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199: Anna Aubuchon: Moving BI workloads into LLMs and using AI to build what you used to buy

199: Anna Aubuchon: Moving BI workloads into LLMs and using AI to build what you used to buy

Published 8 months, 3 weeks ago
Description

What’s up everyone, today we have the pleasure of sitting down with Anna Aubuchon, VP of Operations at Civic Technologies.

  • (00:00) - Intro
  • (01:15) - In This Episode
  • (04:15) - How AI Flipped the Build Versus Buy Decision
  • (07:13) - Redrawing What “Complex” Means
  • (12:20) - Why In House AI Provides Better Economics And Control
  • (15:33) - How to Treat AI as an Insourcing Engine
  • (21:02) - Moving BI Workloads Out of Dashboards and Into LLMs
  • (31:37) - Guardrails That Keep AI Querying Accurate
  • (38:18) - Using Role Based AI Guardrails Across MCP Servers
  • (44:43) - Ops People are Creators of Systems Rather Than Maintainers of Them
  • (48:12) - Why Natural Language AI Lowers the Barrier for First-Time Builders
  • (52:31) - Technical Literacy Requirements for Next Generation Operators
  • (56:46) - Why Creative Practice Strengthens Operational Leadership

Summary: AI has reshaped how operators work, and Anna lays out that shift with the clarity of someone who has rebuilt real systems under pressure. She breaks down how old build versus buy habits hold teams back, how yearly AI contracts quietly drain momentum, and how modern integrations let operators assemble powerful workflows without engineering bottlenecks. She contrasts scattered one-off AI tools with the speed that comes from shared patterns that spread across teams. Her biggest story lands hard. Civic replaced slow dashboards and long queues with orchestration that pulls every system into one conversational layer, letting people get answers in minutes instead of mornings. That speed created nerves around sensitive identity data, but tight guardrails kept the team safe without slowing anything down. Anna ends by pushing operators to think like system designers, not tool babysitters, and to build with the same clarity her daughter uses when she describes exactly what she wants and watches the system take shape.

About Anna

Anna Aubuchon is an operations executive with 15+ years building and scaling teams across fintech, blockchain, and AI. As VP of Operations at Civic Technologies, she oversees support, sales, business operations, product operations, and analytics, anchoring the company’s growth and performance systems.

She has led blockchain operations since 2014 and built cross-functional programs that moved companies from early-stage complexity into stable, scalable execution. Her earlier roles at Gyft and Thomson Reuters focused on commercial operations, enterprise migrations, and global team leadership, supporting revenue retention and major process modernization efforts.

How AI Flipped the Build Versus Buy Decision

AI tooling has shifted so quickly that many teams are still making decisions with a playbook written for a different era. Anna explains that the build versus buy framework people lean on carries assumptions that no longer match the tool landscape. She sees operators buying AI products out of habit, even when internal builds have become faster, cheaper, and easier to maintain. She connects that hesitation to outdated mental models rather than actual technical blockers.

AI platforms keep rolling out features that shrink the amount of engineering needed to assemble sophisticated workflows. Anna names the layers that changed this dynamic. System integrations through MCP act as glue for data movement. Tools like n8n and Lindy give ops teams workflow automation without needing to file tickets. Then ChatGPT Agents and Cloud Skills launched with prebuilt capabilities that behave like Lego pieces for internal systems. Direct LLM access removed the fear around infrastructure that used to intimidate nontechnical teams. She describes the overall effect as a compression of technical overhead that once justified buying expensive tools.

She uses Civic’s analytics stack to i

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