9+ min ago (267+ words) At Monetzly, we've engineered a dual-earning platform that offers a fresh monetization strategy. Here's how it works: Conversation-Native Advertising: Ads are integrated directly into the conversational flow of your AI app. This means users encounter contextually relevant ads that enhance rather than detract from their experience. Imagine a user asking an AI assistant for recommendations on productivity tools and being presented with ads for relevant apps'it's a natural extension of the conversation. AI-Powered Contextual Matching: Our platform leverages advanced machine learning algorithms to match ads with user conversations in real-time. This ensures that ads are not only relevant but also increase engagement, leading to higher conversion rates for advertisers. Developer-First Approach: We prioritize developers with our easy 5-minute SDK integration. You can start monetizing your app without the hassle of complex setups. Plus, our advertiser marketplace is tailored for AI…...

10+ min ago (174+ words) Building Conversational AI: The Modern Tech Stack for Voice-First UX Contemporary voice agents operate through a tightly orchestrated pipeline. Optimizing each component is essential for creating a seamless and natural user experience. The Millisecond Budget: Winning the Race Against'Latency Perceptible latency degrades the user experience. A delay of over 1.5 seconds feels unnatural, while a 300ms delay is noticeable in conversation. A reference architecture achieving sub-second latency might look like this: VAD (20ms) + Streaming ASR (250ms) + NLU (75ms) + LLM (600ms) + Streaming TTS (75ms) " 700900ms Total This is achieved through aggressive optimization techniques like streaming architecture (processing audio in small chunks) and parallel processing (sending early ASR hypotheses to the LLM before the user finishes speaking). Conclusion: Beyond the'Hype A genuinely conversational experience emerges not from a single powerful LLM, but from the careful orchestration of the entire voice pipeline. The competitive advantage belongs to those who master the…...

23+ min ago (676+ words) The entrepreneur discusses AI marketing hype, CIOs being forced to play "vendor referee, and the merits of extreme bootstrapping. Rich Waldron did everything to keep Tray.ai alive. Founding the firm in 2012, Waldron went without a salary and funded the no- and low-code specialist by selling shoes online, running an ad agency and printing a small magazine. It worked. Having piqued the interest of investors, Waldron upped sticks from London to San Francisco with only a few days notice and used its own automation software to seek out more venture capital firms. Tray.ai subsequently pivoted from an email-centric foundation to a broader integration fabric but maintained one tenet of faith: the need to simplify building software by connecting data and actions across systems. Still headquartered in San Francisco, Tray.ai now helps customers create AI agents for common tasks…...

34+ min ago (558+ words) Asynchronous: Code can continue without waiting for operation to complete. Blocking: Thread sits idle, waiting for operation (wasteful). Non-Blocking: Thread is released to do other work while waiting. I/O-Bound: Work that waits for external resources (file, network, database). What it is: Low-level OS thread for executing code concurrently. Use: Legacy code or when you need absolute control (rare in modern C#). Modern alternative: Use Task instead. What it is: High-level abstraction representing an asynchronous operation. Use: Default choice for all async/concurrent work in modern C#. Benefit: Lightweight, composable, better error handling, works with async/await. What it is: C# language keywords that make asynchronous code look synchronous. Use: Any I/O-bound operation (file, network, database). Benefit: Non-blocking, easy to read, automatic error handling. What it is: The recommended pattern for async programming in .NET. Use: All new asynchronous…...

34+ min ago (611+ words) The song was perfect" until the platform started buffering." That single moment can turn a loyal listener into a frustrated one who immediately switches to a competitor. In today's digital landscape, audio streaming has become more than just a trending category'it's a core part of modern entertainment, from music to podcasts to talk shows and live audio experiences. And while platforms like Spotify, Apple Podcasts, and SoundCloud dominate the conversation, there's still massive room for new, innovative web-based streaming platforms. But here's the truth: " The audio platforms winning today aren't winning because of content ' they're winning because of experience. They understand how to deliver sound that is: " fast " reliable " secure " personalized " accessible " creator-friendly Whether you're a developer, startup founder, product designer, or tech enthusiast, understanding how to build scalable and engaging audio streaming experiences is a major advantage. In this…...

39+ min ago (261+ words) Claude Opus 4.5 new features The company says that Claude Opus 4.5 outscored all human candidates on an internal engineering examination, employing parallel test-time compute within a two-hour limit. The new version brings improved vision, reasoning, and mathematics abilities as well. New features include support for extended agent operations, multi-agent systems, and tools like context compaction and memory functions. The new model also incorporates an 'effort' parameter, allowing users to balance performance against latency and cost, and enables self-improving agents that refine their skills over iterations. Anthropic describes the system as the most robustly aligned frontier model available, with heightened resistance to prompt injection attacks compared to rivals. Claude Opus 4.5: Pricing and availability The biggest change is the reduction of prices to help users and business with more accessibility. Claude Opus 4.5 is now priced at $5 per million input tokens and $25 per million…...

39+ min ago (261+ words) Claude Opus 4.5 new features The company says that Claude Opus 4.5 outscored all human candidates on an internal engineering examination, employing parallel test-time compute within a two-hour limit. The new version brings improved vision, reasoning, and mathematics abilities as well. New features include support for extended agent operations, multi-agent systems, and tools like context compaction and memory functions. The new model also incorporates an 'effort' parameter, allowing users to balance performance against latency and cost, and enables self-improving agents that refine their skills over iterations. Anthropic describes the system as the most robustly aligned frontier model available, with heightened resistance to prompt injection attacks compared to rivals. Claude Opus 4.5: Pricing and availability The biggest change is the reduction of prices to help users and business with more accessibility. Claude Opus 4.5 is now priced at $5 per million input tokens and $25 per million…...

48+ min ago (268+ words) We are Dmitrii and Anastasia, the co-founders of Introvert, an AI dating co-pilot. Over the last few months, we have completed all the core interaction mechanics, developed the trust and privacy architecture, conducted dozens of real-world tests, defined our go-to-market (GTM) strategy and aligned the product with the long-term roadmap of the Shegby Network State (our broader vision for a user-owned, privacy-native digital society). We have chosen Geyser Fund as the platform for our early supporters because Introvert is closely linked to Bitcoin/Web3 via our HumanRank trust layer and our dedication to identity management without the use of personal data. If you would like to receive our one-pager or pitch deck, please DM me. If you would like to support us early on, you can also reach out to us directly - we will publish our full press release soon. What…...

53+ min ago (250+ words) Our Bike Shed trio check back in with one another to follow up on some topics that caught their attention over the course of season 1. Sally covers her time working with React over the last few months and the challenges it still presents to her workflow, Jo'l goes back over typescripts and the benefits he's found when debugging, and the cast reflect on the first season as a whole, what they liked, what went well and what they'd like to improve on for season 2. You can read up on some of the topics mentioned in this episode here - Constructive vs Predictive Data - Aji's Keynote - Aji's Recommended Keynote from 2022 Your hosts for this episode have been thoughtbot's own Jo'l Quenneville, Sally Hall and Aji Slater If you would like to support the show, head over to our GitHub page, or check…...

1+ hour, 2+ min ago (835+ words) It was 2 AM on a Tuesday when my phone exploded with alerts. Our e-commerce platform was dying. Response times had ballooned from 200ms to 45 seconds. The CPU graphs looked like a heart monitor during a cardiac arrest. I logged in, hands shaking, coffee forgotten. The culprit? A seemingly innocent query: My "fix" from earlier that day: adding a B-Tree index on the description column. The problem: I'd brought a lockpick to a safe-cracking job. This disaster taught me something crucial: PostgreSQL indexes aren't just about "making queries faster." They're specialized tools, each designed for specific types of heists'I mean, queries. Using the wrong one is like trying to break into Fort Knox with a butter knife. Let me tell you about the six types of indexes in PostgreSQL's arsenal, when to use each, and more importantly, when NOT to. Before we…...