Not hype. Not a demo reel — a tool I reach for every day. It writes code beside me, and it ships as real features inside the products I build. Here is exactly how I use it, where it fits, and the rules I keep it within.
My AI loop↳ AI does the typing — I own every decision
How I use it
Four ways AI earns its place
One tool, four very different jobs — from writing code beside me to features your users actually touch.
As a pair engineer
Claude Code sits in my terminal as a second senior engineer — it reads the whole repo, follows my conventions, and never tires of the boring parts.
What it does
Scaffolds features, refactors, and framework migrations
Writes tests and reproduces bugs from a stack trace
Reviews diffs and explains unfamiliar code
Automates repetitive work — codemods, config, glue
What I get
Days instead of weeks on repetitive work
More time on architecture and the hard calls
Claude CodeRefactorsTestsReviews
AI inside the product
AI features users actually touch — search that understands meaning, assistants that answer from your data, calls turned into searchable transcripts and scored.
Grounding checks so answers stay backed by sources
What you get
Features that feel smart, not gimmicky
AI that does a job — measurable, not a demo
RAGEmbeddingspgvectorLLM
Content & media, faster
AI removes the blank-page problem. Copy in three languages, social images, and video — all produced within the same visual system, not generic AI output.
What it does
Multilingual copy & SEO (EN / ES / UK)
OG images and brand visuals generated to spec
Short videos and showreels from scripts
This very page — drafted, then hand-finished
What I get
A blank page is never the bottleneck
On-brand output, produced in hours
CopyOG imagesVideoi18n
Automation of the boring
Repetitive back-office work that used to eat hours — handled by small, reliable AI workflows that run themselves.
What I automate
Ad-copy generation and bid rules (Google Ads)
Lead routing to Telegram / WhatsApp / email
Internal tooling and one-off data jobs
A team AI Hub so wins get reused, not rebuilt
What you get
Hours back every week
Fewer manual, error-prone steps
AutomationGoogle AdsTooling
In production
AI I have actually shipped
Not slides. Not prototypes — real AI features running in production today. Explore any of them through the code or live product.
1
Speech + scoring
CallLens
Sales calls turned into coaching insights — speaker-diarized transcription, an LLM scorecard backed by quoted evidence, and every call semantically searchable.
Deepgram speech-to-text with speaker separation
LLM scores each rep against a configurable scorecard