Insights

Engineering
GenAI for Production.

Practical insights from the team building agentic systems, RAG pipelines, and AI infrastructure that actually ships.

Jev Explained: How TypeSafe’s Decision Model Fits Into AI Agents

A practical look at typed decisions, calibrated probabilities, agent architecture, and the evidence behind Jev’s performance claims.

Reasoning vs Standard LLMs: When Is It Worth Paying the Thinking Tax?

A local side-by-side benchmark exploring when reasoning models pay off versus standard LLMs — and how to allocate thinking time to task risk.

Code Is Cheap, Context Is Expensive: The Strategic Power of the Forward Deployed Engineer

95% of enterprise AI pilots fail not because of model quality, but because nobody is sitting close enough to the problem to see what the model actually needs.

MCP is Eating Your Model Context — Here's How Code Execution Solves It

Model Context Protocol (MCP) promises seamless tool integration, but it comes with a hidden cost: context window bloat. Learn how code execution offers a leaner, more efficient alternative.

How to Become a GenAI Engineer Without Being an ML Expert

The rise of LLMs has created a new role: the GenAI Engineer. You don't need a PhD in machine learning anymore. Here's what you actually need to know.

December 20, 2024

8 min

Vijay Poudel

Engineering GenAI for Production.

Jev Explained: How TypeSafe’s Decision Model Fits Into AI Agents

Reasoning vs Standard LLMs: When Is It Worth Paying the Thinking Tax?

Code Is Cheap, Context Is Expensive: The Strategic Power of the Forward Deployed Engineer

MCP is Eating Your Model Context — Here's How Code Execution Solves It

How to Become a GenAI Engineer Without Being an ML Expert

Want to build production GenAI systems?

Engineering
GenAI for Production.