Insights, tutorials, and updates from the Mogryat team.
A practical six-stage workflow for taking an app from idea to launch with AI: clarify, brief, scope, architecture, build in small tasks, and learn.
Why AI coding agents forget your project between sessions, and a three-layer context system (rules, specs, task briefs) that works with any tool.
A system for running several freelance software projects with AI: one workspace per client, scoped tasks, a weekly rhythm, and change requests in writing.
A one-page checklist to plan your MVP before opening Lovable, Bolt, or Cursor, so every prompt and credit goes toward the product you actually want.
Turn messy client notes into scoped development tasks with AI in three passes, with prompts and acceptance criteria your client can actually sign off.
Write a PRD with AI the right way: let it interview you, draft section by section, turn requirements into acceptance criteria, then use it as a critic.
Where tokens go in AI-assisted development and nine tactics to cut waste: scoped tasks, fresh sessions, lean context, model routing, and caching.
Spec-driven development vs prompt-driven (vibe) coding: how they differ, where each breaks down, and a simple per-task rule for choosing.
A five-step process for scope changes in AI-assisted client work: log, classify, break into tasks, estimate, and approve before anything gets built.
Ten common mistakes non-technical founders make when building apps with AI, from building before planning to skipping security, and what to do instead.
How to run multiple AI coding agents on one codebase without conflicts: independent tasks, isolated branches, shared context, and gated merges.
How solo builders keep several AI-assisted projects moving: a per-project context kit, active-project limits, and a switching ritual that saves time.
What it really costs to build an MVP with AI: tools, API usage, hosting, fees, expertise, and time, with a worked example and a budget worksheet.
Eight practices freelancers use to cut rework and AI token spend across client projects, from confirmed acceptance criteria to per-client context packs.
Manage AI coding agents and AI-assisted developers without reading code: small tasks, acceptance criteria, review trails, and the right questions to ask.
How to produce project documentation and a client handover pack with AI from artifacts you already keep, and how to test it before you hand over.
A practical system for solo developers to ship faster with AI: one outcome per release, a boring stack, automated setup, small tasks, and a weekly rhythm.
Cursor, Claude Code, and Kiro compared on workflow, persistent context, and planning, based on each tool's documentation, with guidance on choosing.
A step-by-step guide to turning a business idea into a scoped MVP with AI: name the riskiest assumption, get interviewed, write a brief, and cut scope.
Build a working app with AI without coding: choose the right route, plan the first version, build one feature at a time, and test it like a user.
Most AI tools generate code from a prompt. Mogryat does something fundamentally different — it orchestrates the entire product development journey from idea to deployed application.
You don't need to be a developer to build an app. With Mogryat's end-to-end platform and simple integrations with GitHub, AWS, and AI coding agents, you can focus on what matters: your business idea and validating it with real users.
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