From idea to AI pilot: how to test it without betting the company
How to turn a use case into a bounded AI pilot: success metric set before you start, stopping criterion, limited scope and mitigations. No hype.
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All AI Coding Patterns
Technical articles: agents, architecture, tools and design decisions.
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Risk-impact matrix: which AI project to start with
How to prioritize AI projects by crossing business impact with risk of error. Start with high-impact, low-risk work, without burning your budget.
ChatGPT for Better Work: Context, Not Magic Prompts
Being productive with ChatGPT isn't about collecting perfect prompts—it's about giving it context and knowing how to iterate. A practical guide to get started without technical knowledge.
What is an agentic loop: definition and example
An agentic loop is the cycle an AI agent repeats until it meets its goal. The pieces, an example, and how it differs from prompt chaining.
Context Engineering: The Skill That Replaced Prompt Engineering
Context engineering means governing what the model sees at every step, not polishing the prompt. Techniques, cache costs, and trade-offs, backed by verified data.
AI vendor lock-in: the risks and how to reduce them
What AI vendor lock-in is, its three real risks, and a realistic plan to avoid getting trapped with a single provider.
Spec-driven development: from vibe coding to team memory
Vibe coding works for prototypes and falls apart once you have to maintain them. Spec-driven development turns the spec into persistent memory for your AI agents.
AI SaaS: What to Demand Before You Sign
Before signing an AI SaaS, demand five things in writing: what it does with your data, reliability, portability, usage pricing, and model changes.
Skills and MCP security: your invisible supply chain
Installing a skill or connecting an MCP server means running third-party code inside your agent. 2026 data and a checklist for auditing security without slowing your team down.
The Delegation Gap: You Use AI at 60%, But Only Delegate 20%
You use AI in 60% of your work but only delegate 20%. What the delegation gap is, and why it closes with verification, not better models.
Buy or Build AI: How to Decide Without Overspending
Buy AI SaaS, build custom, or wait. An honest framework to decide how to acquire AI in your company based on real cost and vendor dependency.
Loop engineering: the loop is the product, not the code
Loop engineering: designing the loop in which your agent writes, tests, and self-corrects. Context, verification, feedback, and stopping condition.