Dear founder,

I make your engineers 10×by adopting what’s coming, not what’s trending.

I’ve mentored 25+ engineers and currently lead twelve shipping production AI systems today, not from a memory of 2019. I take on one or two teams at a time and turn AI from a buzzword into measured leverage.

Book a discovery call Email me

My specialty

AI adoption, done right

This is where most teams either freeze or set money on fire. Four questions decide whether AI becomes leverage or a liability, and they’re the four I answer:

Which model for which task

Frontier models aren’t interchangeable. I map each job (reasoning, code, extraction, search, cheap-and-fast) to the model that actually wins it, and re-check as the field shifts week to week.

AI inside the real workflow

Not a demo. I wire AI into how your engineers already work (review, tests, docs, the boring 80%) so the leverage shows up in shipped output, not in screenshots.

Guardrails so nothing blows up

Approval boundaries, evals, fallbacks, and a real off-switch. The difference between AI that compounds quietly and AI that pages you at 3am.

Cost that stays sane

AI is expensive, unless you know exactly where to spend tokens and where one cached call does the job. I run a twelve-engineer team on roughly $50 per engineer per month. Maximum output per dollar is the whole game, and it’s the part I’m best at.

the proof is
all public ↗

Why you can trust the advice

I don’t just advise on this. I ship it.

A sample of what I build in the open, while running the team:

Agent-native dev tooling

CLIs and MCP servers that let AI agents research, search, and act: gh-research, reddit-search, hn, x-search-tool.

Browse repos →

Production AI systems

The teams I lead ship production AI: a media-localization platform processing ~18,000 hours of content a day, dubbing pipelines that handle hours-long video where most cap at five minutes, AI twin systems that cut manual response load 75%. Shipped, not slideware.

Full-stack, end to end

TypeScript, Next.js, Python, FastAPI, Bun, Postgres, from ambulance-dispatch platforms to fintech tooling.

In the open

Sixty-six public repositories and counting. The work is inspectable, forkable, and real.

github.com/muneebhashone →

0hours processed daily

0users served

0less manual work

0faster delivery

Across the production AI systems my teams ship for enterprise broadband, B2B SaaS, and healthcare, selected over competing vendors on multi-year engagements.

TypeScript
Next.js
Python
FastAPI
Postgres
Bun
LLMs
MCP

The stack I live in

Fluent in what your team is betting on

These aren’t tools I read about. They’re the ones I run in production every week. That’s the only way to actually know which earn their place, and which are this month’s noise.

Frontier models

Anthropic
OpenAI
Perplexity
Google Gemini
DeepSeek
Kimi
MiniMax

Agents & coding

Claude Code
Cursor
Codex
Opencode
Hermes Agent
OpenClaw
Pi Coding Agent
Manus

Cloud & infra

Vercel
AWS
GCP
Azure

Here’s what I’d actually do for you

Five ways I earn the retainer

1. AI-augmented engineering enablement
The headline act: get your existing engineers to 10×. The mindset, habits, and tooling that turn senior devs into forces, and bring juniors up to senior speed far faster.
2.Architecture & technical review
Codebase walkthroughs, ADR feedback, scaling decisions, build-vs-buy calls. A senior set of eyes before you commit the next six months.
3. Engineering hiring calibration
Interview rubric review, sitting in on senior loops, settling leveling debates. Hire right the first time. It’s the most expensive thing to get wrong.
4. Team unblocks
When your lead engineer is stuck on something an outside brain solves in thirty minutes. On call for the hard ones.
5. Pre-funding technical narrative
The engineering story for your investor deck or due-diligence pack, credible to the most technical person in the room.

this is where
the trust is

And, just as importantly

What I won’t do

Write your code. You have engineers. My job is to make them 10×, not replace them.
Manage your team day-to-day.That’s a CTO, not an advisor.
Source candidates.I’ll review them, not recruit them.
Chase trends.I adopt what’s coming, not what’s loud this week. No hype builds, no autonomous magic. Just leverage that lasts.
Work full-time.I have a job I’m not leaving, which is exactly what keeps the advice current.

The shapes this can take

Pick the one that fits

Every retainer starts with a one-page written scope. Equity, when it makes sense, is a bonus on top of cash, never a discount.

Monthly advisor

$800/mo

A few hours a month: weekly call plus async. Your senior brain on call.

Embedded, 1 day a week

$2k/mo

Hands-on inside your team, every week.

Tech due diligence

$1.25k one-off

An independent engineering read for investors or acquirers.

Architecture sprint

$2.5k one-off

One hard decision, answered in one to two weeks.

How we’d start

Four steps, no theatre

1
Discovery call
Thirty minutes on your stage, your team, the real problem. If you need a full-time CTO or a recruiter, I’ll say so on the call.
2
A one-page scope
Fixed shape, fixed rate, in writing. No bloated statement of work to wade through.
3
We start
Weekly call plus async access. A senior brain on tap, with a clear response-time SLA.
4
Honest exits
Month to month. When the problem’s solved, we say so. No lock-in, no drag.

You’re probably wondering

The honest answers

Isn’t AI just expensive hype right now?

Expensive for teams that use it carelessly. Used well, it’s the cheapest senior engineer you’ll ever hire. Knowing exactly where to spend tokens and where a cached call does the job is most of what I do. On my own team that works out to about $50 per engineer per month, and that’s the whole bill. I optimise for what’s coming, not what’s trending, so you’re not rebuilding it in six months.

Aren’t you working full-time somewhere?

Yes, and that’s the point. You get someone currently doing the job at scale, about half a day a week, with evenings and weekends for async and a clear response-time SLA. Fresh beats merely available.

Do you take equity?

Sometimes, as a bonus on top of a cash retainer, never instead of it. If we both believe in the upside, great. But I don’t trade my rate for a line on the cap table.

What if I actually need a full-time CTO?

I’ll tell you on the first call. Disqualifying honestly is part of the service. A wrong engagement wastes your money and my time.

How fast can we start?

Discovery call this week, a one-page scope within a few days, and we can start the following week.

Do you build it yourself?

No, I’m the brain, not the hands. I make your engineers more effective. If you genuinely need build capacity, my team at Hashone Digital is a separate conversation.

First, the honest pitch

Not an ex-CTO. A current one.

Advice is only as fresh as the last time someone actually did the job. I’ve mentored 25+ engineers over the years and currently lead twelve at Hashone Digital, fullstack engineers shipping production AI systems with the tooling everyone else is still figuring out.

My job with you is simple: make your engineers 10×. Not by working them harder, but by building the mindset and the tooling to envision and adopt what’s coming, not what’s merely trending. The same playbook I use coaching individuals and running a team. The teams that win the next two years are the ones already building for where this is heading.

So, shall we talk?

Tell me the one decision you’d want a second opinion on.

One or two advisor seats open this quarter. Book a call, or send the note below and I’ll come back to you personally.

Looking forward to it,

Muneeb

Muneeb Hussain · Fractional CTO & AI Advisor