Jimmy Bijlani, CEO @ AI Momentum Partners, ex-Google and BCG, recently posted something that made me stop scrolling: "Every consultant should have this — but most don’t. At AI Momentum Partners (AMP), we’ve built 25 GPTs that actually run our AI consulting firm, from research synthesis and proposal drafting to client deliverables and internal ops." This wasn’t another vague AI thought piece; it was a concrete description of how his firm already runs on a stack of specialized GPTs.

He followed that with a point that really stuck with me: "Unlocking AI capability doesn’t take massive tooling investments. Used right, GPTs get you 80% of the way there — and WAY faster than most teams expect." As someone who works with knowledge workers and consulting teams, I think this perfectly captures where the real opportunity is: not in yet another shiny AI platform, but in building a practical, opinionated system around tools we already have.

"Used right, GPTs get you 80% of the way there — and WAY faster than most teams expect."

In this post, I want to unpack what Jimmy is really pointing to, why most consultants are still stuck in "dabbling mode" with AI, and how you can start building your own unfair advantage — even if you don’t have 25 custom GPTs (yet).

The Big Idea: GPTs as Your Consulting Operating System

Jimmy isn’t just using GPTs as a smarter search box. At AMP, those 25 GPTs effectively act as the operating system for the entire consulting firm.

They support work across the full lifecycle:

Research synthesis and insight generation
Proposal drafting and sales support
Client deliverables and analysis
Internal operations and quality control

This is a subtle but important shift. Most consultants still treat AI as a helpful sidekick: something you open in another tab when you’re stuck on a slide or need to rewrite an email. What Jimmy describes is closer to a production system — a reusable, evolving set of workflows that encode how the firm thinks and works.

The impact isn’t just speed. When you turn GPTs into structured workflows, you:

Reduce inconsistency between consultants
Scale your best thinking across projects
Free senior people from repetitive tasks
Create a training layer for new team members

That is the real "unfair advantage" Jimmy is talking about.

Why Most Consultants Still Miss the AI Advantage

If the upside is so clear, why don’t most consulting teams have anything close to AMP’s setup?

From what I’ve seen, there are a few common traps:

Tool tourism instead of system design. Teams try dozens of AI tools but never commit to designing a small, coherent stack that maps to their actual workflow.
Perfectionism. Because GPT outputs aren’t perfect, people treat them as a novelty instead of building processes that assume human review and refinement.
Misaligned expectations. Leaders expect "end-to-end automation" instead of being thrilled with 60–80% acceleration on high-value tasks.
Lack of prompts and guardrails. A bare chat interface is not a system. Jimmy explicitly mentions detailed prompts, instructions, and system-level working styles as core to making these GPTs reliable.

Jimmy’s post cuts through this: you don’t need a huge platform investment; you need a thoughtfully designed set of GPTs, plus the instructions and guardrails that let consultants trust and reuse them.

Inside Jimmy Bijlani’s "Consultant’s Unfair Advantage"

Jimmy mentions a resource they built: a full list of the 25 GPTs AMP uses, along with the prompts and instructions behind them. While he doesn’t list every GPT in the post, we can infer the types of capabilities that matter most in a consulting context.

Broadly, a stack like this will typically cover four domains:

1. Research and Insight GPTs

These GPTs help consultants go from raw information to structured insight:

Summarizing long reports, transcripts, and industry data
Comparing sources and highlighting contradictions
Pulling out client-relevant implications and hypotheses

Instead of a junior consultant manually synthesizing 200 pages into a 10-page summary, a GPT can do a strong first pass in minutes, which the consultant then sharpens.

2. Proposal and Sales GPTs

Here, GPTs support the front end of the business:

Turning discovery notes into structured proposals
Generating options for scopes, timelines, and pricing narratives
Tailoring case studies and credentials to a specific prospect

The key is not to let GPTs invent your sales story, but to encode your firm’s existing story so it can be reused consistently and quickly.

3. Delivery and Client Work GPTs

These GPTs sit closest to the value you deliver:

Structuring problem statements and workplans
Drafting slides, memos, and executive summaries
Translating technical analysis into client-ready language

Used well, they don’t replace your judgment; they compress the time it takes to get from a blank page to a solid draft that reflects your frameworks and style.

4. Internal Ops and Quality GPTs

Finally, there are GPTs that help the firm run smoothly:

Standardizing documentation and templates
Checking for clarity, tone, and logical gaps
Turning meeting notes into action plans and follow-ups

This is where AI quietly removes friction from the everyday machine of consulting work.

How to Build Your Own GPT Stack (Without 25 Tools)

You may not be ready to build 25 GPTs, but you don’t have to. The real lesson from Jimmy’s post is to start designing for workflows, not individual prompts.

Here’s a practical way to begin.

Step 1: Map Your Consulting Workflow

List the stages of a typical engagement in your world: lead generation, discovery, proposal, kickoff, analysis, synthesis, delivery, follow-up. Under each stage, write down the 3–5 tasks that are:

Repetitive
Text-heavy or research-heavy
Currently done by relatively senior people

Those are prime candidates for GPT support.

Step 2: Start with 3–5 High-Leverage GPTs

Instead of aiming for 25, pick just a handful of GPTs to pilot, for example:

A research synthesizer for turning source material into structured notes
A proposal assistant for drafting outlines and standard sections
A deliverable drafter for slides, memos, or reports
A QA reviewer that checks logic, clarity, and tone

Give each GPT a clear, narrow purpose. The more specific the job, the more reliable the outputs.

Step 3: Write Clear Instructions, Not Just Prompts

This is where Jimmy’s mention of "detailed prompts & instructions" and "system-level instructions" matters. High-performing GPTs are less about clever one-line prompts and more about:

Explaining the role: who the GPT is emulating (e.g., a senior consultant at your firm)
Defining the audience and context
Specifying formats, lengths, and examples of good output
Listing constraints and guardrails (what not to do)

Document these once, then reuse and improve them, just like you would a methodology deck.

Step 4: Close the Loop with Human Judgment

Even with strong instructions, GPTs are best at that 60–80% first pass. Build explicit review steps into your workflow:

A consultant verifies facts, nuances, and client specifics
A manager reviews structure and storyline
Feedback is used to refine the GPT instructions over time

This is how your AI stack gets better with each project rather than remaining a one-off experiment.

The Future of Consulting Belongs to Firms Who Systematize AI

Jimmy’s post struck a nerve because it reflects a broader shift. The advantage will not go to the firms that talk the loudest about AI, but to the ones that quietly encode their best thinking into reusable systems.

A few things seem clear:

Individual consultants who master GPT-driven workflows will outperform peers with the same experience.
Small and mid-sized firms can punch above their weight by turning AI into leverage, not spectacle.
The gap between firms who treat GPT as a toy and those who treat it as infrastructure will keep widening.

Jimmy ended his post by asking: what GPTs are you using right now that you actually find useful? It’s a good question to sit with. If your answer is "mostly ad hoc prompts in a chat window," you’re leaving a lot of value on the table.

The opportunity isn’t to copy AMP’s exact 25 GPTs, but to learn from the mindset behind them: start small, design for real workflows, and treat AI as a core part of how your consulting business operates.

This blog post expands on a viral LinkedIn post by Jimmy Bijlani, CEO @ AI Momentum Partners | ex-Google, BCG, Startup Leader | Guiding mid-market companies from AI vision to implementation, using a fast, scalable, and proven approach.. View the original LinkedIn post →