Practical articles on what works in a real team, and what does not.
Book a CallWhat a 2010-era monolith costs you in 2026, how to judge whether modernising is the right answer, and the cheaper fixes worth trying first.
Persistent context without speed degradation: why a huge context window is a crutch for poor design, and how to build memory that stays fast.
Graph-based and linear AI orchestration compared on token burn, and why redundant context passing consumes so much of an enterprise LLM budget.
Relevance AI and Zapier compared for sales ops: where a linear tool stops working, and which problems genuinely need an agentic platform.
A step-by-step guide to implementing RAG in AI workflows, and why enterprise systems still hallucinate despite heavy compute spend.
Most AI initiatives stall because firms bolt AI onto the interface. What a real Salesforce integration changes, and the sequence that avoids the stall.
Open source or custom LLM for an enterprise: where API spend hits diminishing returns, and which workloads justify owning the model outright.
CrewAI, LangGraph and Zapier compared for enterprise orchestration: where each stops scaling, and what hitting the agentic ceiling looks like.
A developer's guide to building LangGraph AI workflows, and why standard LangChain struggles once a workflow stops flowing in one direction.
Tell us about a process you want to automate and we will say whether it is worth building.
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