Choose the right AI approach: Start in context, not tools
Stop picking tools first. Start from your role, goals, and constraints so you choose the right AI approach, run a small pilot, measure, then scale what works.
AI learning path guide: Pick your lane before your first step
AI isn’t one monolith. This AI learning path guide maps five lanes—ambient, chat, tooling, building, training—so you can align with your role and take the next clear step.
Outcome-driven product design: Proven systems for results
AI made baseline UI cheap, but the edge is outcome-driven product design—coherent systems, instrumentation, and brand alignment that move real metrics.
Build Judgment Fast: How to Evaluate and Refactor AI Code
AI can write code; your edge is judgment. This piece shows how to evaluate and refactor AI code quickly—spot smells, iterate refactors, and turn AI into an accelerator.
Set Boundaries with AI: Restore Judgment and Clarity
Name the parasocial dynamic, treat AI as a tool, and set boundaries with AI to keep clarity and human judgment in your workflow. Practical prompts and guardrails show how.
Run Solo Business with AI: Treat It Like a Strategy Partner
AI can be your first hire—codifying judgment, automating busywork, and pressure-testing strategy so one person ships at team speed. Here’s how to run solo business with AI without adding headcount.
Advanced AI for complex bugs: why precision beats patterns
Escalate models based on problem complexity and demand refinements, tradeoffs, and edge‑case coverage to get reliable fixes. This repeatable workflow turns stubborn 1‑in‑20 bugs into shipped confidence.
API design for AI agents: resilient responses that guide recovery
When searches return nothing, agents freeze. API design for AI agents should return context, confidence, alternatives, and next actions to keep momentum.
Avoid Generic AI Content: Prep Specs, Constraints, and Proof Before You Pick a Model
Prep beats model swapping. Set specs, constraints, and evidence to avoid generic AI content and ship sharper drafts with almost any competent model.
LLM function calling best practices: the strategist-toolbox shift
LLM function calling best practices start with a simple shift: let the model orchestrate and your tools execute. Practical guardrails and schemas make it dependable.