At Bankwell Bank, a new employee named Sarah works around the clock. She responds to loan applicants via email and SMS in under three minutes, gathers missing documents, and hands a perfectly structured file to her human colleagues. She has re-activated roughly half of the bank’s otherwise lost applicants and saved loan officers 90% ofContinue reading “New Report: The Architectural Patterns of Financial AI”
Author Archives: Ben Lorica
New Report: The Architectural Patterns of Financial AI
At Bankwell Bank, a new employee named Sarah works around the clock. She responds to loan applicants via email and SMS in under three minutes, gathers missing documents, and hands a perfectly structured file to her human colleagues. She has re-activated roughly half of the bank’s otherwise lost applicants and saved loan officers 90% ofContinue reading “New Report: The Architectural Patterns of Financial AI”
The Next Generation of AI Agents: Large Action Models Explained
As AI agents become commonplace in enterprise workflows, teams are discovering the limitations of building task-specific automated systems from scratch. Large Action Models (LAMs) represent the foundational layer that transforms how we build agents—providing the general-purpose perception, planning, and execution capabilities that individual agents can leverage rather than reinvent. Instead of building isolated automation tools,Continue reading “The Next Generation of AI Agents: Large Action Models Explained”
From tool-chaining to true agentic systems
Subscribe • Previous Issues The Next Generation of AI Agents: Large Action Models Explained As AI agents become commonplace in enterprise workflows, teams are discovering the limitations of building task-specific automated systems from scratch. Large Action Models (LAMs) represent the foundational layer that transforms how we build agents—providing the general-purpose perception, planning, and execution capabilities that individualContinue reading “From tool-chaining to true agentic systems”
Compound Interest: AI’s Invisible Impact on Productivity and Jobs
I’ve learned to tune out the “Are we there yet?” chorus that follows every AI model release. While Twitter debates rage about AGI timelines, something more interesting is happening in the trenches: current foundation models are quietly revolutionizing how knowledge work gets done. My own workflow tells the story. Eighteen months ago, I wrote codeContinue reading “Compound Interest: AI’s Invisible Impact on Productivity and Jobs”
AI Is Quietly Rewriting Work—Here’s What You Need to Know
Compound Interest: AI’s Invisible Impact on Productivity and Jobs I’ve learned to tune out the “Are we there yet?” chorus that follows every AI model release. While Twitter debates rage about AGI timelines, something more interesting is happening in the trenches: current foundation models are quietly revolutionizing how knowledge work gets done. My own workflowContinue reading “AI Is Quietly Rewriting Work—Here’s What You Need to Know”
Beyond the Lab: Performance Engineering for Production AI Systems
The conversation around AI has shifted from whether to adopt the technology to how to make it economically viable at production scale. In previous articles, I’ve covered the strategic playbooks for AI adoption and evaluation frameworks that define success. However, a critical gap persists between successful pilots and sustainable production systems—a gap that costs organizationsContinue reading “Beyond the Lab: Performance Engineering for Production AI Systems”
Before you scale your AI, read this
Subscribe • Previous Issues Beyond the Lab: Performance Engineering for Production AI Systems The conversation around AI has shifted from whether to adopt the technology to how to make it economically viable at production scale. In previous articles, I’ve covered the strategic playbooks for AI adoption and evaluation frameworks that define success. However, a critical gap persistsContinue reading “Before you scale your AI, read this”
A DeepMind veteran on the future of AI and quantum
Quantum computing has always felt just over the horizon, so I’ve only tracked its progress from a distance. But that horizon is suddenly much closer: prototype machines with around 100 logical qubits are already tackling niche but valuable AI workloads, and startups are racing toward the 1,000-qubit mark. Early pilots in areas like recommendation systems,Continue reading “A DeepMind veteran on the future of AI and quantum”
Superposition Meets Production—A Guide for AI Engineers
Subscribe • Previous Issues A DeepMind veteran on the future of AI and quantum Quantum computing has always felt just over the horizon, so I’ve only tracked its progress from a distance. But that horizon is suddenly much closer: prototype machines with around 100 logical qubits are already tackling niche but valuable AI workloads, and startups areContinue reading “Superposition Meets Production—A Guide for AI Engineers”