AgenticBuilder

Advanced prompt engineering — systematic, versioned, regression-tested, Shipped prompt chains that survive contact with real users, not just demo data, Proficient with no-code/low-code automation tools at the complex end of the spectrum: multi-step workflows, conditionals, error handling, loops, API literacy without hand-holding: read docs, handle OAuth/API keys, parse JSON, paginate, retry, respect rate limits, Understands data shapes and how poorly formatted output breaks downstream steps, Can read, lightly edit, and debug code (Python, JavaScript) produced by AI coding assistants, Familiar with LLM concepts: context windows, temperature, tool use, structured outputs, RAG basics, Eval and observability mindset, Cost awareness: can estimate token cost per run, spot a workflow that will bankrupt itself at scale, and choose model tier (Haiku/Sonnet/Opus or equivalent) deliberately, Thinks in workflows, not tasks — naturally maps processes end-to-end before touching a tool, Comfortable designing for failure: edge cases, fallback paths, and human escalation, Can scope what should and shouldn't be automated — knows when a human decision is irreplaceable, Can sit in a business team conversation and extract the automatable signal from the noise, Understands enough about functional operations (finance cycles, campaign pipelines, hiring workflows, CS escalations) to build for how teams actually work, not how they say they work, Can explain why something works (or doesn't) to people who don't code — without talking down to them or hiding behind jargon, Recognize when a workflow touches personal data, financial data, customer data, or regulated content and route to central governance before shipping, not after, Understand basic threat surface: prompt injection, data exfiltration via tool calls, over-permissioned agents, secret handling, Comfortable with audit trails, access scoping, and "least privilege" defaults, Ships working solutions — demonstrates bias toward done over perfect, with a clear standard for what 'done' means, Owns outcomes, not just outputs — follows through on whether the automation is actually being used and delivering value, Earns trust quickly within business teams by demonstrating domain curiosity and delivering fast, Comfortable operating as a change agent in teams that may be skeptical — wins people over through results, not persuasion, Knows when to escalate and involve central engineering — and how to hand off cleanly