Your AI agent works in demos but fails against real operational data.
Operator-Led Businesses
AI Systems, Forward-Deployed
I work with founders, operators, and owner-led businesses to map the real workflow, find the bottlenecks, and deploy AI systems that survive contact with operations: messy data, brittle tools, human approvals, and edge cases included.
Is this the problem?
Your workflows are split across spreadsheets, SaaS tools, inboxes, Slack, docs, and tribal knowledge.
You know there is automation potential, but not where to start.
You need someone who can understand the business system and the technical stack.
You want a working path, not a strategy deck.
What Forward Deployment Means
Traditional consulting stops at advice. Forward deployment goes further: understand the workflow, inspect the data and tools, identify the failure points, and help implement the fix.
The term comes from the forward-deployed engineering model popularized by companies like Palantir: engineers working close to the customer, close to the data, and close to production. My version applies that pattern to AI agents and operational systems.
- Map the operating workflow
- Audit data, tools, prompts, permissions, and handoffs
- Identify agent and automation opportunities
- Prototype or specify the first working system
- Leave a build path your team can execute
Why Ben
The work sits at the overlap of operations, factories, agents, and systems that touch real users.
Hardware scale
Staff TPM at Meta and ex-Apple hardware operations across consumer hardware NPI, factories, quality, supply chain, and launch execution.
Agentic infrastructure
Builder of Injester, Elias on OpenClaw, Data-OnCall, Red Thread, LoopOS, AgentMES, and a home inference fleet.
Operating reality
Runs Stay Ikigai and TurnkeyHost, a five-property short-term-rental operation on custom software, Beds24, Postgres, and Gemini.
Proof under pressure
Three first-place hackathon wins and one top-six finalist in 2026, with shipped systems instead of slideware.
WAYS TO WORK TOGETHER
Forward Deployment Options
Start with a focused call, go deeper with a systems review, or bring Ben in for a deployment sprint when the workflow is important enough to fix properly.
The Operator Call
$399
30 minutes
- Private call with Ben
- One focused decision, workflow, or system bottleneck
- Best for founders and operators who need a fast tactical read
- Leave with the clearest next move
One-time payment at booking
Systems Deep Dive
$1,500
90 minute working session
- Pre-read of docs, workflow, repo, architecture, or data schema
- Diagnosis of failure points and leverage points
- Recommended AI / agent / automation build path
- Written follow-up with next steps
Fit check before booking
Forward Deployment Sprint
Starting at $7,500
Limited availability
- Hands-on advisory over 2-4 weeks
- Workflow mapping, agent architecture, tooling, and implementation guidance
- Async review plus working sessions
- Onsite available when the system requires it
Travel and onsite work scoped separately
Not sure which option fits? Start with the Operator Call or .
Make the Session Useful
The better the operating context, the sharper the read. Bring the actual workflow, not a polished story about it.
- What are you building or operating?
- What workflow is currently painful?
- What tools/data does the workflow touch?
- What have you already tried?
- What decision do you want to leave with?
- Include diagrams, repos, Looms, schemas, docs, or screenshots if useful.
FAQ
Is this consulting or implementation?
Both, selectively. The work starts with diagnosis, but the goal is a practical build path, implementation guidance, or the first working system your team can execute.
Do you write code?
Yes. Ben writes production software and prototypes, but the engagement is scoped around leverage. Sometimes the highest-value output is architecture, workflow mapping, prompts, schemas, or a reviewed implementation plan.
Can you work onsite?
Sometimes. Onsite work can make sense for factories, operations floors, or teams where the real workflow is invisible from a call. Start with the call or deep dive first.
What kinds of teams are a fit?
Founders and operators with a real workflow, messy data, and urgency. The best fit is a team that already feels the operational pain and wants a working system, not abstract AI advice.
What is not a fit?
Generic AI strategy, pitch-deck polish, vendor shopping, or speculative agent ideas without a real operating surface. This is paid, selective, and practical.
Can you partner, invest, or join my company?
Possibly, but not by default. Forward Deployment is paid advisory and implementation work first. If there is a bigger fit, the conversation can go there after the system is understood.
Bring Ben In
Start with the operating system, not the AI demo.
If the system matters and the current path feels fuzzy, start with the Operator Call. If the workflow is already complex, request a Deep Dive.