Deep Tech Software Development: From Innovation to Product
Not every business process deserves an AI agent. Some need better automation, while others require software that can interpret information and take action. This article examines where AI agents create measurable value, when custom development makes sense, and how businesses can avoid investing in unnecessary complexity.
Fractional CTO for SaaS Companies
Table of contents Fractional CTO for SaaS Companies: When Growth Exposes Technical Gaps A SaaS product that works well for 100 customers may struggle when that number reaches 1,000. Not necessarily because the original technology was poorly built, but because the decisions that made sense during development may no longer support the business. In the […]
7 Design System Examples Product Teams Can Learn From in 2026
Table of contents 7 Design System Examples Product Teams Can Learn From in 2026 The best design system examples do more than show you what buttons, forms, and navigation should look like. They show how experienced product teams make recurring design and engineering decisions once, document them, and reuse them as the product grows. That […]
PedalsUp Has Evolved: The Story Behind Our Rebrand
Table of contents PedalsUp Has Evolved: A New Identity for the Work We Do Today PedalsUp has evolved, and our new identity is a reflection of that change. When PedalsUp started in 2018, our focus was on helping businesses build software products and bring their technology ideas to life. Over the years, that work expanded […]
AWS Lambda MicroVMs: Pricing and Architecture Guide
Table of contents AWS Lambda MicroVMs: An Honest Guide to Pricing and Tradeoffs If you’re building a product where users or AI agents run arbitrary code, you’ve probably hit the same wall every team eventually hits: isolating that code safely is expensive to build and easy to get wrong. AWS Lambda MicroVMs, which became generally […]
Legacy App Modernization: Refactor, Rebuild, or Replace?
Before a site or app goes live, Pedals Up runs rigorous QA workflow augmented by LLM + RAG. We ground model outputs in your tickets, specs and logs to generate traceable triage, auto-updated tests, accessibility checks and release-ready docs—so launches go smoothly and issues stay out of production.
Onboarding UX That Works: Key Principles for Better Activation
Before a site or app goes live, Pedals Up runs rigorous QA workflow augmented by LLM + RAG. We ground model outputs in your tickets, specs and logs to generate traceable triage, auto-updated tests, accessibility checks and release-ready docs—so launches go smoothly and issues stay out of production.
How Software Development Is Changing with Agentic Coding
Before a site or app goes live, Pedals Up runs rigorous QA workflow augmented by LLM + RAG. We ground model outputs in your tickets, specs and logs to generate traceable triage, auto-updated tests, accessibility checks and release-ready docs—so launches go smoothly and issues stay out of production.
Next.js 16.0.1: A Complete Guide for Modern Web Teams
Before a site or app goes live, Pedals Up runs rigorous QA workflow augmented by LLM + RAG. We ground model outputs in your tickets, specs and logs to generate traceable triage, auto-updated tests, accessibility checks and release-ready docs—so launches go smoothly and issues stay out of production.
The Hidden Cost of “Vibe Coding”: Why Hard Engineering Still Matters
Before a site or app goes live, Pedals Up runs rigorous QA workflow augmented by LLM + RAG. We ground model outputs in your tickets, specs and logs to generate traceable triage, auto-updated tests, accessibility checks and release-ready docs—so launches go smoothly and issues stay out of production.