M.Littlehale&Co.

Not “add a chatbox.” Real AI leverage.

Most AI initiatives stall because they bolt a tool onto a broken workflow. I help restructure how the work actually gets done so AI becomes a multiplier, not another tax. Where we start depends on who you are.

Who I work with

01Setup

Personal

You're a founder, operator, or independent professional who wants AI to be real leverage in your own work. Not a browser tab full of half-used tools and abandoned subscriptions.

I build a working system around how you actually think and ship: the right tools, wired into your real workflow, with the judgment to know what to hand off and what to keep.

How it works

  1. A working session to map how you spend your time and where the leverage actually is.
  2. A setup tuned to you. Tools, prompts, and habits, not a generic stack.
  3. A follow-up once it's in your hands, so it sticks instead of fading after a week.
02Workflow

Small business

You run a small team that knows AI matters but doesn't have a platform group to figure it out. The risk isn't moving too slowly. It's wiring AI into the wrong places and creating work instead of removing it.

I find the one or two workflows where AI genuinely earns its keep, build them with your team, and leave you owning the result. Not dependent on me to run it.

How it works

  1. A short discovery across the business to find the highest-leverage workflow.
  2. A focused pilot on that real workflow. Built with your team, not in a vacuum.
  3. Handoff, with the team trained to extend and maintain what we shipped.
03Strategy

Enterprise

You're leading an organization where AI adoption is already happening. Unevenly, and mostly off the books. The job isn't a tool decision. It's structure: where AI belongs across the SDLC and the product, and how teams adopt it without chaos.

I work at the org level: strategy, guardrails, and an operating model for AI across teams. Real leverage and accountability, not a mandate that gets quietly ignored.

How it works

  1. An assessment across teams to map current usage, risk, and opportunity.
  2. A prioritized roadmap with pilots on the highest-leverage teams first.
  3. The governance and enablement to scale what works across the org.
04Features

Product

You're shipping AI features into the product itself. The hard part isn't picking a model. It's the workflow that wraps it: latency budgets, evaluation harnesses, the UX when the answer is wrong, and the rollback when it gets worse in production.

I work with your product and engineering teams on AI features users actually rely on. The agent that triages support tickets in production. The summarization step that runs a thousand times a day. The recommendation that has to be right at p95.

How it works

  1. Map the AI surface and the failure modes that actually matter to your users.
  2. Build evaluation harnesses and deterministic scaffolding so regressions get caught before they ship.
  3. Progressive rollout, with the team owning what comes after.

Tell me what you're building.