A base pattern agent for planning B2B projects. It extracts key planning details from user conversations, checks for relevance, and then leverages planning tools to generate a complete project plan.
This agent base pattern helps Ai builders empowers AI agents to work alongside humans to generate well-informed, actionable plans. It provides capabilities such as detailed information extraction, validation of planning inputs, and can include interactive planning tools that enable agents to collect and process key data from user conversations.
Planning agents help Go-To-Market team members craft detailed, actionable plans with structured data. By leveraging this agent, users receive a structured and efficient process that converts raw, conversational inputs into meaningful planning details.
The agent workflow begins with a user requesting something along the lines of "Let's plan X". This triggers the extraction of key details from the conversion. Examples might include client name, project scope, and start/end dates from the conversation. It then classifies these details to check their relevance against the latest user input and prompts for clarification if changes are detected.
Following this, specialized planning tools are deployed—this step may include UI components within the agent chat interface, enabling human users to make selections on, for example, scheduling options, resource allocations, and budget estimations.
Finally, all planning outputs are consolidated into a comprehensive plan document that may be used for human consumption and/or with downstream agents.
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Does this AI agent workflow rely too much on AI and not enough on human know-how? Or the reverse? Is it missing steps or tools?
Note that this Ai workflow is presented as inspiration for what's possible. Adjust the amount, type and quality of the data inputs. Adjust how much or how little your human team mates (or you), AI and fully autonomous agents contribute.
And test it! Learn what works and what doesn't.
Don't forget! In the end, it's not just about efficiency. It's about delivering great experiences for your customers and customers-to-be.
Extract the following information for a B2B plan: client name, project scope, start date (YYYY-MM-DD), end date (YYYY-MM-DD), and number of stakeholders. If the client name or project scope is missing, ask: 'Please specify the client name and project scope for the plan.'
Given the extracted plan details: {planDetails}, and the recent conversation context: {messages}, determine if these details are still relevant for the current planning request. Return a flag 'isRelevant' as true or false.
Using the confirmed plan details: {planDetails}, produce a detailed planning output that includes a timeline, resource recommendations, and an estimated budget.
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