On-demand AI-native engineers

Plank trains and embeds forward-deployed engineers into technical teams that need to build, deploy, and validate production AI faster than they can hire.

Powering AI & FDE engineering at

The Plank AI Accelerator

How Plank develops AI-native engineers

Every Plank engineer is developed through the Plank AI Accelerator, hands-on training in the realities of production AI work: agents, RAG, customer deployment, modern AI tooling, and high-quality engineering habits, then embeds with pod-mates they have already shipped with.

Agentic dev workflow

Shipping with Claude Code + Codex

AI applications

LLM features and products, end to end

Agents & retrieval

Multi-agent systems and RAG

Voice & multimodal

Real-time voice and video AI

Production & deployment

Shipping, monitoring, and reliability

Forward deployment

Customer integration and rollout

Every cohort trained and every team embedded makes the next deployment faster.

Inside the Plank AI Accelerator

How we ship

Harness-driven SDLC

Plank engineers steer a pool of AI agents through a controlled harness, so a small pod ships like a much larger team, with review, QA, and safe deploys built into every pull request.

AI pair-coding

Engineers steer Claude Code and Codex on every feature while the agents do the typing.

  • Small, frequent PRs against main
  • The engineer reviews and merges every diff

Conductor + worker pool

A conductor drafts the spec and hands work to a pool of agents running in parallel.

  • Each agent works in its own clone
  • The conductor never edits code, git is the audit log

Quality, woven in

Nothing reaches production unreviewed or untested, quality is built in.

  • Cross-model review + manual QA on every PR
  • Per-feature blue/green deploys, with fast rollback

Built for production AI from day one

Plank engineers start the same day, stay vendor-neutral, and arrive as a pod that has already shipped together.

Start the same day

Plank engineers embed and start the same day, then ship to production in days, speed of engagement and speed of delivery from the first call, while hiring the same role typically takes two to four months.

Vendor-neutral

Plank engineers work across OpenAI, Anthropic, and open models, so your architecture stays yours.

Trained for production AI

Every engineer is developed in the Plank AI Accelerator, hands-on training in agents, deployment, and modern AI tooling, then embeds with pod-mates they have shipped with before.

Inside the Plank AI Accelerator

Your IP, your repos

NDAs by default, your code in your repositories from day one, and clean IP assignment. Your architecture and your IP stay yours.

Put an embedded AI team on your roadmap

Forward-deployed engineers to deploy, AI-native engineers to build, and on-demand QA pods to validate, embedded with your team, starting the same day.