AI writes code.
    We decide what's
    worth shipping.

    Anyone can generate software now. Fewer people can tell you what to build, what to cut, andwhat'll still be running in five years. That's the work we do.

    What we do

    We help teams ship software thatholds up.

    Every engagement starts with a real problem and ends with something you can run in production. Not a slide deck.

    01

    We work across the stack (frontend, backend, data, infra) and own the parts that don't make the demo reel: auth, billing, migrations, testing, CI/CD, and the runbook you'll need the first time something breaks.

    02

    We design cloud architecture that holds under real load, set up observability you'll use (not dashboards no one reads), harden security boundaries before they become incidents, and make the ops decisions — backup strategy, on-call rotation, cost ceilings — before they become emergencies.

    03

    We design the architecture (RAG, agents, tool use, structured output), build the eval pipeline so you can tell when it's working, and harden it against prompt injection and data leakage before it ships. We also own the unglamorous parts: token cost monitoring, latency budgets, fallback behavior, and model version pinning.

    04

    We audit current workflows, set up guardrails (code review standards, security review, what not to let AI touch), and measure productivity honestly — not with vanity metrics. Good fit for teams 10–100 engineers who've rolled out AI tools and aren't sure if they're helping.

    05

    We help you pick the right problems, avoid the expensive wrong ones, and build a pilot that either proves value in 4–6 weeks or tells you to stop. No moonshots, no "AI transformation" decks.

    Saying no is half the work.

    How we work

    The terms of engagement are part of the work.These are ours.

    Scoped engagements, not seats.

    Every project has a defined outcome and end date. If you need ongoing capacity, we'll help you hire for it — not rent it to you indefinitely.

    One client at a time, per engineer.

    When we're on your project, we're on your project. No split attention, no utilization games.

    The people in the pitch do the work.

    No hand-offs, no delivery teams you've never met. You get the engineers you hired.

    We'll tell you when it's smaller than you think.

    Our goal is a client who comes back, not a timeline we stretch.

    How we build

    Built to last

    Long-term thinking shapes every decision. If we wouldn't want to maintain it in five years, we don't ship it. Not for ourselves, not for clients.

    Security from day one

    Not bolted on after. We think about data, access, and trust before writing code.

    Infrastructure that holds

    Monitoring. Backups. Alerts. The boring stuff that matters at 3am.

    AI where it helps

    Not as a gimmick. Only when it genuinely makes the product better.

    About StackSloth

    StackSloth started by building software we wanted to run ourselves. WedLoop and Navver are still live, still pay rent, and still page us when something breaks. That's what clients hire.

    Small by design. Senior by default.

    The principles in "How we work" aren't aspirations. They're what we deliver — because the person in the pitch is the person on the keyboard.

    "Sloths aren't slow — they're deliberate. They don't waste a move. Most software does the opposite."

    We help you ship less.

    Who you're hiring

    StackSloth is one person — by design.No account managers, no delivery teams.Just the operator behind it.

    Dan Slapelis

    Dan Slapelis

    Founder

    11 years in industry. Cybersecurity degree from RIT. Started on bare-metal infrastructure — storage arrays and compute blades — then moved into consulting: Kubernetes rollouts, CI/CD, Python apps, the messy middle of getting code to production. Most recently at Intuit Credit Karma, running cloud infrastructure and building AI agents and RAG systems that did real work.

    Now: building web applications and custom software for businesses, plus the supporting infrastructure and alerting that keep them running. Specializing in secure AI agents — not demos, but ones trusted with real systems and real data.

    Applied AI EngineerSoftware EngineerDevOps Engineer

    Say hello

    Have a product that needs shipping? An architecture that needs a second opinion? Let's talk.