Insights & Case Studies

Our Blog

Technical deep dives, industry trends, best practices, and case studies from the projects we've shipped.

  • Give Every Bot a Job: How We Use AI Agents, Tools, and Grok Bots

    Agents have moved out of the chat window. They now have their own computers, tools, and schedules. Here's how we use coding agents, MCP tools, and Grok Bots in our own work and in client products, and the guardrails that keep them useful instead of risky.

    Best Practices 8 min read
  • AI Can Build Your App. We Make It Ship.

    Everyone's using Cursor, v0, Bolt, and Claude to build apps — and they can get you 60-80% of the way there. But the last 20% (production-ready code, deployment, integrations, edge cases, security) is where most founders hit a wall. That's where Six One comes in.

    Industry Trends 7 min read
  • AI-Powered Developer Tools Are Changing How Teams Ship Code

    From AI code completion to automated PR validation, developer tooling is undergoing its biggest shift in a decade. We break down where AI is delivering real value in the development workflow — and where the hype still outpaces reality.

    Industry Trends 7 min read
  • Building Real-Time Features Without the Complexity

    WebSockets, server-sent events, polling, CRDT-based sync — real-time features can be architecturally simple or nightmarishly complex. Here's how we approach real-time in production apps, and why you probably don't need the complexity you think you do.

    Technical Deep Dive 7 min read
  • Case Study: Building Doka AI's Document Intelligence Platform

    How we built an AI-powered document workspace that lets teams upload PDFs, slides, audio, and video — then chat with their content and get cited answers. A deep look at the RAG architecture, multi-tenant design, and real-time collaboration features behind Doka.

    Case Study 6 min read
  • The RAG Pipeline Playbook: Lessons from Building Production AI

    Retrieval-Augmented Generation sounds simple in theory — chunk documents, embed them, retrieve relevant context, generate answers. In practice, every step hides pitfalls. Here's what we've learned building RAG systems that actually work in production.

    Technical Deep Dive 7 min read
  • Case Study: Building LGTM's AI-Powered PR Validation Engine

    How we built looksgoodtome.ai — a developer tool that reads PR diffs, identifies affected user journeys, spins up Playwright sessions, and posts merge confidence reports. A look at the architecture behind zero-config, ephemeral test validation.

    Case Study 7 min read
  • Why Mobile-First Design Still Wins in 2025

    Mobile-first isn't a trend — it's a constraint that produces better products. After building dozens of applications, we've seen firsthand how designing for the smallest screen forces clarity, prioritization, and performance that desktop-first approaches consistently miss.

    Best Practices 6 min read
  • Case Study: From Spreadsheets to SaaS — Building PropPanda

    How we helped PropPanda go from an idea to a mobile-first property management platform for solo landlords. Rent collection, tenant portals, Plaid-powered expense tracking, and smart notifications — built lean and launched fast.

    Case Study 7 min read
  • The Real Cost of Technical Debt (And How to Pay It Down)

    Technical debt isn't just slow code and messy abstractions — it's slower feature velocity, harder hiring, and compounding risk. Here's a practical framework for identifying, prioritizing, and systematically reducing the debt that's holding your product back.

    Best Practices 7 min read
  • Choosing the Right Tech Stack for Your SaaS MVP

    The tech stack decision for your MVP matters less than you think — and more than you think. Less because any modern stack can build a great product. More because the wrong choice creates friction that compounds every day. Here's how we think about it.

    Best Practices 7 min read
  • The Small Team Advantage: Why Startups Should Think Like Studios

    The best software isn't built by the biggest teams. It's built by small, focused groups with strong opinions and fast feedback loops. Here's the case for the studio model — and why we believe 3-5 senior engineers outperform teams of 20.

    Industry Trends 7 min read