> AI, implemented.
Take your AI initiatives from stuck to shipped.
runpoint//pipeline
Take your AI initiatives from stuck to shipped.
// Explain the problem
Your CEO has read the articles. Seen the demos. Set expectations.
Now your team is stuck: Smart people running pilots that never ship fast enough to justify the investment or make good on the promise.
Six-month timelines. Steering committee approvals. Security training before you write a line of code. By the time you ship, GPT-6 is out and does it out of the box.
Traditional agencies: Strategy decks and roadmaps. Then they hand you back the problem.
AI consultants: They'll build you a prototype. Then disappear before it touches production.
The result: Rudderless experiments. Siloed efforts. No follow-through. Your initiative stays stuck while competitors ship.
ERROR: Timeout Project: Q3_2024_ChatBot Status: Pending approval (184d)
ERROR: Deprecated Project: Document_Analyzer Status: Superseded by GPT-5
ERROR: Resource unavailable Project: Sales_Assistant Status: Blocked (GitHub access)
// Show the solution
MIT says 95% of AI projects fail. Good. That's supposed to happen.
Bezos's hit rate at Amazon? About 10%. His secret? Enough at-bats that the 10% covered the 90%.
You need to structure your AI initiatives like a venture portfolio: Quick wins (proven ROI in weeks), moonshots (10x potential), and infrastructure (makes everything else possible). Spread risk. Accept failures. Move fast.
You don't need a dev team. You need the right individual.
The Operator Engineer is a new archetype: Someone with business instincts who's run things, knows what problems actually matter, and has obsessive curiosity about AI. Technical ability? That's actually the least important skill. We can teach Claude Code in a month. We can't teach operator instinct.
Knows which problems actually move the needle
Can vibe code their way through prototypes
Building on weekends because they want to
Execs set the priorities. We handle everything downstream: features, tech stack, workflows, user testing. We're aligned to your do-ers, not your PowerPoint schedule.
Speed matters: We ship prototypes in days, production systems in weeks. Monthly retainers, continuous iteration, measurable business impact.
// Give examples
Not all "AI" is the same. The term covers everything from simple automation to autonomous agents.
Understanding where your work falls on this spectrum helps you choose the right tools, set realistic expectations, and avoid the common trap of applying agent-level thinking to automation-level problems.
The key distinction: Deterministic vs. Probabilistic.
If your processes are pre-defined with fixed rules, you're in deterministic territory—same input, same output, every time.
If AI has discretion to adapt its approach based on context, you're in probabilistic territory—same goal, different paths to get there.
"You design it, tools execute it"
AI coding assistants and automation platforms help you build traditional software and workflows faster. Workflows are trigger-based and execution is completely predictable. You're the architect—AI just speeds up the building.
"AI contributes, you orchestrate"
AI generates content or makes decisions at specific steps in your workflow. The structure is still rigid and pre-defined, but AI adds intelligence where you specify. Inputs and outputs are predictable even if the exact content varies.
"Agent decides how to accomplish your goal"
You give the agent a goal, tools, instructions, and knowledge. It determines the best approach, adapts to unexpected inputs, and handles diverse scenarios without predefined paths. It has discretion over how to use its tools and when to ask for help.
// Demonstrate credibility
It's a reasonable question. Everyone and their cousin is shilling AI. But that's because it is a gold rush.
It's new. It's transformative. It can be a little confusing.
So let's start with what we're not, and what we are.
// Tell them how to engage
Structure the chaos before you build
Investment: $5,000 (credited toward retainer)
Outcome: Clear roadmap and organizational buy-in
Your embedded AI execution arm
Investment: Starts at $15K/month per partner
Outcome: Production AI shipping weekly with measurable impact
Enable your internal AI builders
Investment: Add-on to strategy or retainer
Outcome: Self-sufficient team shipping independently
⭐⭐⭐⭐⭐
"These guys are operators who code. They understand business context in a way no tech team does. They think like founders, build like engineers, and ship like they've got equity." — Evan, Partner at JSTAR
// The Takeaway
The framework is simple:
Build something that works for one person, solves one real problem, and maps to your company's top priorities. Don't be precious. Don't worry about scale. Don't add features because you might need them later.
Ship it ugly. Learn fast. Iterate or kill it.
START → Real problem? → Maps to priorities? → Works for 1 person? → SHIP
↓ NO ↓ NO ↓ NO
KILL KILL ITERATE
Start with the 5-minute playbook. Or skip ahead and schedule a call.