Engineering blog
What we have learned building AI systems and software products in production: costs, architecture decisions and the parts demos skip. Written by the engineers who do the work.
Latest articles
Stripe subscription webhooks that don’t double-bill: idempotency, ordering and scheduled downgrades
Why subscription billing breaks in production, and the five patterns that fix it: event de-duplication, ordering-safe handlers, Stripe as source of truth, scheduled downgrades and payment-failure grace periods.
Startups & MVPsMigrating off Bubble to real code: when it’s worth it and how to do it without losing users
The signs you have outgrown Bubble, what you can and cannot take with you, and a step-by-step plan for moving live users, data and Stripe subscriptions to a coded stack.
AI chatbotsHow much does an AI chatbot cost? Build price, running cost and when not to build one
Off-the-shelf tool, configured platform or custom build — what each costs, what moves a custom quote, and worked token arithmetic for running a chatbot at current API prices.
AI agentsHow to choose an AI development company: 12 questions that separate production teams from demo builders
A buyer’s checklist for AI projects: the questions to ask about evaluation, data, cost, ownership and hand-over — and the answers that should make you walk away.
AI agentsAI agent vs chatbot vs automation: which one does your business actually need?
Plain definitions, a side-by-side comparison and a decision table — plus why most good "AI agents" are mostly ordinary automation with AI in two or three steps.
MCP & AI integrationBuilding a production MCP server for your SaaS: auth, tool design and lessons from ~115 tools
What it actually takes to put a Model Context Protocol server in front of a real product: remote transport, OAuth, permission scoping, tool design and testing with real clients.
AI agentsHow much does it cost to build an AI agent? A breakdown from real builds
The two bills behind every AI agent — building it and running it — with the drivers that move each, and worked token-cost arithmetic at current API prices.
AI engineeringFrom AI proof of concept to production: what demos skip
The gap between an AI demo and a feature you can ship: evaluation sets, judges you can trust, structured output, permissions, cost tracking, fallbacks and a gradual rollout.
AI engineeringRAG vs fine-tuning for business knowledge: a decision framework
When to retrieve, when to fine-tune, when to do both — and the retrieval failures that actually decide whether your AI answers are right.
Startups & MVPsHow much does a SaaS MVP cost? What actually moves the number
Our honest range, the seven drivers that move it, what you should never cut, and the running costs that arrive after launch.
AI engineeringHow to add AI features to an existing SaaS without a rewrite
The engineering playbook we use to ship LLM features inside existing products: what to build first, the architecture defaults, tenancy, privacy and rollout.
Developer tutorials
Claude vs Cursor: Which AI Coding Tool Is Better?
A detailed comparison of Claude and Cursor for software development — code generation, debugging, workflow integration, and pricing.
CSS Grid vs Flexbox: When to Use Which
A comparison of CSS Grid and Flexbox for building responsive layouts.