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On Tuesday, I shared an example of how a government contractor was losing out on opportunities because their manual work was preventing them from having the speed to identify, respond to, and handle all the activities that occur before, during, in between, and after.

(Read the full story here if you missed it.)

The question isn't whether AI can do everything; it's having a framework to use it to solve your velocity problem in small steps.

THE FOUR-STEP PROCESS:

Transformation comes from the little actions you take over a sustained period of time.

So, how do you get started to figure this out? Because the struggle of what to do is more impactful than how to do it. Let's walk through the steps.

JOB: Identify Your Process Bottleneck

First, use your favorite AI assistant - whatever that is for you. But let's start with the JOB.

You'll say:

“Act as a capture management expert who has won $2 billion in contracts, and you've helped speed up capture processes for companies with manual work bottlenecks that prevent them from converting more opportunities because they can't respond quickly enough. I want you to interview me to understand my process, my pain, my bottlenecks, and where my opportunities might lie for an AI employee to help with a particular aspect of the process."

PLAN: Score and Rank Your Micro Tasks

When you're done with that interview, you'll have identified several micro tasks to focus on. Now we need to come up with a plan and figure out which one would be the best to start with.

At the end of the process, the AI will give you a few recommendations. What you should do from there is score and rank them based on:

Which one would have the most impact the fastest? Find the easiest to implement with the most impact - that's what you start with first.

So how do you do that? You give it criteria for a plan and say:

"Build out the steps to do this. Create a strategic prompt that will help build out this micro AI employee. Before I build any automation, I want to test this with the existing tools I already have to validate the benefits. Also, tell me how I should rewire my current workflow around this so I can have the most impact."

DEPLOY: Build Your Micro AI Employee

Now here's where it gets practical. Take that instruction prompt and tell the AI exactly what I need:

"I want to create this micro AI employee. Here are the tools I currently use for this work. This process takes me 6 hours every week. I have no technical skills, but I want something fast and easy. Give me everything - assume I know nothing. Write all the prompts, tell me where to put them, and show me the best way to set this up. What built-in features should I use? Can I leverage deep research, agent mode, or projects? I use Google Workspace and ChatGPT Plus - work within what I already have."

The AI walks you through the complete setup. It writes the system prompt, shows you how to create a project, tells you what files to upload, and maps out exactly where each piece goes.

Tip: If you use ChatGPT, OpenAI has a prompt optimizer. Have it build your prompt first, then move it to the optimizer for refinement.

Within an hour, you have a working micro AI employee handling that specific bottleneck. No coding, no complex integrations. You are just using tools you already pay for strategically.

REWIRE: Change How You Work

Here's the hardest part: rewiring how you do the work. Instead of your old process, you initiate everything from your AI employee.

If it's fully automated, great. If it requires input from you, you provide it with what it needs and let it handle the activities.

You can enhance and advance it from there, but this gets you started.

The key is running things through this AI employee, giving it instructions to execute, rather than sprinkling AI into your old, broken process.

It's a completely different experience.

This AI employee has a job description, knowledge, and information tied to your proposal volume target.

Once you rewire your workflow around it, you can measure the benefits and iterate.

Think of it like a startup for your business. Just as startups iterate to improve, and employees become better with each learning experience and task, you should apply the same approach to your AI employee. It gets smarter and more effective over time.

If you want some help with more structure around this for your AI transformation goals, check out our THINK Guide. It'll give you everything you need to build out your AI workforce using this exact methodology systematically.

VELOCITY Advantage

This is how you get the velocity advantage.

While others schedule "AI readiness assessments," you're building micro AI employees that handle specific bottlenecks.

One team does everything manually. Another has AI employees for aspects of opportunity assessment, compliance checking, and proposal drafting.

Same team size, 10x faster output.

Your competitors aren't announcing their AI workforce; they're mysteriously handling twice the opportunities with less effort.

While others fear what AI will do wrong, you're taking action. You don't fire an employee for one mistake; you put guardrails around them to prevent future errors.

Baby steps, prove, and add. Same approach for AI.

The revolution is happening right now, rewiring how work gets done while others debate whether AI is "ready."

Marvin