Notes on building.
Guides on mobile apps, web platforms and AI products. Cost breakdowns, stack comparisons and how we ship.
AI for Marketplace Growth: Matching, Pricing, and Trust in 2026
Two-sided marketplaces struggle with cold-start, pricing, and trust. AI-powered matching, dynamic pricing, and fraud detection can increase liquidity by 30 to 50%.
AI & strategy · Mar 12, 2026 · 14 min read
How to Build AI Tool-Use Agents with MCP and A2A in 2026
MCP crossed 97M monthly SDK downloads and A2A joined the Linux Foundation. Here is how to combine these protocols to build agents that discover tools, invoke APIs, and collaborate.
AI & strategy · Mar 11, 2026 · 15 min read
AI for Revenue Operations: Automating Your GTM Stack in 2026
60% of B2B SaaS companies plan to automate RevOps with AI by 2027. Here is how to implement AI-powered lead scoring, pipeline forecasting, and deal intelligence today.
AI & strategy · Mar 11, 2026 · 14 min read
Multi-Model AI Strategy: Using Claude, GPT, and Gemini Together
73% of production AI apps now use multiple LLM providers. Here is how to build a multi-model strategy that optimizes for cost, quality, and reliability without vendor lock-in.
AI & strategy · Mar 11, 2026 · 14 min read
How to Measure AI Engineering Team Productivity in 2026
AI coding tools can reduce development cycles by 40 to 60%, but CTOs struggle to measure the ROI. Here are frameworks for tracking AI-assisted productivity without gaming metrics.
AI & strategy · Mar 11, 2026 · 14 min read
How to Price AI Features: Usage, Seat, and Bundled Pricing in 2026
A practical, opinionated guide to pricing AI features in 2026. Compare usage, seat, credits, and bundled models with real examples from Notion, Intercom, and Linear.
AI & strategy · Mar 9, 2026 · 14 min read
AI Model Routing: Cut LLM Costs with Smart Orchestration in 2026
Most teams run every prompt through their most expensive model. AI model routing sends easy requests to cheap models and hard requests to premium ones, cutting LLM spend 40-70% without sacrificing quality.
AI & strategy · Mar 9, 2026 · 13 min read
AI Observability: Logging, Tracing, and Debugging LLM Apps in 2026
LLM apps are non-deterministic, expensive, and fail silently. Here is how to build a production observability stack that catches hallucinations, tracks costs, and debugs agents without losing your mind.
AI & strategy · Mar 9, 2026 · 14 min read
How to Hire AI Engineers vs ML Engineers for Your Startup in 2026
AI engineers and ML engineers solve very different problems, yet most startups conflate them and waste six figures on the wrong hire. Here is how to tell them apart, what to pay, and where to find the people who actually ship.
AI & strategy · Mar 9, 2026 · 14 min read
From AI Prototype to Production: Shipping LLM Features in 2026
Most AI prototypes never ship. This playbook walks through the exact stages, systems, and org structure required to move an LLM feature from demo to production.
AI & strategy · Mar 9, 2026 · 15 min read
How to Fine-Tune an LLM for Your Domain: A Practical Guide in 2026
Fine-tuning was supposed to be obsolete after RAG. Then LoRA made it cheap and Llama made it accessible. Now it is back as a serious tool for domain accuracy. Here is how to do it without wasting six figures.
AI & strategy · Mar 8, 2026 · 13 min read
AI Content Moderation at Scale: A Technical Guide for Platforms
Every platform with user-generated content discovers content moderation the hard way. AI-powered moderation is now table stakes, but most teams build it wrong. Here is the architecture that actually works.
AI & strategy · Mar 7, 2026 · 13 min read