What actually breaks when you put an agent in production
The demo always works. Here's what fails once real data, real users and real latency show up — and the guardrails that catch it before your customer does.
From the team
Notes on shipping AI systems.
Short, practical write-ups on agentic AI, automation and the engineering decisions behind what we ship — from the team building it.
The workflow audit we run before we automate anything
Not every repetitive task should be automated as-is. The checklist we use to decide what to fix first, what to remove, and only then what to wire up.
Evals are the thing nobody budgets time for
Everyone plans the build. Almost nobody plans how they'll know it's working. A practical starting point for evaluating an LLM feature before it ships.
Scoping a fixed-price AI project without the scope creep
How we write a spec that holds up once the build starts — and what we push back on when a "quick addition" shows up mid-sprint.
New posts are on the way. In the meantime, book a call or follow along on Instagram and LinkedIn.