AI workflow consulting for product teams
A practical approach to agentic workflows, automation, and AI-enabled tooling for startups.
Map the workflow before building
AI wins come from removing the slowest steps in a repeated workflow, not from building a flashy demo.
Start by listing the tasks that happen weekly and decide which can be automated safely.
Prototype fast, harden later
A quick prototype shows whether the workflow is even worth automating.
Once it works, add guardrails like input checks, rate limits, and human review.
Pick a narrow first target
Reporting, QA checks, and internal knowledge lookups are good early wins because the scope is tight.
These give value without changing the core product.
How I help
I build and test workflows with product and engineering teams, then package them into usable internal tools.
The goal is steady time saved, not a one-off experiment.
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Need hands-on support with software consulting, design systems, or AI workflows?