SaaS Development

Software as a Service strategies and development

The £400+ an Hour AI Disaster Cleanup Business

An entertaining and brutally honest look at the booming industry of fixing AI-generated code disasters. For the first time in history, experienced developers are outearning law firms. Covers why we are now charging £400 per hour to clean up the mess left by agencies and developers who thought AI meant they did not need to know what they were doing. Explores the complete absence of TDD and BDD in vibe-coded projects, how fixing one thing breaks three others when there are no tests, the nightmare of undocumented AI-generated spaghetti, why companies end up paying three times more to fix than they would have paid to build properly, and how AI actually should be used by people who understand software development. A celebration of the new gold rush for senior developers and a warning for companies considering the cheap route.

AISaaSeCommerceGrowth Hacking

Why Companies Hire Me (And Why I Could Never Go Back to Nine to Five)

A personal and philosophical exploration of why companies choose to work with contractors over employees, and why the conventional explanation misses the point entirely. Discusses how employment law around working hours is the real driver, the ability to work marathon sessions when deadlines demand it, delivering complex solutions rapidly for clients like Deliveroo and Selfridges, the focused deep work that comes from loving what you do, and the freedom trade-off that makes it all worthwhile. An honest look at contractor life, pricing, and why some of us could never trade this chaos for the safety of a predictable schedule.

Growth HackingSaaSeCommerce

Time to Market: The Critical Path to Shipping Products That Matter

A comprehensive guide to shipping products faster without sacrificing what matters. Covers critical path methodology and how to identify what actually blocks launch, the over-engineering trap and why perfect is the enemy of shipped, QA reality and accepting that users will break things you never imagined, the trust the process mindset for working under pressure, time management strategies for maintaining quality under deadline pressure, why customers must define design and logic instead of management teams in meeting rooms, maximising profit by minimising waste, and testing products with real users before committing massive budgets. Includes detailed examples from e-commerce, SaaS, fintech, and agency work with multiple perspectives on each principle.

Growth HackingSaaSeCommerceMarketing Automation

The Complete Guide to Digital Marketing Testing Methods

A comprehensive deep dive into every major testing methodology used in digital marketing. Covers running without tests, A/B testing with two variants, multi-split testing with three or more variants, multivariate testing for element combinations, holdout control groups for measuring incremental lift, geographic split testing for regional campaigns, audience split testing for segment-specific optimisation, and sequential time-based testing for low-traffic scenarios. Each method includes detailed explanations of when to use it, statistical requirements, implementation considerations, advantages and disadvantages, and real-world examples across e-commerce, SaaS, fintech, travel, and retail industries.

Growth HackingStatisticsMarketing AutomationeCommerceSaaSData Science

Is AI Another Dot Com Bubble Waiting to Burst?

A balanced, in depth analysis of whether AI represents another dot com style bubble or a genuine technological revolution. Examines the financial reality of 700 billion dollars in annual spending against actual revenue, explores whether we are using AI correctly or just bolting chatbots onto everything, investigates why most startups are recycling old ideas as wrappers, identifies where AI is genuinely transformative (small custom solutions, problems blocked by thinking power, cost barriers), explains why Meta and Google are rehiring developers despite AI hype, exposes hidden costs in inference, error checking, and implementation, and dissects the benchmark gaming problem of tokenmaxxing. A grown up verdict that acknowledges both the bubble and the real technology underneath.

AIMachine LearningGrowth HackingSaaSeCommerce

Onboarding and Habit Formation: The Science of Making Products Stick

A comprehensive deep dive into the psychology and mechanics of user onboarding and habit formation. From finding your product's Aha moment through cohort analysis to Nir Eyal's Hook model, James Clear's habit stacking, the Zeigarnik effect, endowed progress effect, and goal gradient effect. Includes Chamath Palihapitiya's Facebook growth team methodology, research data, Python code for measuring activation, and practical implementation strategies.

Consumer PsychologyGrowth HackingSaaSData ScienceMarketing Automation

Conversion and UX Psychology: The Science of Why Users Click or Bounce

A comprehensive deep dive into the psychological laws that govern user behaviour and conversion. From Hick's law and Fitts's law to the peak-end rule, serial position effect, Miller's law, cognitive load theory, friction frameworks, and attribute framing. Includes research data, Python code for measuring UX impact, and practical implementation strategies backed by Baymard Institute research.

Consumer PsychologyGrowth HackingeCommerceSaaSData ScienceStatistics

Behavioural Economics Frameworks: The Science of How Customers Actually Decide

A comprehensive deep dive into the behavioural economics frameworks that shape consumer decisions. From Kahneman's dual process theory to Thaler's choice architecture, cognitive biases, hyperbolic discounting, mental accounting, choice overload, and status quo bias. Includes when each framework applies, how to design for real human behaviour, and Python code for measuring effectiveness.

Consumer PsychologyGrowth HackingData ScienceeCommerceSaaS

Referral and Viral Mechanics: Engineering Exponential Growth

A comprehensive deep dive into the mathematics and psychology of referral programmes and viral growth. From K-factor calculations to viral cycle time, two-sided incentives, network effects versus viral effects, referral psychology, Jonah Berger's STEPPS framework, and NPS as a growth predictor. Includes Python code for modelling viral growth and measuring programme effectiveness.

Growth HackingGrowth HacksConsumer PsychologySaaSeCommerceData Science

Vibe Coding: The Hidden Cost of AI Built Architectures

A deep dive into the fundamental architectural flaws that emerge when systems are built with AI assistance but without proper planning. Covers database architecture failures, scaling bottlenecks, framework selection mistakes, and the real limitations of popular Python frameworks (Django, Flask, Streamlit, Gradio, Plotly Dash, FastAPI, Reflex) when projects grow. Includes analysis of rapid development frameworks, language selection criteria, and why certain technical choices create insurmountable problems at scale. Real examples of where architectural debt catches up with you.

SaaSeCommerceGrowth HackingAI

The Math Behind It All: Growth Marketing Mathematics Explained

A comprehensive deep dive into the mathematics that powers growth marketing and data-driven decision making. From LTV:CAC ratio and payback period to cohort analysis, survival analysis with Kaplan-Meier curves, Bayesian A/B testing, multi-armed bandits with Thompson sampling, marketing mix modelling vs attribution, power law distributions, price elasticity with Van Westendorp's price sensitivity meter, and the compounding math of retention. Includes LaTeX formulas, Python code, visual explanations, and practical implementation guidance for both beginners and advanced practitioners.

Data ScienceGrowth HackingStatisticsSaaSeCommerceMarketing Automation

Less Well Known but Battle Tested: The Hidden Psychology That Actually Converts

A comprehensive deep dive into 18 lesser-known but highly effective psychology principles for conversion and retention. From goal-gradient acceleration and temporal landmarks to identity-based marketing, implementation intentions, foot-in-the-door, labour illusion, operational transparency, defaults as nudges, status games, sunk cost retention, social comparison, reactance, and risk reversal. Includes research data, Python code for measuring impact, and practical implementation strategies backed by academic literature.

Consumer PsychologyGrowth HackingGrowth HackseCommerceSaaSData ScienceMarketing Automation

TDD and BDD for APIs: When Your Web Apps Need to Talk to Each Other

A deep dive into test driven and behaviour driven development for APIs that connect separate web applications. Covering the unique challenges of distributed systems, contract testing, consumer driven contracts, and how proper testing becomes your most reliable documentation. With detailed comparisons of testing tools for Ruby on Rails and Django.

eCommerceSaaSGrowth Hacking

The £35,000 Lesson: When AI Generated Code Meets Production

A brutally honest account of what happens when your integration partners decide to let AI write their entire codebase. Two real projects, one in the US and one in the UK, have cost my clients over £35,000 in the past month alone. This is the story of why I built ai-code-detector and why the industry needs to wake up.

AIeCommerceSaaS

Why Rapid Development Frameworks Destroy PHP In The Long Run

A brutally honest deep dive into why Ruby on Rails and Django absolutely demolish PHP and other legacy frameworks over time. Covering security, scalability, and most importantly the testing ecosystem that makes bug free releases actually possible. Featuring TDD, BDD, Minitest, RSpec, and Cucumber with real world examples.

eCommerceSaaSGrowth Hacking

Dynamic Pricing With AI: A Growth Hacker's Guide

The dynamic pricing software market is projected to grow from $6.16 billion in 2025 to $41.43 billion by 2033, and 55% of retailers plan to implement AI pricing in 2026. Amazon changes prices 2.5 million times a day. You don't need to be Amazon. This post breaks down how ML-driven dynamic pricing actually works - price elasticity estimation, demand signals, competitor monitoring, and margin guardrails - with practical Solidus/Rails code and Python scripts you can run today.

Machine LearningeCommerceGrowth HackingData ScienceSaaS

AI-Powered Demand Forecasting for eCommerce

IKEA's Demand Sensing tool halved their forecast error rate from 8% to 2% by using up to 200 data sources per product. That's what AI-powered demand forecasting looks like at scale. But you don't need IKEA's budget to get meaningful results. This post compares three forecasting approaches - Prophet, SARIMA, and XGBoost - with practical examples from Solidus ecommerce and custom SaaS, showing which model works best for which scenarios and how to implement them in a Rails-based product stack.

Machine LearningeCommerceData ScienceAISaaS

AI Compliance for the DACH Market

If you're building AI-powered SaaS for the DACH market, you're not dealing with one regulatory framework. You're dealing with at least five: the EU AI Act (directly applicable in Austria and Germany), GDPR (enforced differently by each country's DPA), Austria's Digital Austria Act 2.0 and KI-Servicestelle, Germany's KI-MIG implementation law and Bundesnetzagentur oversight, and Switzerland's entirely separate FADP with its own rules on AI, profiling, and personal liability. This post maps the specific nuances for Austrian, German, and Swiss businesses, shows where the regulations overlap and where they diverge, and provides the practical architecture decisions that let you ship AI features across all three markets from a single Rails codebase.

AIGDPRDACHSaaSMachine Learning

Building GDPR-Compliant AI Features in Your SaaS

A developer's practical walkthrough of Data Processing Agreements, Privacy by Design, and Data Protection Impact Assessments for AI features. Not the legal theory, the actual Rails code and architecture decisions you need to make before shipping AI features to production. With real examples from four production Ruby on Rails applications: GrowCentric.ai (marketing optimisation), Stint.co (marketing dashboard), Regios.at (regional platform), and Auto-Prammer.at (automotive marketplace on Solidus).

AIMachine LearningGDPRSaaSMarketing Automation

GDPR and AI: The "Right to Be Forgotten" Now Means "Unlearning"

When GDPR's Article 17 was written, 'erasure' meant deleting a row from a database. In 2026, it means something far more complicated. If a user's data was used to train an AI model, deleting the database record isn't enough. The data has been absorbed into model weights, influencing predictions for every subsequent user. The EDPB has made right to erasure its coordinated enforcement priority for 2025-2026, with 30 data protection authorities investigating how organisations handle deletion requests. And the Italian DPA already fined OpenAI 15 million euros for, among other things, failing to handle training data properly under GDPR. This post explains what machine unlearning is, why it's a nightmare for developers, and what practical architectural decisions you can make right now to avoid the problem in the first place.

AIMachine LearningGDPRSaaSData Science

The EU AI Act Kicks In August 2026: What SaaS Builders Need to Know

The EU AI Act's biggest enforcement date is August 2, 2026. That's less than five months away. High-risk AI system obligations, transparency rules, and the full enforcement framework all go live on that date. If you build SaaS products that use AI and serve European customers, this directly affects you. This post explains the four risk tiers, how to figure out which one your product falls into, what the obligations actually mean in practice, and what you should be doing right now. No legal jargon. Practical guidance from someone building AI-powered SaaS for the European market.

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AI-Powered Marketing Automation: Beyond Email Drips

Most marketing automation in 2026 is still glorified email scheduling. Send this email on day 3. Send a follow-up on day 7. If they click, send offer A. If not, send offer B. That is not AI. That is a flowchart. Real AI-powered marketing automation means dynamic pricing that adjusts to demand in real time, personalised product recommendations that learn from behaviour, predictive churn detection that intervenes before customers leave, and autonomous campaign optimisation that reallocates budget without waiting for a human to notice what is happening. This is what I am building with GrowCentric.ai, and this is what I implement for ecommerce clients on Rails and Solidus.

AIMachine LearningMarketing AutomationeCommerceSaaS

How to Actually Integrate AI Into Your Existing Workflows (Without Breaking Everything)

Most AI projects fail. Not because the technology is bad, but because the data is messy, the systems are old, and nobody knows where to start. Gartner predicts that 60 percent of AI projects will be abandoned due to poor data quality. This is the where do I even start post. Data quality, legacy systems, realistic first steps, and real examples from Rails, Solidus, and SaaS projects I have actually built.

AIMachine LearningeCommerceSaaSData Science

AI Agents vs Chatbots: What Actually Changed in 2026

Everyone is talking about AI agents in 2026, but most people still confuse them with chatbots. The difference is not cosmetic. Agents book flights, purchase groceries, manage inventory, and negotiate with other agents, all without a human clicking a single button. This post explains what actually changed, shows real examples of agents in action, breaks down the protocols making it all work, and explains what it means if you build ecommerce on Rails and Solidus or run a SaaS.

AIMachine LearningeCommerceSaaS

Agentic AI for eCommerce: What It Actually Means, Why It Matters, and How to Build It on Rails and Solidus

Agentic AI is the biggest shift in ecommerce since the smartphone. AI agents that autonomously manage inventory, handle customer support, route orders, and optimise pricing are already reshaping how online businesses operate. But what does agentic actually mean in plain English? How is it different from a chatbot? And how do you build these systems on Ruby on Rails and Solidus? A practical guide from someone who is building this right now.

AIMachine LearningeCommerceSaaS

Building Custom AI Recommendations in Solidus

A technical but accessible walkthrough of adding ML-powered product recommendations to Solidus, the open-source Ruby on Rails ecommerce framework. Covers three recommendation approaches (collaborative filtering, content-based, and hybrid), complete with Python ML scripts, full Solidus/Rails integration code, event tracking, cold start handling, A/B testing, GDPR compliance, and the honest limitations and pitfalls you'll hit along the way. No black boxes - every piece is explained and every trade-off is named.

Machine LearningeCommerceAIData ScienceSaaS

TDD and BDD in Ruby on Rails: How to Ship Without Fear, and How AI Is Changing the Game

A deep dive into Test Driven Development and Behaviour Driven Development in Ruby on Rails. What they are, how they differ, why they exist, and how they prevent the costly bugs that plagued the old way of building software. Includes a detailed comparison of RSpec, Minitest, and Cucumber, practical examples from building Auto-Prammer.at on Solidus and the Regios fintech SaaS powered by GrowCentric.ai, plus a best practice guide for using AI tools like Claude to supercharge your testing without losing control.

AISaaSeCommerceData ScienceMachine Learning

The EU Cyber Resilience Act Is Coming: What It Means, Who Needs to Prepare, and How I Can Help

The EU Cyber Resilience Act entered into force in December 2024, with reporting obligations kicking in September 2026 and full enforcement by December 2027. If you build, sell, or distribute software or connected products in the EU, this affects you. Here is what you need to know, what you need to do, and how a Growth Hacker and SaaS developer with cybersecurity experience can help you get compliant.

GDPRSaaSeCommerceMarketing Automation

Why I Left the Google Ads Partner Programme and Why You Might Want to as Well

For years, I was a certified Google Ads Partner. Not because I wanted the badge, but because I thought it gave my clients confidence. After all, the label implied expertise, accountability, and a seal of quality from the biggest name in digital advertising. But recently, I let the certificate expire. Not due to a lack of ad spend. Not due to a lack of expertise. But because remaining a Google Ads Partner increasingly comes at a cost, one paid by the client.

Growth HackingSaaSeCommerce