I help teams build AI.
And build with AI.
I'm an independent data and AI consultant with extensive experience in the tech industry. I've advised and taught teams building AI-powered systems, including engineers from Netflix, Meta, and Amazon. I host Vanishing Gradients, where I explore cutting-edge developments in data science and artificial intelligence, and I've written for publications such as Harvard Business Review and VentureBeat.
# what I'm up to
$ cat now.json
{
"podcasts": "Vanishing Gradients · High Signal",
"course": "Building AI Apps · Maven",
"writing": "hugobowne.substack.com",
"building": "agents · harnesses · skills",
"based-in": "Sydney, AU"
}
$
# currently using
claude · gemini · qwen · mistral · gemma · pi
amp-code · codex · agent-skills
python · typescript · marimo · modal
pydantic · logfire · chroma · hf · obsidian
Podcasts
for the people building AI · and the people leading teams that build it
Everything you wanted to know about data, ML, and AI, but were too afraid to ask. Guests include Jeremy Howard, Wes McKinney, Hamel Husain, Shreya Shankar & more.
Deep conversations with the people shaping data science, ML & AI, for engineering leaders and practitioners.
Writing
essays, opinion, and research · substack · O'Reilly · HBR
2026.04.10
Vanishing Gradients
essay
→
2026.03.24
O'Reilly Radar
tutorial
→
2026.03.16
Vanishing Gradients
tutorial
→
2026.03.11
Vanishing Gradients
essay
→
2026.02.28
Vanishing Gradients
workshop
→
2025.06.27
Vanishing Gradients
opinion
→
2018.08.15
Harvard Business Review
research
→
Guests, co-teachers, co-authors
a partial index · 2022–2026 · podcasts, workshops, essays
Jeremy Howardfast.ai
Fei-Fei LiStanford
Wes McKinneypandas
Hamel HusainParlance Labs
Hilary Masondata science
Michael JordanUC Berkeley
Andrew GelmanColumbia
Shreya ShankarUC Berkeley
Thomas WieckiPyMC Labs
Samuel ColvinPydantic
Cassie Kozyrkovex-Google
Travis OliphantAnaconda
Peter WangAnaconda
Katharine Jarmulprivacy
Stefan KrawczykMaven co-teacher
Matthew RocklinDask
Alan NicholRasa
Charles FryeModal
Ravin KumarDeepMind
Akshay AgrawalMarimo
Building AI Agents: the open-source course
self-paced · free · 6 sections
A self-paced course on building agent harnesses. Posts, podcasts, workshops, and code from me and my collaborators — plus links to a few external resources too.
A more detailed guide here ↗An agent is just an LLM calling tools in a loop. A harness is everything around it: tools, context, hooks, sandboxes, memory, the loop itself.
The LLM is the brain. The harness is the body.
01 · start here
Build something
Give an LLM read, write, edit, and bash. You have a computer-using agent.
02 · next
Agents that build themselves
Hot-reloading tools, markdown memory, hooks, sandboxes. With Ivan Leo.
03 · deepen
Harness engineering
The deeper conversations. Why context engineering is the new system design.
04 · specialize
Agentic search
Where a lot of this is heading. The traditional search stack falls away.
05 · evaluate
Evals: please do them
End-to-end task success first, then step-level diagnostics.
06 · keep building
Show us your agent skills
A live series. Builders show their actual workflows. Then a cohort if you want depth.
Want it taught live? I also run team workshops and cohort courses on building agents, and on building with AI. Email
workshops@vanishinggradients.co to find out more.
subscribe_to(vanishing_gradients)
Essays, a new podcast, and occasional workshop invitations, in your inbox every week. Read by 13,000+ practitioners and leaders.
13K+ readers · Substack · no spam, ever