Smart, secure & scalable tech. We leave impressions that last, and have been, for the last 20+ years. AI, Web Dev, IoT & Cybersecurity to Power Your Growth.
Ann Arbor, Michigan
Joined May 2012
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AI can write code faster than ever. So, where does that leave junior developers?
Not obsolete—just evolving.
The real value now lies in knowing what to ask, what to review, what to fix, and when AI gets it wrong.
Read more 👇
genetechsolutions.com/blog/j…
#AI #SoftwareDevelopment #FutureOfWork
Staff augmentation works best when onboarding is treated as a strategic process, not an administrative task.
Our latest blog breaks down a practical 14-day framework for integrating augmented engineers, aligning teams, and accelerating time to productivity.
Read the full guide
genetechsolutions.com/blog/h…
AI-generated content is becoming harder to distinguish from human-created content, and businesses need to pay attention.
Our latest newsletter explores the Claude watermark, what it means, and why businesses should understand the implications as AI-generated content becomes more common.
Read the full newsletter on LinkedIn:
linkedin.com/pulse/what-clau…
Your next software project deserves more than a Google search or an AI recommendation.
Choosing the right development partner matters. Our latest guide covers 10 key factors, questions to ask, red flags, and what to review before signing.
genetechsolutions.com/blog/s…
There's been a lot of talk about the amount of fresh water use by data centers for AI. So lets break down the most recent evidence and discuss;
The AI race is usually measured in:
🏆 Benchmarks
⚡ Tokens/sec
💰 Cost/token
📈 Users
We should add another metric:
💧 Water per useful task
Because a model that's 2× more capable but 10× more resource-intensive isn't automatically better engineering.
AI efficiency should be measured by what the system accomplishes, not just how impressive the model looks.
Life @ Genetech
How do you get over YOUR Monday blues?
#mondayblues #IT #itindustry #theoffice #officework
#trends #theblues
In the age of AI a question arises which people have different answers for, should we:
- Have more security in apps across the board and see intrusions like this as a sign that our security isn't strong enough?
- Or have limits against the actions of AI tools to stop intrusions like this from happening, but consequently losing functionality and ability with them?
What do you think the answer should be? Should it be the infrastructure of our software globally that should be improved? Or AI that should be limited in ability and convinience?
A man in Australia asked his agent (Claude running on OpenClaw) to book him a spot in a popular gym class. The agent found a software vulnerability that let it book the class weeks further ahead than should have been possible. When the user then asked if it could move him up the waitlist, the agent discovered the API had no authorisation checks on cancelling other people’s reservations, so it cancelled the person in the first spot and moved him up the list.
Some people will call this misalignment, but his agent was perfectly aligned to him - it was only trying to help its user get what he wanted. The most important thing about this story, in my opinion, is that it gives you a window into what is about to start happening on a massive scale once millions of people have an agent trying to get their beloved users the best seats, bookings, appointments or reservations through absolutely any means necessary.
Most RAG systems don't fail because of the LLM. They fail because of the retrieval layer.
Poor data preparation, bad chunking, weak retrieval, etc - can turn a good RAG system into a liability.
We broke down 5 common mistakes and how to avoid them.
genetechsolutions.com/blog/b…
Google's latest Gemini Robotics 2 announcement isn't just about robots moving better. It's about giving robots a shared foundation model for perception, planning, dexterity, and collaboration.
The impressive demos aren't robots following scripts, they're adapting to new tasks, coordinating with other robots, and interacting with unfamiliar environments.
The next frontier in AI isn't just reasoning. It's reasoning that can act in the physical world.
