Case Studies
Real stories of AI applied to real business problems. Not theory, not hype — proof of capability from the field. Each case study covers what happened, what went wrong, what worked, and what it means for your business.
One AI assistant on one Mac, eight months later a messaging app, a solar controller, wildlife reels, websites and a small specialist team. This is the story, told cinematically — the capstone of everything we've built.
How a personal side project became the fastest-growing open-source project in history — and what it tells us about the age of AI agents. The origin story, the explosion, the crisis, and the foundation.
6 mo
1M → 700K DAU
300K+
GitHub stars
$0
Marketing budget
The real journey from pay-per-token burn to a multi-provider AI team running 24/7. The costs, the rate limits, the subscriptions, the free-tier discoveries — and what it means for your business.
8+
AI Providers
67%
Cost reduction
9
Specialist agents
We asked our AI team to build a messaging app. Five versions, multiple restarts, database corruption, and hard lessons about modularity, process, and agent boundaries. The BeeChat story.
5
Versions
3
Major restarts
81
Tests passing
From one solar dashboard to thirty automated jobs running research, email triage, security, memory, and synthesis — without anyone asking them to. What happens when you stop doing the work and start building the system that does it.
30
Automated jobs
6
AI agents
24/7
Self-operating
We're building a knowledge graph tool using the same process we sell. 14 formal decisions, every rationale documented, every spike tested before code. The case study is the proof of work — the project is the proof of concept.
14
Decisions documented
5
Model providers reviewed
0
False positives
Two agents needed to communicate. The simplest approach — write a JSON file — became a protocol, a product, and 823 passing tests. Gate-by-gate development, adversarial review, and the story of how simple beats clever.
823
Tests passing
20
Delivery gates
2
Agents live
A live home-energy dashboard became a locally controlled, safety-engineered system. Read locally, act locally, verify the result, fail safe — and let 182 days of real winter use shape what happens next.
182
Winter days of data
2/2
Charge + discharge proven
25 pts
Floor-limited discharge
Each case study is a standalone deep-dive — structured differently to match the story, but always covering the real details: context, crisis, resolution, and lessons.
Who, what, and why it started. The context that makes the story matter.
What went wrong, what went right, and what nobody expected.
What actually happened. Data, timelines, decisions, and outcomes.
What this means for your business. Actionable takeaways, not platitudes.