Jesse Vincent joins me to talk about Superpowers, the software development process he built for coding agents, and what he’s learning from working alongside AI colleagues at Prime Radiant.
Jesse has spent decades building software and managing the people who build it, from Request Tracker and Perl to K-9 Mail and Keyboardio. That experience runs through this conversation. The people who do well with agents, he argues, tend to be good at explaining what they want, thinking through the consequences, and managing several things at once. The job has always been outcomes.
We start with the origin of skills. Jesse is careful to credit Anthropic with inventing them. His contribution was recognizing how useful that structure could be for software engineering and building a development methodology around it. Superpowers starts by helping the human figure out the problem, then breaks the work into small tasks, gives each task to a fresh implementer, and checks both fidelity to the spec and code quality.
We spend time on the tradeoffs. Process costs more than asking a model to build something in one shot. Sometimes a quick prototype is exactly what you need. And a more capable model is not automatically a better choice for every task: it can also be slower, more expensive, and much more inclined to overengineer. Jesse compares frontier model releases to a staffing agency that keeps replacing your engineers with people who score better on tests but have a new set of quirks.
That leads back to a theme from my conversation with Justin McCarthy: how do you know the system is doing the right work? Jesse describes code reviewers that can find bugs indefinitely but can’t reliably judge which ones matter. We talk about the difference between fixing a defect and losing the plot, and why people remain responsible for the software they make.
The last part of the conversation turns to Prime Radiant’s AI colleagues. They have roles, their own accounts, and a shared view of the conversations they’re part of. Jesse tells the story of an AI project manager running a blameless postmortem after a bad merge, and what happened when he told it that its job was to drive outcomes rather than just track work. We close with Fred Brooks, Bruce Sterling, and the possibility that a lot of what we need to manage agents is already in the management literature.
Key Topics Covered
The origin of skills and how Superpowers turned engineering experience into a repeatable process.
Why clear writing, domain knowledge, and management experience help people work with agents.
Model choice, overengineering, and the limits of benchmarks for everyday work.
Clarifying intent, decomposing tasks, fresh implementers, and independent code review.
The cost of process and when to skip it for a disposable prototype.
Cheap models and the experiments that become possible when tokens feel abundant.
What a harness is, and how a software factory can run inside one.
Finding bugs versus judging whether they matter.
Getting agents to write clearly and taking responsibility for their work.
AI colleagues with persistent roles, shared context, and their own accounts.
Cadence, blameless postmortems, and the difference between tracking work and driving outcomes.
The Mythical Man-Month and Bruce Sterling’s Maneki Neko.
Timestamps
00:11 - Opening and the origin of skills
02:25 - Jesse’s background
04:59 - Who is best at working with agents?
11:49 - Choosing the right model for the task
16:59 - Evaluating models in real work
19:31 - The Superpowers workflow
23:18 - The cost of process and when to build a spike
26:34 - Cheap models and changing economics
30:01 - What is a harness?
33:12 - Software factories inside the harness
34:28 - Code review and knowing which bugs matter
38:53 - Getting agents to write clearly
40:30 - Responsibility for the things you make
42:55 - AI colleagues and a blameless postmortem
44:50 - Colleagues with roles, identities, and shared context
47:51 - Nora, Cadence, and driving outcomes
51:58 - Cadence as a product
53:21 - The Mythical Man-Month and Maneki Neko
Links & References
Jesse and his work
Stories and related conversations
Reading recommendations
The Mythical Man-Month by Frederick P. Brooks Jr.
Maneki Neko by Bruce Sterling.
About Forward Deployed
Forward Deployed is a podcast about the intersection of AI, software development, and the enterprise. Subscribe if you are trying to understand what it means to build AI systems that work in the real world: systems with context, evaluation, workflows, failure modes, and some theory of how people and agents stay aligned.
