The Problem Nobody Talks About in AI Consulting
You land a client. Great discovery call. They want an AI strategy. You quote $15K and they say yes.
Then the grind begins.
Two hours researching their industry. Four hours writing the proposal. Eight hours building the deliverable. Another three hours drafting a status email that somehow needs to sound bespoke. By the time you invoice, you have maybe 15 hours of genuinely valuable thinking — buried under 45 hours of work that, if you are honest, AI should be doing.
That is the real problem. Not that consultants lack knowledge or skills. It is that 70% of billable-adjacent work is operational overhead disguised as consulting.
I spent the better part of 2025 trying to fix this for myself. What I built became WEDGE Method, and we are launching on Product Hunt tomorrow.
What I Actually Built
WEDGE Method is a platform with six integrated tool systems for consultants:
- Research — Structured AI research workflows that take a client brief from blank to comprehensive competitive landscape in 20 minutes instead of 2 hours
- Proposals — Templated proposal frameworks with AI fill-in that cut proposal time from 4 hours to 30 minutes, with a built-in ROI calculator that has helped beta users close over $200K in deals
- Deliverables — Slide, report, and framework generators. An 8-hour deliverable becomes a 2-hour one when you have the right scaffolding
- Client Communications — AI-assisted status updates, meeting recaps, and follow-up sequences. Everything professional, nothing that sounds like a template
- Operations — SOPs, rate cards, onboarding sequences, and the $192K/year consulting framework that shows you exactly what you need to charge at every project size
- Analytics — Track utilization, project profitability, and identify where you are losing time
The headline numbers: users save 10–20 hours per week. The best-performing beta user is running a six-figure consulting practice on about 25 hours per week instead of 60.
The Technical Story
The stack is React 19 + Vite 7 + TypeScript + Vercel Serverless. I deliberately avoided a backend server — everything runs on Vercel functions and Vercel KV. The AI pipeline is xAI Grok as primary, Anthropic Claude as fallback, OpenAI GPT-4o-mini as last resort. This three-layer failover means users never hit a dead end because one provider is rate-limited.
What was hard to build:
The ROI calculator. Getting the math right was straightforward. Getting it to feel conversational — where filling it out feels like a good discovery conversation rather than a spreadsheet — took probably 15 iterations. The current version asks four questions and produces a personalized rate card with justification language you can paste directly into a proposal.
The 300+ prompt library. Writing good prompts is easy. Writing prompts that work consistently across different consulting niches, different client sizes, and different writer voices is genuinely hard. Each prompt in the library went through at least three rounds of testing against real consulting scenarios. The final library covers research, proposals, deliverables, client communications, thought leadership, business development, and operations.
TypeScript strictness across Vercel functions. I run tsc --noEmit clean on every commit — no any types, no implicit nulls. The pre-commit hook blocks anything that does not pass. This is non-negotiable for a platform that consultants are trusting with client-facing work.
Legal compliance. FTC, GDPR, CCPA, CAN-SPAM, ADA/WCAG 2.1 AA — all of it. When you are a solo founder, it is tempting to ship first and add the privacy policy later. I did it the other way because consultants using this for client work cannot afford compliance gaps.
The test suite runs 740 tests across 20 files — unit tests for auth, rate limiting, input sanitization, webhook verification, plus E2E tests for the full customer journey. 740/740 passing before any production deploy.
The 12 AI Agents Running in the Background
One thing that does not show up in the UI: there are 12 autonomous agents running on cron schedules. They handle content generation, SEO optimization, competitive monitoring, email sequences, and analytics aggregation. The platform self-maintains to a significant degree.
This was the part I found most technically interesting to build. The agent framework uses a base class with a task queue and scheduler. Each agent registers itself, and the hourly cron fires the queue. The agents do not know about each other — they communicate through Vercel KV as a shared state store.
Why We Are Launching on Product Hunt Tomorrow
We have been running a closed beta for three months. The feedback loop has been tight — every piece of feedback went into the prompt library or the UI. We have refined it to the point where I am confident showing it publicly.
If you are a developer, technical consultant, or anyone who works adjacent to consulting work, I would genuinely love your take on what we built. The dev community has very high standards for what "well-built" means, and that feedback is more useful to me than any vanity metric.
We go live on Product Hunt on March 16: https://www.producthunt.com/posts/wedge-method
An upvote helps, but what I actually want is: if you try it and find something broken, tell me. The free tier includes the core templates and the rate card calculator — you do not need to subscribe to see what we built.
What Is Free vs Paid
- Free: Core templates, rate card calculator, 7-day trial of the full platform
- Starter ($29/mo): All tools, 300+ prompt library, SOPs
- Professional ($79/mo): Everything plus the agent-assisted workflows and analytics
- Enterprise ($199/mo): Team access, white-label, SLA, priority support
The 7-day trial is no-card-required. I want consultants to actually use it before deciding whether it is worth paying for.
One Thing I Wish I Had Built Earlier
The $192K/year framework. This is a structured model that shows you exactly what combination of project types, retainers, and one-off work gets you to $192K annually as a solo consultant — broken down by rate, utilization, and project mix.
I built this in week eight of the beta because five different users asked some version of "how do I know what to charge?" It should have been in version one. If you build something for consultants, start with the pricing math. Everything else flows from whether someone can see how the economics work.
We are launching tomorrow. If you are reading this on March 16: the Product Hunt page is live at https://www.producthunt.com/posts/wedge-method. Support from the dev community genuinely matters on launch day — the algorithm weights early upvotes heavily.
If you are reading this after: the platform is at https://thewedgemethodai.com and the free trial is still there.
Either way, thanks for reading. Build things that remove friction. It is the only category that never goes out of style.
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