Designing for Adaptability
The pace of model updates has forced me to rethink permanence. Prompts that worked six months ago don’t always behave the same way today. That instability isn’t a flaw; it’s a condition of the environment. So I’ve been…
AI Thoughts
Ongoing notes on strategy, tooling, and building with AI.
AI as a Strategic Layer
This month I’ve been thinking about AI less as an operational assistant and more as a strategic layer sitting above everything else. Not just drafting or summarizing, but shaping how decisions are framed in the first pl…
The Year of Orchestration
Looking back, 2025 wasn’t about discovering new tools. It was about orchestrating them. Designing how models, prompts, automation layers, and human review interact coherently. The evolution feels subtle but significant.…
Data Discipline as Advantage
The cleaner the inputs, the sharper the outputs. I’ve invested more time in organizing internal knowledge — standardized naming conventions, structured documentation, consistent formatting. AI rewards order. Disorganize…
Where AI Still Fails
I intentionally pushed AI into edge cases: ambiguous scenarios, emotionally nuanced communication, conflicting objectives. The failures are instructive. Patterns emerge. AI struggles when trade offs require value judgme…
Agentic Experiments
I revisited semi autonomous workflows with more structure. Instead of open ended “agents,” I tested bounded systems with explicit objectives, evaluation criteria, and stopping conditions. Autonomy without clarity drifts…
The Economics of Speed
I’ve been analyzing how iteration velocity changes competitive positioning. If one team can test ten strategic variations in the time another tests three, the probability of finding a superior outcome increases. AI does…
AI and Client Advisory
I’ve been integrating AI into advisory work carefully. It sharpens analysis, surfaces overlooked angles, and stress tests recommendations. But the responsibility remains mine. The key insight is that AI enhances prepara…
Designing Resilient Workflows
Models update. Features change. Tools disappear. I’ve started designing workflows that can survive those shifts. Modular steps. Clear inputs and outputs. Replaceable components. Resilience matters more than optimization…
AI and Brand Consistency at Scale
Maintaining brand voice across multiple outputs is harder than generating content. I’ve been experimenting with constraint driven prompts: fixed sentence length ranges, prohibited phrases, tone anchors, structural rules…
Decision Acceleration
I’ve been focused on shortening the time between question and clarity. AI compresses research cycles dramatically, but the real benefit shows up in faster iteration loops. Idea → critique → refinement can happen in minu…
Evaluating Model Differences
I ran identical workflows across multiple AI models to observe differences in reasoning, tone, and reliability. Some models feel more decisive. Others are more cautious. The variance is subtle but strategically relevant…
Versioning Prompts Like Code
I began tracking prompt changes the way developers track software revisions. Small tweaks in structure, tone constraints, or example inputs materially change outcomes. Without versioning, it’s impossible to know what ac…
AI as Infrastructure
This year I stopped thinking about AI as a tool and started treating it like infrastructure. Prompts became protocols. Workflows became pipelines. Instead of asking, “Can AI help with this task?” I began asking, “Where…
Compounding Small AI Wins
Looking back at the year, the biggest gains didn’t come from massive breakthroughs. They came from dozens of small workflow improvements — each shaving minutes, reducing friction, clarifying decisions. Compounding is su…
Operationalizing Creativity
Creativity used to feel unpredictable. Now I’m testing structured ideation frameworks powered by AI — constrained brainstorming sessions, category driven expansion, forced analogy exercises. The surprising result is tha…
Bias Detection in Decision-Making
I ran parallel decisions this month — one made independently, one assisted by AI prompts designed to challenge assumptions. The difference isn’t always dramatic, but blind spots become visible faster. I’m noticing that…
AI for Strategic Thinking
I’ve begun using AI less for content and more for pressure testing ideas. I feed it assumptions, ask for counterarguments, request edge cases. The tool becomes a structured adversary. The insight isn’t that AI replaces…
Context Windows & Compression
I’ve been testing how much information is truly necessary to produce high quality output. Large context windows are powerful, but they also invite clutter. More input can dilute signal. This month has been about compres…
Measuring Leverage, Not Output
I’ve stopped tracking volume. More drafts, more ideas, more content means very little. I’m now tracking leverage: time saved, decision clarity gained, reduction in cognitive load. The shift is subtle but important. AI s…
Building Internal AI Playbooks
Experiments are useful, but undocumented experiments are wasted. I’ve started turning successful workflows into internal playbooks — clear prompt structures, examples, failure cases, and revision notes. The process feel…
Reducing Friction Intentionally
Most automation conversations focus on eliminating friction. I’m exploring the opposite: which friction is productive? A pause before sending. A second pass before publishing. A checkpoint before execution. The paradox…
Testing Multi-Step Agents
Single prompts feel increasingly primitive. I’ve been testing structured chains: research → outline → critique → refine → finalize. Each step has its own constraints and objective. The outputs feel more coherent when th…
AI and Revenue Alignment
I started asking a harder question: does this AI workflow tie directly to revenue, margin, or retention? Productivity gains are interesting, but they’re not automatically valuable. If faster output doesn’t connect to ec…
Automation Boundaries
I’ve been actively mapping what should not be automated. It’s easy to get intoxicated by speed, but certain areas — financial decisions, sensitive communication, strategic positioning — carry asymmetric downside risk. T…
Designing Human-in-the-Loop Systems
This year started with a shift in how I think about automation. Instead of asking how much I can remove myself from a workflow, I began asking where my judgment matters most. I stopped chasing full autonomy and started…
From Operator to Orchestrator
By the end of the year, my role had subtly shifted. I was spending less time executing individual tasks and more time designing how tasks moved between systems. The work became less about output and more about orchestra…
Workflow Redesign
Instead of layering AI onto old processes, I began redesigning workflows from scratch. If AI were native to the system, how would I structure it? This reframing exposed inefficiencies I had normalized. Some steps existe…
Speed vs. Depth
As outputs accelerated, I questioned whether depth was eroding. Faster drafts can encourage premature conclusions. I tested slowing the process intentionally — asking for critiques and counterarguments before moving for…
AI for Research Compression
I experimented with feeding long reports and asking for structured distillation. Bullet pointed summaries, decision briefs, key risks highlighted. The value wasn’t in replacing reading entirely. It was in compressing in…
Stacking Tools Together
I started connecting AI outputs with other automation platforms. Draft generation feeding into email systems. Summaries populating documentation tools. Individual tasks began linking into pipelines. The insight was that…
AI and Creative Voice
I tested whether AI could maintain a distinct voice across multiple drafts. The results were mixed. Tone drifted when instructions were loose, but improved when I defined structural rules and examples. It became clear t…
Data In, Quality Out
I began noticing how dramatically input quality affected results. Vague briefs produced vague answers. Structured context produced sharper thinking. This wasn’t about AI intelligence. It was about input discipline. When…
Building Prompt Libraries
Instead of rewriting prompts from scratch, I began saving and categorizing what worked. Sales messaging. Strategic analysis. Research summaries. Each refined over time. The value wasn’t just in the outputs but in the re…
Separating Hype from Utility
The noise around AI grew louder, and I felt the need to evaluate more critically. Which tools actually improved my workflow? Which were impressive but unnecessary? This month was about restraint. I tested features delib…
AI as Draft Partner
I leaned heavily into using AI for first drafts. Not final deliverables — scaffolding. It removed the friction of the blank page and allowed me to react to something tangible instead of staring at possibility. I realize…
Prompting as Skill
I started noticing that better instructions led to dramatically better outputs. That realization reframed everything. Prompting wasn’t a trick; it was a form of systems thinking. The more clearly I defined role, objecti…
First Real AI Workflows
At the start of 2023, I moved from curiosity to application. Instead of casually experimenting with AI outputs, I began embedding it into actual workflows — drafting proposals, outlining strategy documents, summarizing…