How to Choose the Best Tech Stack for Startups

🛠️ Journey to Assessments.lol Launch - Dev Log #2 Tech Stack Deep Dive After much research and consideration, I've locked in the tech stack for assessments.lol. Here's why each piece matters: 📱 Frontend: Next.js + TypeScript • Why? Next.js has been really hyped lately and I wanted to take this as an opportunity to learn it. It also has a really great development experience and does a lot of heavy lifting in stuff like page navigation/routing. • TypeScript catches bugs before they happen (TypeScript is almost a no brainer in these days, we want that extra type safety!) 🔐 Backend: Supabase • PostgreSQL database with real-time capabilities • Built-in authentication that took 30 minutes to set up instead of weeks • Row Level Security means each user only sees what they're supposed to 🎨 Styling: Tailwind CSS + Daisy UI + Shadcn UI • Consistent design system out of the box • No more fighting with CSS specificity issues ☁️ Deployment: Vercel + Cloudflare • Zero-config deployments • Edge functions for speed • DDoS protection included This entire stack is free to start with and scales beautifully as we grow. We can handle thousands of users without touching the infrastructure. 🔑Takeaway: Pick a tech stack that solves your core problems out of the box. ----------------------------------------- For those new to my Dev Logs, assessments.lol is a platform for sharing anonymous, crowdsourced data about technical assessments at top companies. I’m sharing my thoughts and progress publicly to keep me accountable and this is one of the Dev Logs of the journey. I’m learning a lot along the way so if you have any valuable input please share them in the comments! Join the waitlist: https://lnkd.in/emxD58bM Stay tuned for the next dev log! 🌟 #BuildInPublic

Your ops stack can make or break your startup. Building a startup is exhilarating, but it's the unsexy parts that often determine success. Here's what we've learned at Clarify after 9 months of building our foundation. 🏗️ 🔍 Do your homework: Don't just copy your friends' stack. What works for them might not work for you. We evaluated alternatives for each tool. It took time, but saved us from "referral hell" and tool regret later on. ⚒️ Get your hands dirty: Resist the urge to hire an "ops person" right away. I set up and ran our system for months. It was tough, but gave me invaluable insights into our operations. ⚖️ Balance innovation and stability: As a startup, it's tempting to try every shiny new tool. Be cautious with core systems (HR, finance, etc.). We're bold with low-impact tools, conservative with the essentials. 🔗 Integration is key: Great individual tools don't always play nice together. We prioritize integration capabilities when choosing new tools. 🧑💻 Adoption > features: The fanciest tool is useless if your team hates using it. We involve key team members in tool decisions and provide thorough onboarding. 🌱 Plan for scale, but don't overdo it: Early on, we over-engineered our stack, preparing for 100+ employees when we were just 10. Now we choose tools that can grow with us, but optimize for our current needs. 🛡️ Security isn't optional: In the rush of startup life, it's easy to backburner security. Big mistake. We bake security considerations into every tool choice from day one. ♻️ Continuous improvement is key: Your ops stack isn't set-it-and-forget-it. We do quarterly reviews, gathering feedback and reassessing our needs. Remember, your stack shapes employee experience, operational efficiency, and your ability to make data-driven decisions. It's about building a foundation for scale. Here's where we landed after 9 months: 📨 Email: Google Workspace 🤝 HRIS: Rippling (onboarding, payroll, devices) 💬 Comms: Slack (pro tip: custom emojis boost culture) ✍️ Docs: Notion + Google Docs (company wiki vs. collaborative editing) 🛣️ Project management: Linear (roadmaps, projects, milestones) 🎨 Design: Figma (open access) 💰 Banking: JPMorganChase + Mercury (stability meets UX) 💳 Credit cards: Ramp (expense management on steroids) 🤔 Financial planning: Causal (because spreadsheets don't cut it forever) 📅 Calendars: Cal.com, Inc. + CalendarBridge (bye-bye, scheduling headaches) Takeaway: Stay flexible and keep optimizing – your needs will evolve. For folks building a company: What's been your biggest ops stack challenge or win?

One bad tech decision can destroy your startup. I've led the creation of 100+ software products for Silicon Valley startups & global businesses. The 5 key principles for choosing right in 2025: Most founders get their tech stack totally wrong. I've watched companies burn hundreds of thousands rewriting their entire codebase because they chose trendy tech that couldn't scale. Your tech stack choice today will impact: • How easily you scale • How fast you ship features • How much talent you attract Most chase whatever's hot in tech Twitter threads. But your business isn't a testing ground for experiments. Here are 5 principles I've learned from building software for Silicon Valley startups: 1. Avoid Fads Like The Plague Every year brings a new "revolutionary" framework that's supposed to change everything. 90% disappear within months. Your tech stack needs to solve real problems, not win coolness points. 2. Think Long-Term Your tech choices are marriages, not one-night stands. Pick solutions that will still be relevant in 5-10 years. The strongest technologies are usually the battle-tested ones. 3. Accept The Trade-offs There are no perfect solutions, only smart compromises: • Microservices scale better but add complexity • NoSQL gives flexibility but sacrifices consistency • Serverless cuts costs but increases dependency 4. Go Mainstream The more developers using a technology, the better your position: • Easier hiring • Better tool integration • Fewer scaling headaches • Lower maintenance costs Don't get stuck maintaining some obscure framework nobody uses. 5. Get Expert Eyes One bad tech choice = years of technical debt and scaling nightmares. Talk to experienced CTOs. Study where others failed. Ask around. The cost of getting it wrong is massive. I've seen it firsthand: • $300k spent on rewrites • 8-month delays • Entire teams quitting If you're building something serious and want to avoid these expensive mistakes, let's talk. We help companies choose and implement tech stacks that scale. Book a free consultation here: https://lnkd.in/dndQiR9A

Selecting the Right Technology - It's Not Just About Speed, Cost and Quality When evaluating technology options for a software project, we often rely on the old adage - "Fast, Cheap, Good - Pick Two". This suggests there are inherent tradeoffs between speed of delivery, cost, and quality. However, I believe the choice isn't always that simple. The suitability of any technology depends greatly on three additional interrelated factors: Knowledge: This represents the existing expertise your team has with a technology, or how quickly they can ramp up. Picking a completely unfamiliar technology will impact delivery timeline and quality, even if the tool promises efficiency gains when used optimally. Suitability: Every project has unique needs and constraints. Technologies have specific capabilities and sweet spots. The alignment between the two greatly impacts the ability to deliver. A highly popular or fast technology is not necessarily the right tool for a particular job. Popularity: While not a perfect proxy, a technology's popularity often indicates the availability of reusable components, libraries, tutorials, and community support. These can enhance developer productivity. Obscure or niche technologies may lack that ecosystem. Rather than seeing these factors as independent attributes, I visualize them as three interconnected dimensions that bound the solution space for a project: By mapping our specific needs and constraints onto these axes, we can better evaluate technology options both quantitatively and qualitatively, rather than relying on generic claims about speed or cost. The optimal choice emerges from the subset of options our team has experience with and can quickly master (Knowledge), that has capabilities matching the problem domain (Suitability), and has an ecosystem to amplify productivity (Popularity). Of course, there is no perfect choice - tradeoffs still apply. But thinking critically about these dimensions allows us to make better technology decisions that enhance delivery with our time, budget and skills constraints. The most gain comes from growing our collective Knowledge over time. What do you think? How do you visualize or make technology selection decisions? I'd love to hear other perspectives.