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.
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.
10 times goal per engineer
12 Engineers led
25+ Engineers mentored
8 Years shipping
01
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:
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.
02
Why you can trust the advice
The proof is all public ↗
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.
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.
18k+ Hours processed daily
20k+ Users served
75% Less manual work
3 times faster 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
03
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
04
Here’s what I’d actually do for you
Five ways I earn the retainer
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.
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.
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.
Team unblocks
When your lead engineer is stuck on something an outside brain solves in thirty minutes. On call for the hard ones.
Pre-funding technical narrative
The engineering story for your investor deck or due-diligence pack, credible to the most technical person in the room.
05
And, just as importantly
This is where the trust is
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.
06
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
A few hours a month: weekly call plus async. Your senior brain on call.
$800/moEmbedded, 1 day a week
Hands-on inside your team, every week.
$2k/moTech due diligence
An independent engineering read for investors or acquirers.
$1.25k one-offArchitecture sprint
One hard decision, answered in one to two weeks.
$2.5k one-off07
How we’d start
Four steps, no theatre
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.
A one-page scope
Fixed shape, fixed rate, in writing. No bloated statement of work to wade through.
We start
Weekly call plus async access. A senior brain on tap, with a clear response-time SLA.
Honest exits
Month to month. When the problem’s solved, we say so. No lock-in, no drag.
08
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.
09
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.
10
So, shall we talk?
Context is optional. One line is enough.
Book a call, or say hello.
One or two advisor seats open this quarter. Book a call is fastest; the short form below is fine if you prefer email — context is optional.
Looking forward to it,
Muneeb Hussain