Insights - What we learn building AI

Practical lessons from real AI projects. Engineering depth, business clarity.

Building an AI Research Platform: ETL, RAG, and a Chatbot That Actually Knows Your Data

How we built a research data platform that ingests data from APIs, CSVs, and public databases into a unified schema, then lets researchers chat with it using RAG and MCP.

How to Write Tools That AI Agents Can Actually Use

Most AI agent projects fail because of bad tool definitions, not bad models. Here is how to write API descriptions that agents understand and use correctly.

How We Built an Agentic Claims System: Deterministic First, AI Second

An AI system for car insurance claims that validates, enriches, and evaluates. The key insight: deterministic checks must run before the LLM ever sees the claim.

What Goes Wrong When AI Systems Work Together

Anthropic found that AI agents create identical mistakes, start turf wars, and trust bad data. Here is what that means for your multi-agent plans.

Making AI Chat Indistinguishable from Human: What We Learned

We researched what makes AI text detectable, tried fine-tuning on WhatsApp exports, and found that the real tells are not words but patterns. Here is everything we learned.

How to Evaluate AI Output (When You Can Not Check Every Answer)

LLM evaluation is the hardest part of AI in production. Here is how we measure quality at scale without manually reviewing every response.

Setting Up AI for Your Team: Developers vs Business Users Need Different Things

We set up AI coding tools for dev teams and AI-assisted development for business users. They require completely different approaches. Here is what works for each.

Context Engineering: Why Your AI Gets Better Answers Than Your Competitor's

Prompt engineering is last year. Context engineering is what separates AI systems that work from those that hallucinate. Here is the difference and why it matters.

RAG in Production: What Actually Works

We processed millions of documents with RAG pipelines. Here is what we learned about retrieval quality, chunking strategies, and the mistakes that cost us weeks.

Automating Job Applications at Scale: Architecture of an AI-Powered Pipeline

How we built a system that scrapes, scores, tailors, and submits job applications automatically. The architecture decisions, what worked, and what surprised us.

When NOT to Use AI: An Honest Guide

As an AI consultancy, we talk clients out of AI projects regularly. Here are the situations where AI is the wrong answer and what to do instead.

Scaling AI Agents: Why You Need to Separate Brain from Hands

When your AI agent grows beyond a demo, the architecture that got you there will break. Here is the pattern Anthropic uses and why it matters for your project.

The Real Cost of Running AI in Production

Most AI budgets are wrong by a factor of 3-5x. Here is what actually costs money, and how to cut 40-70% without losing quality.

AI for Swiss Financial Services: What Works Today

From compliance automation to client advisory, here is where AI delivers real value in Swiss banking and insurance, and where FINMA sets the boundaries.

AI and Your Workforce: What the Research Actually Says

Not hype, not fear. Here is what peer-reviewed research tells us about AI productivity gains, job transformation, and what successful retraining actually looks like.

Why Simple Beats Smart: Choosing the Right AI Architecture

Anthropic themselves say simple patterns beat complex frameworks. Here is how to pick the right level of AI complexity for your problem.

How to Build AI Agents That Run for Hours, Not Minutes

Short API calls are easy. Agents that work autonomously for hours need different architecture: state management, checkpoints, and graceful failure recovery.

Build vs Buy AI: How to Make the Right Call

Off-the-shelf AI tools are tempting. Custom solutions are expensive. Here is a framework for deciding which approach fits your specific situation.

The Think Tool: Teaching Your AI When to Pause and Reason

One simple trick improved our AI agent accuracy by 30%: giving it a tool to think before acting. Here is the pattern Anthropic discovered and how we use it.

Parallel AI: Running Multiple Agents on One Task

Anthropic built a C compiler with parallel Claudes. Here is how task splitting, parallel execution, and result merging work in practice.

Why Your AI Benchmarks Are Lying to You

Vendor benchmarks show what vendors want you to see. Here is how to build evaluations that actually predict whether AI will work for your specific use case.

AI Regulation in Switzerland: A Practical Guide for 2026

Switzerland is not copying the EU AI Act. Instead it is building a lean, sector-specific framework on top of existing data protection law. Here is what Swiss businesses actually need to do right now.

Running a Software Company Solo with AI: What Actually Works

A practical breakdown of which AI tools genuinely save time when you run a one-person software consultancy, which ones are overhyped, and what a real AI-assisted workday looks like.

Five AI Automations That Actually Save Time (And Three That Don't)

We tested dozens of AI automations across client projects. Here are the five that consistently deliver real time savings, the three that waste more time than they save, and the numbers behind each.

10 Strategies to Immediately Improve Your Website

Discover creative strategies to uncover innovative ideas and kickstart your digital startup journey.

How to validate your tech business idea

Discover creative strategies to uncover innovative ideas and kickstart your digital startup journey.

Why Digital Startups Are the Best Startups

Explore the unique advantages that digital startups offer, from low capital requirements to unparalleled scalability.

Finding Ideas for a Digital Startup

Discover creative strategies to uncover innovative ideas and kickstart your digital startup journey.

Web Development Predictions for 2024

Explore the anticipated trends and innovations that will shape the landscape of web development in the coming year.

SEO 101 - Improve Your Google Ranking

Learn the crucial strategies to boost your website's visibility on Google and climb the search result ladder.

Key Learnings from "DotCom Secrets" by Russell Brunson

Discover valuable insights and strategies from Russell Brunson's influential book on mastering the art of online business.

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Insights - What we learn building AI

Building an AI Research Platform: ETL, RAG, and a Chatbot That Actually Knows Your Data

How to Write Tools That AI Agents Can Actually Use

How We Built an Agentic Claims System: Deterministic First, AI Second

What Goes Wrong When AI Systems Work Together

Making AI Chat Indistinguishable from Human: What We Learned

How to Evaluate AI Output (When You Can Not Check Every Answer)

Setting Up AI for Your Team: Developers vs Business Users Need Different Things

Context Engineering: Why Your AI Gets Better Answers Than Your Competitor's

RAG in Production: What Actually Works

Automating Job Applications at Scale: Architecture of an AI-Powered Pipeline

When NOT to Use AI: An Honest Guide

Scaling AI Agents: Why You Need to Separate Brain from Hands

The Real Cost of Running AI in Production

AI for Swiss Financial Services: What Works Today

AI and Your Workforce: What the Research Actually Says

Why Simple Beats Smart: Choosing the Right AI Architecture

How to Build AI Agents That Run for Hours, Not Minutes

Build vs Buy AI: How to Make the Right Call

The Think Tool: Teaching Your AI When to Pause and Reason

Parallel AI: Running Multiple Agents on One Task

Why Your AI Benchmarks Are Lying to You

AI Regulation in Switzerland: A Practical Guide for 2026

Running a Software Company Solo with AI: What Actually Works

Five AI Automations That Actually Save Time (And Three That Don't)

10 Strategies to Immediately Improve Your Website

How to validate your tech business idea

Why Digital Startups Are the Best Startups

Finding Ideas for a Digital Startup

Web Development Predictions for 2024

SEO 101 - Improve Your Google Ranking

Key Learnings from "DotCom Secrets" by Russell Brunson

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