// Topic
Business
Definition
Business coverage in this archive spans 4 posts from Feb 2016 to Mar 2026 and links technical decisions to margin, distribution, and execution durability. The strongest adjacent threads are ai, leadership, and startups. Recurring title motifs include ai, infrastructure, startup, and landscape.
Working claims
- The posts consistently push for explicit unit economics and practical tradeoffs over narrative hype.
- The consistent theme from 2016 to 2026 is disciplined execution over hype cycles.
- This topic repeatedly intersects with ai, leadership, and startups, so design choices here rarely stand alone.
How to apply this
- Tie roadmap bets to measurable outcomes: cost, throughput, risk reduction, or revenue impact.
- Start with the newest post to calibrate current constraints, then backtrack to older entries for first principles.
- When boundary questions appear, cross-read ai and leadership before committing implementation details.
Where teams get burned
- Treating technical strategy as branding instead of an operating constraint.
- Running broad experiments without clear stop conditions or budget discipline.
- Applying guidance from 2016 to 2026 without revisiting assumptions as context changed.
Suggested reading path
- Start here (current state): AI Startup Landscape 2026
- Then read (operating middle): Pitching Infrastructure to People Who Don’t Care About Infrastructure
- Finish with (foundational context): The True Cost of Technical Debt
Related posts
- AI Startup Landscape 2026
- Measuring AI ROI Without Lying to Yourself
- Pitching Infrastructure to People Who Don’t Care About Infrastructure
- The True Cost of Technical Debt
References
5 posts
- AI Capital Allocation: What Great CTOs Stop Funding First
Strong AI strategy starts with a kill list. If a project cannot defend margin, risk, or speed, it should not survive the next budget meeting.
AI Startup Landscape 2026
By early March 2026, the AI startup market looks less like a gold rush and more like a durable industry with clear pressure points. This post lays out where leverage sits, what buyers reward, and what durable execution looks like now.
Measuring AI ROI Without Lying to Yourself
Most AI ROI calculations are fantasy. Here's how to measure honestly: pick one workflow, capture the full cost, tie benefits to outcomes the business already tracks, and report a range instead of a single number.
Pitching Infrastructure to People Who Don't Care About Infrastructure
Your board doesn't care about Kubernetes. They care about money, risk, and speed. Here's how I learned to pitch infra investment at the fintech startup.
The True Cost of Technical Debt
A pragmatic look at technical debt in 2016: what it is, how it shows up, how to measure it, and how to make a business case for paying it down without stalling delivery.