and quarterly data: Revenue growth. Subscription revenue growth. Remaining performance obligations. Current remaining performance obligations. Billings growth. Gross margin. Operating margin. Free cash flow margin. Rule of 40. Sales and marketing efficiency. R&D intensity. SBC / stock-based compensation. Dilution. Cash position. Debt. Net cash or net debt. Return on invested capital if relevant. Quality of earnings. GAAP versus non-GAAP profitability. Free cash flow conversion. Margin expansion potential. Do not just list numbers. Interpret what they mean for the investment case. Growth quality and sustainability. Analyze whether current and expected growth is: Durable. Accelerating or decelerating. Supported by secular demand. Dependent on macro conditions. Dependent on upselling and cross-selling. Dependent on AI monetization. Already fully priced into the stock. At risk from enterprise budget pressure. Assess whether ServiceNow can realistically sustain strong double-digit growth over the next 3–5 years. Management and execution. Evaluate management quality: CEO and leadership team. Track record of guidance credibility. Execution history. Capital allocation. M&A strategy. Product innovation. Sales exec

Trust & Safety appeal form broken

Hello There. Recently, I received an automated suspension notice. Regardless of the reason, I noticed that the entire pipeline for users to interact with the Trust & Safety team is currently broken and pointing to dead endpoints. If anyone else is trying to navigate this system right now, here is the loop you will likely get stuck in: The UI Redirect Loop: The official notification tells you to log in to appeal. However, going to the appeal URL (claude.ai/restricted) instantly triggers a forced redirect back to the standard claude.ai login page. The UI completely blocks access to the native appeal flow. The Support Bot Fallback: If you email [support@anthropic.com](mailto:support@anthropic.com) to report the broken UI, the automated Zendesk bot replies with a hardcoded fallback link, stating you must use a specific Google Form to reach Trust & Safety. The Dead Endpoint: The Google Form link provided by the bot is unpublished. When you click it, Google Drive throws a hard error: "Sorry, the file you have requested does not exist/is unpublished." Essentially, the automated systems are routing users to a closed circuit with no exit node. Has anyone else documented this UI loop recently? It seems like Anthropic deprecated their old Google Form but forgot to update the automated bot responses and the platform's redirect rules. PS: I am not asking for account support or a ban appeal here, just documenting a severe bug in the platform's offboarding/appeal infrastructure to see if others are experiencing this system issue. PPS (Update): Using AbelOrtiz25 form link I receive a refund from my subscription, BUT without even sending me an email to let me know! At least I could get my money back. F*ck*ng AI process! submitted by /u/tristobal [link] [comments]

I got tired of the current ticketing systems, so I (Claude ofc) built a better one for everyone — thank you Claude

WARNING: anecdotal rant incoming. Jira requires a PhD to administer properly, and a second one to figure out why a Story is in the wrong sprint. ServiceNow requires the wealth of a cartel drug lord and a procurement team to even get a quote. Freshservice and Zendesk are fine until you need anything custom, then they fall apart. Most of the rest are form-builders with status fields strapped to a queue. Y'all know what I mean. For the better part of my career — 15+ years in IT — auditing tickets for accuracy (ticket triaging) was just taking up too much time. Tickets where the priority was wrong, the category was blank, the subject line three words and a typo. Then writing reports (this is not the focus of the tool, use something else for better reporting, like powerbi / tableau or w.e.) from that data. Manually. Like it was 2010. So I built my own. It's called BITSM. Multi-tenant IT helpdesk with an AI layer called Atlas baked in from day one — not bolted on. Atlas runs a tool-use loop rather than one-shot completions. It searches the knowledge base, looks up ticket history, writes custom fields, and decides when to hand off to a human. The whole point is to handle the grunt work that fills up support queues — tagging, categorizing, routing, drafting responses, flagging when something looks like a known issue — so the people on the queue can focus on the things that actually need a human. Intake channels: web portal, chat widget, inbound email (Cloudflare Email Worker), SMS, WhatsApp, and a voice agent (Twilio + ElevenLabs). Three-tier escalation — Claude Haiku for frontline, Sonnet for harder problems, human for everything else. BYOK for every external service: Anthropic, OpenAI, Voyage, Resend, Twilio, ElevenLabs, Stripe. Stack is Flask 3.x, React 19, PostgreSQL 16 with pgvector, Redis 7, Docker Compose. Running in production at bitsm.io. Built solo on weekends over the past year — and full transparency: I pair-programmed a huge amount of this with Claude (Anthropic's). I'm a one-person shop and that collaboration is the only reason it shipped at the scope it did. If you're a solo builder hesitating on AI-assisted dev, stop hesitating. License note, because someone will ask: Business Source License 1.1, not open source. Self-hosting for your own team is free. If you're building a hosted or managed service on top of it, that requires a commercial license. Converts to Apache 2.0 in four years. Upfront rather than buried. The repo: https://github.com/NovemberFalls/BITSM Happy to answer questions about the architecture or the AI design. A lot of the Atlas patterns came out of Ed Donner's agentic LLM courses, which I'd recommend to anyone building in this space. submitted by /u/Novaworld7 [link] [comments]