标签：#Startup

"# The AI Cost Crisis: How Startups Can Survive the Tokenpocalypse\n\n## Introduction\n\nThe artificial intelligence boom has brought unprecedented innovation, but it has also ushered in a era of spiraling costs. Training state-of-the-art models now requires millions of dollars in compute resources, while simultaneously, the cryptocurrency token market shows signs of a potential collapse—a \"Tokenpocalypse.\" For AI startups, this dual crisis presents an existential threat: how to sustain innovation when both traditional funding avenues and speculative token economies are under pressure? This post explores practical strategies for AI startups to navigate this landscape, focusing on cost optimization, alternative funding, and strategic pivots that can turn crisis into opportunity.\n\n## Understanding the Cost Explosion\n\n### The Compute Crunch\n\nModern AI models, particularly large language models (LLMs) and multimodal systems, demand vast computational resources. Training a single cutting-edge model can consume exaflops of processing power, translating to cloud bills that easily exceed $10 million for a single training run. For startups without deep-pocketed backers, these costs are prohibitive.\n\n### The Token Market Volatility\n\nParallel to the AI boom, the cryptocurrency space experienced explosive growth through token launches—initial coin offerings (ICOs), decentralized finance (DeFi) tokens, and utility tokens for AI-driven projects. However, regulatory crackdowns, market saturation, and declining investor sentiment have led to a sharp downturn. Many tokens have lost significant value, and launching new tokens has become increasingly difficult, removing a once-viable funding path for AI startups.\n\n## Strategies for Survival\n\n### 1. Embrace Model Efficiency\n\nInstead of chasing ever-larger models, startups can focus on efficiency techniques that deliver comparable performance at a fraction of the cost:\n\n- Model Distillation : Train smaller \"student\

These newer social apps offer alternatives to Big Tech’s feeds, focusing on interests, creativity, and community.

Day 48 of building GoDavaii, and the toughest problem isn't the sheer volume of allopathic medicines or the complexity of their interactions. It's the invisible logic of 'Desi Ilaaj' - the home remedies and traditional practices deeply ingrained in Indian families for generations. When everyone knows the comfort and efficacy of 'haldi-doodh' (turmeric milk) for a cold, how does an AI health platform authentically verify and integrate that knowledge without replacing professional medical advice? This isn't just a cultural nod; it's a fundamental challenge for any health AI truly built for India. Global competitors like Epocrates or drugs.com, while excellent within their scope, are entirely English-centric and focused on Western allopathic data. They have no framework for the millions of people who search for health guidance in Hindi, Tamil, or Marathi, and whose first instinct for a cough might be a herbal concoction, not an over-the-counter syrup. The Unspoken Truth About India's Health Landscape For a vast majority of Indian families, health decisions often involve a blend of modern medicine and traditional wisdom. From specific herbs to dietary adjustments passed down through generations, these practices are effective for many minor ailments. Yet, in the digital health space, they're largely ignored. Why? Because the data is fragmented, often anecdotal, and doesn't fit neatly into structured pharmacological databases. It's a goldmine of practical health knowledge, but also a minefield for safety if not handled with care. My realization as Pururva Agarwal, 27-year-old founder of GoDavaii, was simple but profound: if we truly want to serve families coming online in their mother tongue, our AI needs to understand and interact with this context. This means going far beyond just translating English medical terms into 22+ Indian languages. It means building a knowledge graph that can intelligently cross-reference traditional remedies with known active compounds, potent

AI Does Not Cancel Reality I watched the conversation between Mo Gawdat and Marina Mogilko about the future of AI. The conversation is strong. It contains important ideas, but it also contains many claims that sound large in scale, although on closer inspection they rely on very broad generalizations. AI is indeed changing the labor market, education, startups, content, hiring, and ways of thinking. But it does not cancel money, connections, trust, the human vector, creativity, necessity, morality, or people’s ability to adapt. Video on YouTube AI in hiring: automation amplifies chaos Many people have entered the job market. Companies receive huge volumes of resumes. HR departments cannot handle the volume. It is natural that part of the selection process is moving to AI. But there is a serious problem here. Candidates are also starting to play against AI. Resumes are adjusted to vacancies. Cover letters are assembled around keywords. Profiles become optimized for the filter, not for real work. In such a system, the best specialist does not necessarily pass. Often, the person who understood the selection mechanism better passes. The result: the picture becomes cleaner, while the quality of the decision becomes lower. The company gets not the strongest candidate, but the candidate who matched the algorithm best. This leads to lower hiring quality, lower productivity, and slower development. “I built a startup in six weeks”: a product is not a startup The conversation includes the idea that an AI startup would once have taken years and hundreds of engineers, and now it can be built in weeks. Technically, this is true. Prototypes are now built faster. Small teams have powerful tools. One person can now do more than a group could do before. But two different things are mixed here. Building a product faster has become real. Building a startup faster has become real only when resources are present. A startup is not only code. A startup is money, connections, trust, reputa

I and I imagine a lot of other folks, don't believe the future of work should be a smaller group of executives commanding a larger system of people and machines. We have seen what AI can do not just to software product quality without guardrails, but to the junior and midlevel team members who are laid off or never hired at all in exchange for better profit rates with AI tokens vs human salaries. That is just the old hierarchy with better software. The history of work has always had this tension. You can go back to the start of US history and look at the military, commissioned officers were trained and trusted to command while enlisted service members carried out the work and risk. In the corporate and business world, executives and managers became the people who planned, measured, and optimized, while workers became the people being measured. Those structures were not only about class, but race and in America they were built inside a society already shaped by racism, classism, unequal education, unequal access to capital, and unequal access to leadership. AI now forces us to confront that history again. If we are not careful, AI will not flatten organizations. It will make the hierarchy invisible. Instead of a manager with a clipboard, we will have an algorithm. Instead of a foreman with a stopwatch, we will have dashboards, productivity scores, automated performance reviews, and AI systems that decide who gets opportunity and who gets replaced. That is not progress. The goal should not be to replace people with AI. The goal should be to replace bureaucracy, repetitive work, bad process, and unnecessary gatekeeping. What I am trying to do at Buildly is simple: AI should remove drudgery, not dignity. Automation should increase agency, not surveillance. Productivity gains should be shared, not extracted. Hierarchy should be functional, temporary, and accountable — not a measure of human worth. This is why we talk about AI-native product development differently. An AI

While the AI fundraising machine keeps breaking its own records, some founders are building in the other direction. Mirror founder Brynn Putnam just raised money for Board, a startup focused on bringing people together through in-person games and social experiences. Cyberdeck creators are going viral crafting whimsical DIY computers that literally encourage users to touch grass. Unlike the AI-free browser crowd, this doesn’t just feel like backlash, […]

Supabase, an example of an open source project becoming a fast-growing company, has greatly benefited from AI tools like Claude, Codex, and other vibe-coding platforms.

Former DOGE members and Elon Musk allies are backing a startup aimed at using AI to apply "learnings" from DOGE to the private sector.

Indie Hacking the App Store: Navigating Apple's Guidelines for Niche Catholic AI Applications The era of building generic software-as-a-service (SaaS) platforms is shifting. For independent developers and indie hackers, the real opportunity now lies in underserved, highly specific markets. One of the most fascinating and complex niches emerging today is the intersection of artificial intelligence and religious utility. Building a catholic ai application presents a unique set of technical, ethical, and regulatory hurdles. Developers must create highly accurate systems while navigating strict platform guidelines. Unlike general-purpose chatbots, religious applications require absolute precision. A single theological error can ruin user trust. Furthermore, platforms like the Apple App Store have strict rules regarding user safety, privacy, and functionality. This article explores the technical architecture, prompt engineering strategies, and platform compliance steps required to build and launch a successful catholic ai app . Whether you are using Flutter, Swift, or Kotlin, these insights will help you build a robust, secure, and helpful application. Designing a Catholic AI: Aligning with the Catholic Church Stance on AI Before writing a single line of code, developers must understand the domain. Building tools for this community requires respect for established doctrines and traditions. Fortunately, the Vatican has provided clear guidance on this technology. The Catholic Church Stance on AI The Vatican has taken a proactive and surprisingly technical approach to modern computing. Under the leadership of Pope Francis, the Church has introduced the concept of "algorethics"—the ethical development and deployment of algorithms. The catholic church stance on ai emphasizes that technology must always serve human dignity, protect personal privacy, and promote truth. For developers, this means your application must prioritize: Truthfulness: Minimizing errors in theological ou

We’re a tiny team of 2–9 engineers who believe business messaging should be simple, reliable, and accessible to everyone. Today we’re officially opening up BulkSMSOnline to the Dev.to community, and we’d love your feedback. What’s BulkSMSOnline? A global bulk SMS platform that lets you send campaigns, alerts, OTPs, and notifications via: A clean web portal A REST API An HTTP API It’s designed for developers who want reliable global delivery without fighting arcane telecom protocols or opaque pricing. Why We Built It We noticed a pattern: most SMS platforms either overcomplicate things with bloated SDKs or hide behind enterprise gatekeepers that don’t listen. We wanted something different a lean, transparent API backed by real people who actually care about your deliverability. So we built BulkSMSOnline around three principles: Reliability : Messages must arrive, every time. Radical simplicity : A clean API you can integrate in minutes. Transparency : Honest pricing, clear limits, no surprises. Quick Start: Send an SMS in Under 5 Minutes Here’s how simple it is with our REST API. For full docs, check out our developer portal . curl -X POST https://api.bulksmsonline.com/v1/sms \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "to": "+1234567890", "message": "Hello from BulkSMSOnline!", "sender": "MyApp" }' You’ll get a JSON response with a message ID and status. That’s it. No multi-page setup or carrier negotiations. What else can you do? Send bulk messages with a single API call Track delivery in real time via webhooks Pull reports programmatically Use our HTTP API for legacy systems Who’s Behind This? We’re a small, agile team (2–9 people). That means: No bureaucracy: Fixes and features ship fast. Direct access: When you email support, you reach the engineers who built the platform. Your feedback shapes our roadmap: Many of our recent features came from developer conversations. Tech stack we love: Python, Node.js, PostgreSQL, an

I used to think the best AI food logging flow would be simple: Take a photo, let the model identify the meal, confirm it, done. That works surprisingly well for a lot of meals. But while building MetricSync, I learned the awkward product truth: the best input method changes depending on what is in front of the user. A photo is great for a plate. A barcode is better for packaged food. Text is better when the user already knows what they ate or wants to fix one detail quickly. The mistake is treating one input mode like the whole product. Photos feel magical until the meal gets messy Photo logging is the most impressive demo because it removes the blank search box problem. The user does not need to know the exact database name for “rice bowl with chicken and avocado.” They can just show the app what they ate. But meals are messy. A photo might miss the sauce. It might not know if the drink is diet or regular. It might confuse a small serving with a large one. It might identify the food category correctly but still need a portion correction. That does not make photo logging bad. It just means the UX cannot end at “AI guessed something.” The real product is the correction loop. Can the user fix the meal without starting over? Barcode scanning is boring in the best way Barcode scanning is not as exciting as AI, but it is often the right tool. If someone is logging a protein bar, yogurt, cereal, or a packaged drink, asking an image model to infer the nutrition facts is silly. The barcode is more direct. That changed how I thought about the app. AI should not be the star of every interaction. Sometimes AI should get out of the way. The goal is not “use AI everywhere.” The goal is “make logging the thing in front of me take the least effort.” For packaged foods, that means barcode first. For mixed plates, that means photo first. For quick edits, that means text. Text still matters The more AI features you add, the easier it is to forget text input. But text is still the fas

With just two weeks to go, StrictlyVC Los Angeles is quickly approaching. On Thursday, June 18, at The Aerospace Corporation Campus in El Segundo, investors, founders, and tech leaders will gather for an evening of conversation exploring some of the most consequential shifts taking place across venture capital, defense technology, artificial intelligence, and advanced industry. Secure your spot here. […]

On August 19, Startup Battlefield is returning to Sydney in partnership with Stripe, one of the world's most iconic technology companies. We're taking over Stripe Tour Sydney for a night that the Australian startup ecosystem won't forget.

The California startup released the fourth-generation of its home assistance robot, Stretch.

The Bengaluru startup has crossed 1 million orders and reached a $50 million annualized GMV run rate within a year of launch.

Lovable and Google signed an expanded multiyear deal that involves a 5x expansion of Lovable's footprint on Google Cloud, and expanded access to Anthropic Claude.

I built Xaloia AI , a privacy-first AI platform focused on trust and human interaction. And now, I’m shutting it down. Not because the idea was empty. Not because the tech didn’t work. But because I tried to build it from Romania. The Problem Wasn’t the Product Xaloia was built around things that are becoming increasingly important: privacy secure communication human-centered AI But building something meaningful isn’t enough. It needs the right environment to grow. And that’s where things started to break. What I Ran Into Trying to build in Romania, I kept hitting the same walls: Lack of early adopters willing to pay - People are curious about tech, but not ready to invest in new products. Limited startup ecosystem - Fewer accelerators, fewer investors, fewer people who understand what you’re building. Cultural friction around ambition - If your idea isn’t small or conventional, it’s often questioned instead of supported. Low exposure to global markets - Even if you build something good, getting it in front of the right audience is much harder. None of these stop your project instantly. But together, they slowly drain momentum. Why the US Is Different From everything I’ve seen and experienced, the US offers something fundamentally different: Access to capital — people invest earlier Distribution opportunities — platforms, networks, visibility Cultural support for big ideas — ambition is expected, not questioned Faster feedback loops — you know quickly if something works It’s not that success is guaranteed there. It’s that the conditions for success actually exist. The Real Lesson Talent is everywhere. Ideas are everywhere. But opportunity is not evenly distributed. And trying to ignore that reality cost me time, energy, and a product I genuinely believed in. What’s Next Shutting down Xaloia isn’t the end. It’s a reset—with better clarity. Next time, I won’t just focus on building something good. I’ll focus on building it where it actually has a chance to grow.

I’m building Obex, a faith-rooted self-control app for men who want to quit porn and stay consistent with daily discipline. The stack is Expo / React Native, with a web landing page and a desktop blocker companion. Core features: Streak tracking and rank progression Panic Mode for urgent moments Accountability partners Blocker support on desktop Christian-focused language and reminders The goal is to make the product feel practical rather than preachy. People usually respond better to clear feedback loops, a visible streak, and a calm recovery path after setbacks. If you want to see it or give feedback, the site is here: https://obex.so

The startup's own stack for Africa and Middle East is now handling more than 17,000 calls per day.

The Series F round values Coralogix at $1.6 billion and comes less than a year after its previous raise.