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nickhac/README.md
Nick Holmes à Court — Technical founder and engineering leader. 3× VC-backed, 2 exits. 20+ years, 200+ production systems, ex-AWS VC manager.

LinkedIn Substack Email


▲ Now Shipping


  AGENT INFRA 

 Relationship infrastructure for AI agents: agent identity, intent graphs and connector patterns, so agents remember who they work with and why.

BUILT — Production prototypes plus reusable connector patterns.
Founder and lead engineer


  AUTONOMOUS GTM 

 Paste a URL and agents run the full GTM workflow: ICP, landing pages, cold email, prospect lists. A 5-email sequence in 13.8 seconds. Founder approves, system executes.

RESULT — Built in 21 days. 97.8% agent run success. Patched its own production bug and shipped the fix, unattended.
Product and systems lead · Case study →


  🏆 HACKATHON WINNER 

 Rapid revenue prototype built under event constraints at the SF Hermes Hackathon, Jul 2026.

RESULT — Winner: most revenue generated in cohort.
Lead engineer


  AGENT FACTORY 

 Agentic software factory: fixed-scope 21-day sprints from defined problem to live production system. Proof case: Blackline, a government accountability engine that logged 274,659 signals and mapped $164.6B in dollar exposure in its first two weeks.

BUILT — The system that builds the systems.
Architect and engineering lead · The build → · The findings →


■ Operating Range


 ENGINEERING 


Computer Science degree. 20+ years across Python, JavaScript, C#, SQL, REST and FastAPI, ETL and BI. Personally shipped and managed 200+ production systems: multi-tier, cloud-native, event-driven, API-first.


 AI SYSTEMS 


Hands-on daily with Cursor, Hermes, Amazon Bedrock and open-source models. Built copilots, multi-agent orchestration, evaluation systems and tool-calling stacks. Research focus: intent graphs, verification architectures, context compression.


 CLOUD & VC 


Former Venture Capital Manager at AWS. Worked with hundreds of startups, VC firms and CTOs from Seed through IPO on architecture, migration, security and scaling.


 ENTERPRISE 


Direct work with Australia's largest organisations: board and C-suite stakeholder management, procurement, security review, solution architecture and AI strategy.


 PRODUCT & GTM 


Founder-led sales, enterprise negotiation and value engineering. Operated as CEO, CPO and founder: translates deep tech into commercial outcomes, not features.


● Build Stack

frontend   Next.js · React · TypeScript · Tailwind
backend    Node.js · Python · Postgres · MongoDB · ClickHouse · Temporal
ai         Cursor · Hermes · Bedrock · open-source LLMs · vector DBs
agents     multi-agent orchestration · tool-calling · eval harnesses
infra      AWS · Vercel · Cloudflare · GitHub Actions
workflow   atomic commits · focused PRs · verification-first CI

◈ Research & Writing

Data first, opinion second. I build the dataset, then write what it says.


 GITHUB SCANNER 


The Loudest People in Australian AI Aren't Building Anything
Built a pipeline to scan GitHub for Australians actually shipping AI code, then compared it against who talks about AI. The overlap is small.


 20 YEARS OF M&A 


ANZ Startup Acquisitions: Who Buys, and What They Pay
Twenty years of Australian and New Zealand tech M&A, analysed for Post Exit Founders AU: acquirer patterns, price bands and what actually gets bought.


 600M ATO ROWS 


I Spent Six Months Modelling Leaving Australia. The Math Was Brutal.
Six months of modelling on 600 million ATO data points, productised as ExitProof.com.au. First 100 respondents: average $4.8M better off over 10 years offshore. Discussion on LinkedIn.


 1,691 COMPANIES 


The Venture Efficiency Report 2025
Screened every US venture-backed company that raised $20M+ in 2025 for revenue per dollar raised. Median efficiency: $0.11 per $1. The distribution is uglier than anyone admits.


 28 OUTLIERS 


The 28 Quiet Winners
The follow-up screen: above $0.50 revenue per $1 raised, $10M+ revenue, under 150 people. 39% are consumer brands, not SaaS. Grüns: 8.57× efficiency. The LinkedIn post drew 793 reactions and 984 comments.

 FULL ARCHIVE ON SUBSTACK → 


◆ Operating Principles


 01 

Verify, then trust

Agents earn autonomy through test harnesses, eval loops and human review on risky changes. Speed without auditability is chaos.



 02 

Intent is the spec

Model what humans mean, not just what they type. Intent graphs turn ambiguity into executable, reviewable work.



 03 

Revenue is a feature

Every system ships against a commercial outcome. Built to be sold, adopted and renewed, not just demoed.



 FULL EXPERIENCE PROFILE → 


BUILD WITH ME →   LinkedIn · Substack ·

📍 Sydney / San Francisco

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