content systems · technical writing · code

Publish like a ten-person content team. With one contractor.

Content pipelines for US agencies: voice cloning, technical content, editorial automation. Writing and code included.

You sold the retainer. Now you’re drowning in production.

The pitch was the easy part. The work is volume: a dozen pieces a month, each one supposed to sound like the client, hit a real quality bar, and ship on a date you already promised. Hire fast and the voice drifts. Edit everything yourself and you become the bottleneck you hired around.

Adding another writer doesn’t fix that. It splits the same problem across more people. The fix is a system that keeps the voice steady as the volume climbs, so quality stops depending on who picked up the brief. That’s the work I do.

The voice pipeline, running live.

It reads a writing sample and compiles a reusable voice profile. That’s the first step the production pipeline runs before it drafts anything.

voice-engine / built in productionlive demo

A stripped-down slice of the real pipeline: drafts in, a voice + editing skill out.

The production version runs on Python and Claude. It reads a client’s back catalogue, builds a deeper profile than these client-side heuristics can, and gives every draft a voice and editing skill to work from. The first pass already sounds like the client, not like a model. This page runs the lightweight version so you can see how it works without a server.

Three ways to put me to work.

  • a.

    Content pipelines

    Voice cloning, brief-to-draft automation, editing systems. 3× the output on the same headcount, and it still sounds like the client.

  • b.

    Technical content

    AI, fintech, and developer-facing writing for the clients generalist writers tap out on. I read the docs and the charts.

  • c.

    Copy + code, one invoice

    Landing pages, programmatic SEO, and the small internal tools that make a content team faster. Written and built by the same person.

Work that went live, on real deadlines.

AI observability · $10M-funded startup

what it required
Technical content on LLM evaluation and observability, accurate enough for a developer audience and held to agency deadlines.
what shipped
Long-form technical articles and docs explaining evaluation, tracing, and observability to engineers.
outcome
Delivered on schedule and cleared technical review without a rewrite cycle.

Venture capital · mid-size firm

what it required
Investor-grade thought leadership written by someone who can actually read the charts.
what shipped
Market commentary and thesis pieces that hold up in front of LPs and founders.
outcome
Published under the firm's name with edits measured in lines, not paragraphs.

I’m the contractor agencies call when the work sits between two job titles.

Strong writers usually can’t build the tool. Strong builders usually write like engineers. I do both and bill it as one line item, which is what an agency wants when a project won’t sit cleanly under “writer” or “developer.”

  1. foundationCS degree. I think in systems and write the Python myself.
  2. marketsYears in trading and finance, so I write fintech and VC content without faking the fluency.
  3. shippingFreelance dev work: real clients, real deadlines, code that goes live.
  4. the mergeRan agency content for AI and VC clients, then built the voice pipeline when the volume outgrew the writers.
  • python
  • claude api & skills
  • technical writing
  • content strategy
  • marketing ops
  • web dev

Jack of all trades, master of none — though oftentimes better than master of one.

Have a content bottleneck?

30 minutes, your timezone. I’m based in Pakistan and work US hours: async-first, with weekly Loom updates, and you won’t wait a day for a reply. If I’m not the right fit, I’ll tell you who is.

Book a 30-min call