Your engineers are one of your biggest investments. Help them turn AI into a force multiplier—with practical workflows, coding agents, and the confidence to take on more.
Unlock your team’s potentialHands-on AI coaching and consulting for software teams, SaaS companies, and individual engineers.
Maybe your team hasn’t embraced AI yet. Maybe you use Claude or ChatGPT every day, but the gains still feel incremental. The next step is learning how to put AI to work across the engineering tasks that slow you down.
A 5× or 10× ambition needs more than better prompts. It needs context, repeatable workflows, and a reliable way to check the work. We help you build those habits, then measure what improves in your own environment.
Help experienced engineers spend more time solving important problems, with AI carrying more of the execution.
Build AI into the engineering work that consumes your week: understanding unfamiliar code, planning changes, writing tests, debugging, and reviewing pull requests. We shape workflows around your codebase and delivery process.
Move from one-off chats to repeatable ways of getting work done. We connect coding agents, project context, and custom tools so engineers can delegate more of the execution while staying accountable for the result.
Whether you’re an individual engineer finding your stride or a team still getting started, we work alongside you on real tasks. Learn what to delegate, how to verify the output, and when your own judgment matters most.
An engineer was already using Claude and ChatGPT. The bigger opportunity was to build a system around the way they worked—and help the rest of the team benefit from it.
AI was part of the individual’s toolkit, but it hadn’t yet become a coordinated way of delivering work.
We helped build a custom control plane and conductor application that brought specialized bots and engineering workflows together in one place. The system was tailored to the individual’s specific tasks and ways of working.
The engineer became more fluent in working with AI, then shared the workflows and what they had learned with teammates. Individual progress became a starting point for broader team adoption and greater productivity.
These Agent Control concepts reimagine the control plane from the case study with an anonymized interface. They show the kind of workspace we can tailor to a team—not an off-the-shelf product.
Your agents, your work, one clear view.
A shared view of agent work, review queues, and delivery stages. Human decisions stay visible as work moves forward.
Specialists configured for your engineering workflow.
Read the project context before reviewing changes.
Check correctness, clarity, tests, and security.
Explain the reasoning behind actionable feedback.
Flag decisions that need an engineer’s judgment.
Give each specialist a role, reusable instructions, and the connections it needs. Build around the way your team actually works.
platform-api · Agent-assisted change
Session expiry handling has been checked against the task context. The implementation includes explicit expiry behavior and regression coverage.
Bring the task, agent activity, checks, and review handoff together so an engineer can inspect the work before it moves on.
On a smaller screen, swipe across the mockup to explore the workspace.
A look at the roles a custom control plane can bring together. Your team sets the direction and makes the decisions.
Helps turn an open question into a clearer starting point.
Helps carry a well-defined task through implementation.
Helps surface questions and feedback for an engineer to consider.
Helps examine the result before it reaches a human decision point.
Original concept characters and example roles. Each engagement’s agent setup is tailored to the team; internal instructions and workflow details are not shown.
A practical engagement built around your engineers, your codebase, and the bottlenecks that hold delivery back.
We look at how your team works today, where AI adoption stalls, and which tasks offer the clearest opportunity. Together, we define what better looks like.
We pair on real engineering work, configure agents and context, and develop workflows your team can use again. Progress comes from practice.
We document what works, teach verification habits, and review the results against your starting point—so the capability stays with your team.
Focus on useful changes: shorter feedback loops, less repetitive work, and more room for complex problems. Every engagement has a custom scope and project-based quote.
We work with your stack, delivery practices, and current level of AI adoption. The workflow has to make sense for the engineers who use it.
Engineers stay responsible for design, review, and correctness. We teach teams how to inspect AI output, test assumptions, and recognize when to step in.
Tell us where your team is with AI—and where you want to go. Starting from scratch, stuck at autocomplete, or ready to work with agents? Let’s find a useful next step.
Every engagement starts with a conversation.
Custom scope. Clear outcomes. Project-based pricing.