Useful Machinery

I spent the summer talking to engineering leaders about how AI adoption is playing out in their organizations. Each conversation had rhyming anecdotes. Effectiveness is jagged. Every team has an AI-whisperer managing agent swarms and pushing dozens of parallel tasks. They are thrilled to reinvent their workflow every other week when a new S-tier model drops. The rest of the team is tired of the treadmill, more interested in just getting their jobs done. A team’s impact ceiling is higher than ever before but the floor hasn’t come up with it.

AI has made so much automation possible that if an existing process hasn’t broken yet, it’s liable to break with the next model release. How do you even define a best practice anymore? Everything software developers have validated and codified over decades of experimentation is suspect. In order to rapidly learn new AI techniques engineering orgs emphasized adoption. They established leaderboards and celebrated tokenmaxxing. VPEs that definitely know better are measuring individual activity metrics like PRs per engineer. The industry has collective amnesia about the learnings of DORA and SPACE.

The saying goes, “If you want to go fast, go alone. If you want to go far, go together.” Teams need more effective ways to disseminate and evolve practices to collectively better leverage AI. No organization is going to achieve a 90% automated SDLC or software factory with disparate individual processes.

We founded Useful Machinery to get you on a better path. You have a successful business with honed pre-AI processes. Useful Machinery’s platform meets your team where it is. We automate, standardize, and centralize existing workflows while maintaining human judgement where maturity and risk tolerances deem it appropriate. You can then incrementally ratchet up the automation globally. When a new model drops, your team should be able to try it on feature work you already understand and see whether it clears the same checks. If it does the job better, you can update things once and everyone immediately gets the benefit.

In our own application of Useful Machinery we’ve pushed the automation envelope. We’re operating an SDLC process in the way we envision all software organizations will eventually. We deliver quality software with extremely high levels of automation. We leverage both deterministic and agentic techniques for our ideal blend of speed, cost, and rigor. Background workflows routinely eliminate flakey tests, refactor to enforce architectural boundaries, and identify pain points in our onboarding process. Team members routinely improve workflows that immediately accelerate us all.

Your team can achieve the same starting from where you are today. To learn more check out our landing page and reach out.