Expert insights on AI, software engineering, UX design, agile, and the craft of building great software.
How Pepla uses Flutter to build natively compiled iOS and Android apps from a single codebase.
Composition API, Pinia state management, and production patterns for Vue.js applications.
Pepla's primary back-end technology — minimal APIs, DI, EF Core, and patterns that scale.
Service discovery, API gateways, RabbitMQ messaging, and the patterns Pepla uses for enterprise Java.
The decision between hiring full-time and augmenting with external talent isn't always obvious. Here's a framework.
Every month a developer position sits empty costs your business more than just the missing output.
Augmented team members can be productive in days, not months — if you onboard them right.
Product launches create temporary spikes in development demand. Here's how to scale without overhead.
Need a .NET architect for 3 months? Here's how to access specialist talent on demand.
What does a software developer actually do day-to-day? Skills, responsibilities, and career paths explained.
How Pepla uses Claude Code to accelerate development, improve code quality, and ship features faster — without replacing the developer.
SOLID, DRY, KISS — these principles are decades old. Here's why they're more relevant than ever.
Two decades of Agile adoption. What survived, what evolved, and what needs to change.
Vibe coding treats AI as a magic wand. AI-assisted development treats it as a power tool. Here's why the distinction matters.
Every R1 invested in UX returns R100. But how do you measure it, and how do you make the case to stakeholders?
AI can generate code fast. But clean, maintainable code still requires human judgement and engineering discipline.
How to document, analyse, and improve business processes — from swimlane diagrams to value stream maps.
AI won't replace developers — but developers who use AI will replace those who don't. Here's what the role actually looks like in 2026.
The bridge between business requirements and technical implementation — what solutions architects really do.
The pendulum is swinging back. Here's how to decide which architecture actually fits your project.
A comprehensive guide to the SDLC — from requirements gathering through to deployment and maintenance.
From frontier models to enterprise adoption — a comprehensive look at where AI stands today and where it's heading.
Consistency, speed, and quality — how design systems transform the way teams build digital products.
Technical debt isn't just a metaphor. Here are concrete strategies for quantifying and paying it down.
Most sprint planning sessions waste time. Here's a structured approach that respects everyone's time.
100% QA coverage, real-time sentiment analysis, and automated compliance checks — how AI is reshaping contact centres.
Requirements, stakeholders, and process maps — the business analyst's toolkit and daily workflow.
RESTful conventions, versioning strategies, error handling, and documentation — building APIs developers love.
80% of software defects trace back to requirements. Here's how to write requirements that actually work.
Mobile-first isn't just about screen size anymore. It's about context, performance, and user intent.
The complete journey of a software project — every phase, every deliverable, every decision point.
Most AI prototypes never make it to production. Here's the engineering required to bridge that gap.
Beyond the buzzwords — how to build deployment pipelines that are fast, reliable, and maintainable.
Servant leadership, ceremony facilitation, and impediment removal — what the Scrum Master role really entails.
Practical prompt engineering patterns that development teams can use today to get better results from LLMs.
Blockers kill velocity. Here's how Scrum Masters can identify, escalate, and resolve them systematically.
Normalisation, indexing strategies, read replicas, and sharding — patterns that scale from startup to enterprise.
WCAG compliance isn't just legal risk mitigation — it's good design. Here's how to build inclusively.
How AI code review tools catch bugs, enforce standards, and free up senior developers for higher-value work.
Technology is the easy part. The hard part is understanding which processes to transform and why.
SQL injection, XSS, broken auth — practical defences for the most common vulnerabilities in web applications.
Research, wireframes, prototypes, and testing — inside the UX designer's process and deliverables.
Unit tests, integration tests, E2E tests, and load tests — building a testing strategy that catches bugs before users do.
ROI frameworks, cost models, and real examples for executives evaluating AI automation investments.
They're not competitors — they solve different problems. Here's how to choose the right fit.
A full-stack guide to finding and fixing performance bottlenecks — queries, APIs, rendering, and network.
From design tokens to developer handoff — practical Figma workflows that eliminate the designer-developer gap.
Bias, privacy, transparency, and accountability — the practical ethics every AI team needs to address.
Identifying, engaging, and managing stakeholders — the skill that makes or breaks IT project delivery.
Latency, data sovereignty, and cost considerations for SA companies choosing between Azure, AWS, and private cloud.
Pipelines, containers, monitoring, and infrastructure as code — the DevOps engineer's world explained.
Retrieval-Augmented Generation explained — architecture patterns, vector databases, and production considerations.
If your retros produce action items that nobody follows up on, you're doing it wrong. Here's how to fix it.
You don't need a research lab. Five user interviews can uncover 85% of usability issues.
How to build a deployment pipeline that lets you ship to production multiple times a day without fear.
What we learned building a production voice automation platform — the wins, the failures, and the architecture decisions.
How business analysts translate ambiguous business problems into clear, actionable technical specifications.
Scope, schedule, budget, and stakeholders — how project managers keep complex IT projects on track.
Story points, T-shirt sizes, Monte Carlo simulations — which estimation method works for which context.
