Point of view
The position

Most AI adoption doesn't fail because the technology doesn't work. It fails because nobody did the design work first. Effort shifts somewhere less visible and gets called efficiency. Outcomes quietly drift to match what the AI can deliver rather than what the work actually requires. I've seen both happen — and neither shows up on a dashboard until it's already embedded.

The real work is deciding what stays human before you touch the tools. Relationship. Judgment. Accountability. Context that can't be captured in a prompt. Get that boundary wrong and you haven't automated anything — you've just moved the problem.

Where the line belongs
Stays human
Relationship building and trust Complex training and enablement Account and customer management Opportunity identification Strategic brainstorming Final decision making Contextual judgment — reading the room, the relationship, the moment
Built for AI
Research and synthesis Pattern recognition Assumption validation Idea stress-testing Iterative problem solving Repetitive and readable tasks Documentation and summarization Information synthesis across sources
The line isn't always a handoff. Sometimes AI runs alongside the human work without replacing it.
AI in practice
What's running, what's being built
Active — What's running
Synthesis

Pre-kickoff Intelligence Brief

AI ingests account notes and call recordings to produce a structured customer brief before every kickoff. Replaces manual document hunting.

Documentation

Account Update Generator

Takes call summaries and produces formatted stakeholder updates after every implementation touchpoint.

Pattern Recognition

Audience Auditor

Accepts multiple audience files, identifies overlap and redundancy, produces a consolidation recommendation.

Summarization

Handover Documentation

AI drafts the end-of-implementation record for clean handoff — platform config, decisions made, training status, research pipeline.

Generation

Custom Spreadsheet Builder

Produces customer-specific structured spreadsheets built around their platform setup and program design.

In Progress — Being built
Synthesis + Project Intelligence

Per-Customer AI Agents

Custom agents that connect call recordings, manage project trackers, and surface to-dos — giving each implementation its own persistent AI layer that knows the account.

Analysis

Training Gap Assessor

Identifies coverage gaps across training sessions and surfaces what still needs to be addressed before handoff.

Generation

Kickoff Deck Personalization

Customer-specific deck generation from a templated base.

Exploring — Next frontier
Recommendation

Solution Pairing Guidance

Guided AI recommendation for research approach based on customer goals and platform setup.

Generation

Research Pipeline Visualizer

Branded graphic showing confirmed and potential research program — what's locked vs. what's coming.

Delivery

Async Training Support

AI-delivered resources and guidance between live training sessions.

What I'm building
Updated as work ships
Apr 2026 Built merlinkomenda.com via Claude Code. Full site architecture, deployment pipeline, serverless functions, and ongoing infrastructure — no agency, no developer. Claude Code as the build partner throughout.
Apr 2026 Deployed interactive leadership reporting suite. Live dashboards connected directly to data sources — giving senior leadership self-serve access to annual, quarterly, and monthly performance data. Replaced static reporting with an always-available analysis layer.
Mar 2026 Built autonomous multi-agent system. A network of AI agents that communicate and operate independently without human triggering. Always running. Built to explore the boundaries of agent autonomy and inter-agent coordination.
Ongoing Per-customer AI agents in development. Building account-specific agents that synthesize call recordings, manage project trackers, and surface next steps — giving each implementation its own persistent AI layer.
What I'm still working out

My default is to protect the nature of the work from AI reshaping it. But I'm less sure that's always right. Some processes are outdated and AI just makes that impossible to ignore. I haven't fully resolved when redesign is the right call versus resistance — and that's what I want to think through with people doing this work.

I think out loud on LinkedIn — follow the thinking there.

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