Agentic Workflows
Agentic workflows are multi-step processes where an AI system plans, executes, and iterates on tasks with minimal human intervention between steps. Unlike a single prompt-response exchange, an agentic workflow might involve the AI researching a topic, drafting a document, reviewing it against criteria, revising, and publishing—each step informed by the results of the previous one. The appeal is obvious: you describe the outcome and the system figures out the steps. The risk is equally obvious: errors compound across steps, and the system may confidently execute a plan that was wrong from step two. Production agentic workflows in 2025 tend to be narrowly scoped with clear checkpoints—processing invoices, triaging support tickets, generating reports from structured data. The fully autonomous AI employee that handles ambiguous, high-stakes work without oversight remains aspirational. Building reliable agentic workflows is less about model capability and more about designing the right guardrails, evaluation criteria, and fallback paths.
Related terms:
AI Governance
AI governance comprises the policies, processes, and technical controls that organizations use to manage the risks of AI deployment, from deciding appropriate use cases and evaluating models to ensuring accountability, data privacy, bias mitigation, and regulatory compliance under frameworks like the EU AI Act. Without clear governance, “shadow AI” can proliferate as employees use unmonitored AI tools with no oversight or audit trails.
Conway's Law
Conway’s Law states that organizations designing systems are constrained to produce designs mirroring their own communication structures. For example, separate sales, marketing, and support teams often yield a website organized into Shop, Learn, and Support sections—reflecting internal divisions rather than user needs.
Accretive Software
Accretive software refers to AI platforms that automatically absorb model improvements as margin expansion by treating models as interchangeable components and routing queries to the optimal model in real time. Rather than fighting obsolescence, these platforms convert every efficiency breakthrough into customer value or profit margin.