Build an AI Agent for Your Work - From Workflow to Prototype

Most professionals do not need another general introduction to AI. They need help identifying where AI can genuinely improve their work, and then turning that opportunity into something they can actually test. In this private build sprint, we will transform one recurring, clearly defined workflow from your professional life into a functional AI-agent prototype. Your workflow might involve research, document analysis, meeting preparation and follow-up, competitive intelligence, reporting, content development, decision support, customer operations, or another knowledge-intensive process. The engagement consists of four stages: 1. Workflow diagnosis and opportunity selection We will map the current process, including its inputs, outputs, decision points, bottlenecks, repetitive work, and areas requiring human judgment. We will define what success should look like and determine whether an AI agent is actually the right solution. If a simpler automation would work better, I will tell you. 2. Agent architecture and tool selection We will design how the system should work: the tasks it performs, information it needs, tools it uses, steps it follows, and points where a person should review or approve its work. We will also select an appropriate no-code, low-code, or AI platform based on your technical comfort, security requirements, budget, and intended use. 3. Guided prototype development We will build and refine a functional proof of concept for the selected workflow. This includes creating the agent’s instructions, prompts, workflow logic, example inputs and outputs, and any practical integrations supported by the agreed platform. You will participate in the build so that you understand how the system works and can continue improving it after the engagement. 4. Testing, evaluation, and implementation planning We will test the prototype against realistic scenarios, identify failure modes, and determine where additional guardrails or human oversight are needed. We will conclude with a prioritized plan for piloting the agent in your actual work. Throughout the package, I will draw on more than a decade of experience in data science, applied AI, AI strategy, and technical education. My approach combines strategic judgment with hands-on implementation: we will consider not only what can be built, but whether it will create meaningful value and how its performance should be evaluated. No coding background is required. Technical clients may choose to work at a deeper architectural level. This package covers one bounded workflow and a proof-of-concept implementation. Production software development, custom model training, large-scale enterprise integration, and ongoing system maintenance are outside the package’s scope.