I make companies AI-native · hands on, end to end

"What should we do with AI?"The answer isn't a deck. It's working software.

I'm Rohit Sharma — operator for 20 years. I transformed my own company into an AI-native business. Now I do it for yours.

Book an intro call See the proof
$23M+raised as Kanmon co-founder — Bessemer, Homebrew, Inspired, FIS
56xgrowth as VP Product, Funding Circle — through IPO
$9.5B+moved through products my teams built
20+ yrsfintech & data products — D&B, Plastiq, Dell
How I think

Every company wants AI doing real work. Few have it — and the difference isn't a smarter model. It's the harness around it. A model is raw horsepower; the harness — the connections to your systems, the testing, the guardrails, the governance — is what turns it into work you can trust.

I've built both halves — the agents that do the work, and the harness that makes them trustworthy — running every day at my own company. No handoff to "implementation partners": I build it with you, strategy through code.

Work with me

Three doors in. All end in running software.

For engineering orgs

Ship faster

Your codebase is older than the tools. You want agentic engineering that sticks — not a Copilot license and a shrug.

  • Coding-agent rollout that survives your codebase
  • An MCP tool layer over your systems — build once, swap harnesses freely
  • AI-native dev workflow with review gates

Agentic Engineering Transformationembedded with your team · measured on cycle time

For finance & ops teams

Run leaner

Teams drowning in manual knowledge work. The flagship: an AI employee — an always-on agent embedded in your company that learns the business and takes over jobs, one at a time.

  • Lives in Slack and your systems; builds its own skills as it learns
  • Targeted builds: close, reconciliation, monitoring, document analysis
  • Permissions, evals, and an audit trail — show it to your auditor

Ops Automation Buildone workflow, or a full AI employee · pilot → production

For GTM & revenue teams

Sell more

Revenue teams buried in manual motion — decks, data entry, reporting. Work that steals selling time.

  • Opportunity-tailored decks, on brand, in minutes not days
  • CRM reporting and pipeline visibility, automated
  • Rev-ops workflows: enrichment, routing, follow-up

Revenue Automation Buildpilot → production

Not sure which door? · Start here

AI Opportunity Audit

2–3 wks · fixed fee

A ranked roadmap of AI wins across your company — plus a working prototype of the #1 item, not just a document.

Fractional AI Lead — ongoingmonthly retainer · roadmap, builds, vendor and model calls

The dividends

What going AI-native actually bought — function by function.

A sample, not the whole list — the doors above, delivered.

Ship faster · engineering & product

Simple changes shipped end-to-end by coding agents — humans review, agents do.

  • Tickets created and triaged automatically
  • Customers get answers in-flow from an AI agent, day and night
  • Documents parsed automatically, in the flow of business
Run leaner · finance, risk, ops & data

Decisions that took days per file now take minutes — same rules every time.

  • A quarterly-scale monitoring task, now daily and automated
  • Monthly close reconciled to the cent; memos fact-checked before they ship
  • Anyone queries the warehouse in plain English, through Slack
Sell more · GTM

Collateral and one-pagers produced on demand, on brand.

  • Pipeline updates and CRM hygiene handled in Slack
  • Call logs analyzed automatically
  • Every customer-facing number verified against the warehouse
On the side

losaltos.space — a neighborhood directory that runs itself. Born from 2,000 buried WhatsApp messages, it now serves real neighbors every day: new recommendations flow in automatically, search learns from what people couldn't find, and SEO tunes itself from real search data — agents propose, guardrailed scripts decide, and every change is an audited commit.

The workbench

Tools I run in production

Not logos I've evaluated — tools I pay for and use daily. Vendor-neutral by practice.

Coding agentsClaude CodeCodex CLICursor
Agent harnessesOpenClawAnthropic Managed AgentsClaude Desktop
Tool layerMCPFastMCPOAuthguardrailed writes
ModelsAnthropicOpenAIGoogle
Data & infraSnowflakedbtPostgresGCP
EvalsCustom Eval HarnessOpik
Evals before scaleNothing rolls out that can't be measured.
Ship behind flagsReversible beats impressive.
Governance in codePolicy in documents gets skipped. Policy in code gets enforced.
Right-size the intelligenceLLMs where the job is fuzzy. Code where it isn't.
About

Operator first. Consultant second.

Twenty years as an operator — first product hire through an IPO, GM, co-founder. I transformed my own company into an AI-native business, building the agents, tool layer, and evals with my own hands.

MS in Computer Science, MBA — I speak both rooms. My house runs on six AI agents.

Find me
Career file
  • Kanmon — Co-founder · $23M+ raised
  • Funding Circle — VP Product & Design · IPO
  • Plastiq — GM, Growth & Retention
  • Dun & Bradstreet — Director, PM · $20M+ API line
  • Education — MS Computer Science · MBA
Operator at KANMON · FUNDING CIRCLE · PLASTIQ · DUN & BRADSTREET · DELL
© 2026 Helicon Works · Rohit Sharma GitHub · llms.txt · humans.txt Helicon: home of the Muses — and of Hari Seldon.