Tech stack I use in Mid 2026

Laxman K R • 2026.05.25

Building modern, scalable applications requires moving away from heavy, monolithic frameworks toward modular architectures, type-safe data layers, and deterministic agentic systems. This is the breakdown of the production-ready stack I am building with in Mid 2026.

Frontend: Highly Interactive & Type-Safe

The client layer focuses heavily on strict type safety, zero-boilerplate data fetching, and micro-interactions.

  • Next.js Next.js: Remains my primary framework foundation for core production routing, server-side rendering, and robust framework feature coverage.
  • TanStack TanStack Start: My preferred choice for full-stack React architectures, providing exceptionally well-designed, type-safe isomorphic routing, loaders, and middleware.
  • TanStack TanStack Router: Utilized for pure, deterministic client-side routing with complete type safety across parameters and routes.
  • React React: The underlying core UI foundation for building dynamic interactive components.
  • Shadcn Shadcn: Clean, accessible primitives that don’t lock the interface into a rigid, monolithic component UI.
  • ReactBits ReactBits: Integrated for drop-in, creative animated components that bring smooth visual layouts to life.
  • Paper Shaders Paper Shaders: Elevates layouts into immersive, visually unique user experiences using high-performance WebGL and canvas-based shaders.

Backend: Functional, Fast, & Type-Inferred

My backend architecture prioritizes high throughput, minimal overhead, and explicit error handling.

  • Bun Bun: Serves as the high-performance, all-in-one JavaScript/TypeScript runtime engine, drastically reducing cold starts, bundling times, and memory footprints across backend services.
  • Effect Effect: The crown jewel of the backend. Moving to an ecosystem built on functional programming primitives allows for structured concurrency, built-in tracing, and deterministic error handling without fragile try/catch blocks.
  • Elysia Elysia: Built natively on Bun to handle ultra-fast HTTP APIs, using end-to-end type inference via Eden to connect the frontend and backend seamlessly.
  • FastAPI FastAPI: Reserved for data science environments, heavy LLM orchestration, and Python-centric AI pipelines where rapid ecosystem compatibility is required.

Databases & Storage: Hybrid & Multi-Model

Data belongs where it runs best. I use a combination of local, managed, and specialized vector databases depending on the workload.

  • PostgreSQL PostgreSQL: Self-hosted inside dedicated VMs for raw cost efficiency, deep configuration access, and complete data ownership.
  • Supabase Supabase: Deployed for rapid prototyping, real-time sync capabilities, and taking advantage of managed serverless Postgres primitives.
  • Neon Neon: Used specifically when serverless database branching and instant scalability are required for dynamic feature preview workflows.
  • MongoDB MongoDB: Leveraged as the primary document store for flexible, schema-less application datasets.
  • SQLite SQLite: Lightweight relational storage deployed for edge execution, local utility states, or fast local caching layers.
  • Zvec VectorDB Zvec VectorDB: Integrated for specialized, hyper-efficient vector indexing workflows.
  • Qdrant Qdrant: Handles large-scale, production-grade embedding retrieval and high-performance similarity searches.

Cloud & Infrastructure: Serverless Control & Edge

Infrastructure in 2026 is about blending the control of raw virtual instances with the speed of edge routing.

  • Google Cloud Google Cloud Compute Engines: The baseline infrastructure bedrock for hosting predictable, continuous server workloads and databases.
  • Google Cloud Google Kubernetes Engine (GKE): Orchestrates, scales, and manages larger, decoupled containerized microservices.
  • Google Cloud Google Cloud Storage: Provides durable, globally accessible object storage for unstructured assets.
  • Vercel Vercel Fluid Compute: Used for frontend hosting and advanced edge execution, allowing multiple requests to share warm processes to eliminate cold starts.
  • Vercel Vercel AI Gateway: Sits in front of inference models to handle intelligent caching, rate-limiting, and deep telemetry.
  • Netlify Netlify: Utilized as an alternative edge target deployment platform for distributed web applications.
  • OpenRouter OpenRouter: Acts as a unified, resilient API interface to access over 300+ LLMs with native fallback rules and token budget controls.

Agents & Automation

Autonomous execution requires developer-focused toolchains that can parse, generate, and execute code natively.

  • Opencode Opencode: Unmatched excellence in the TUI space.
  • Codex Codex: The gold standard for Agentic Development Environments.
  • Gemini Gemini CLI: Unbeatable value with complimentary, high-limit access.
  • Antigravity Antigravity CLI: Premium testing framework that trades Gemini's free tiers for better performance.

Agentic Frameworks: The Orchestration Layer

Building reliable agents means moving away from brittle, free-form text prompts and embracing structured, type-safe runtime environments.

  • Google ADK Google ADK: Leveraged for deeply integrated Google ecosystem automations and native service-level intelligence.
  • Microsoft AutoGen Microsoft AutoGen: Handles complex multi-agent conversation patterns and hierarchical task routing.
  • AI SDK AI SDK: The reliable gold standard for building fast UI stream bindings and robust, structured tool-calling pipelines.
  • TanStack TanStack AI: Provides brilliant, framework-agnostic agent clients and middleware utilities like contentGuard and toolCache.
  • Effect Effect AI: Brings provider-agnostic abstractions to LLMs, ensuring that streaming chats, tool calls, and retries benefit from Effect's structured concurrency and deep tracing.