Every week has a job that's the same clicks, in the same order.

I make it run by itself, the same way every time.

I spent a year automating lead-finding for an outbound agency, got good at it, got bored of it, and noticed the same missing piece everywhere: nobody measures whether the automation is right. So now I build the thing, and the test for the thing.

Delhi, India. UK working hours are my afternoon and evening, US mornings my evening.

Running right now · Tender Radar

Government contract notices for cleaning, security and facilities work are spread across several UK websites. I wanted one script to read all of them every morning and sort out which ones each trade should bid on.

117

mornings it has started on its own since 4 July 2026.

One bar per day, last 40. Black finished, red failed. Last run: 28 Oct, 11:31 UTC. Read live from GitHub.

It sorts for 7 trades, from cleaning and security to pest control, and has 498 notices on file.

Its worst stretch was about three weeks, from 21 July to 11 August, when a data-format change broke the morning run and nothing told me.

Watch it work (under 5 min) ↗See the code ↗

Work, and who vouches for it

Jobs

At Precise Leads

GTM automation engineer · Nov 2025 → now · remote

Outbound, built end to end

Finds the companies worth writing to and the right person at each, then writes emails that only say what the research found.

I built the agency's outbound pipeline. One run sorted 34,044 companies in four days, and every yes came with a quote from the company's own website. Each draft is checked claim by claim against that research, and when someone spots a new kind of mistake, it becomes a check that runs before anything goes out. I also built the Slack bot that buys and warms up the sending inboxes, the tool that turns a client's sequence into a ready campaign, and a daily scan of five sales-tool Slack communities that passes likely buyers to the sales team.

0: contradicted claims in 300 drafted emails
34,044: companies sorted in four days

built with python, typescript, clay, smartlead, n8n

At Caprae Capital Partners

Machine Learning Intern · Aug 2025 → Jan 2026 · US, remote

Resume screening, automated

Reads incoming resumes, ranks the candidates, and books the interviews.

A recruiting team was spending about ten hours a week reading resumes by hand. The system reads each one, scores it against the role, writes the shortlist and schedules the calls.

10h → 3h: screening per week
5 → 1.5: days to a shortlist

built with python, embeddings, slack

“…produced clear and maintainable technical documentation, and effectively communicated complex engineering concepts to non-technical stakeholders.”

Zackary Beckham, Chief Operations Officer, Caprae Capital Partners
From a signed letter of recommendation, 11 Jan 2026. Full letter available on request.

Built on my own

My own project

leadlens

Reads a job posting and tells you whether the AI role is real, dressed up, or a scam.

Out of 72 postings I checked by hand:
9 caught	2 missed
0 false alarms	61 left alone

built with python, gemini, pydantic

How I tested it →

My own project

PresentAI

Type a topic, get a first-draft slide deck you can edit.

Gemini writes the outline first, then the slides, and Pexels adds a photo to each. You finish the deck in a drag-and-drop editor with 25 themes. Its AI step needs a model update before it runs again.