Build Tiny Tools That Remove Real Friction
“Every time I have a question, I ask it to write an app for me.” — Lou
What This Page Is
This page used to be a single insight but accumulated 26 inbound references — a sign that it had become a load-bearing hub doing too much conceptual work. Per the Hub Split Protocol in schema.md, it has been split into three sub-insights, each owning one stage of the tiny-tool building journey: decide → build → leverage. This page is the meta-page that names the three stages and links to each. Use it as an entry point.
The Big Move
One of the most practical breakthroughs in the original session was deceptively simple: stop assuming AI’s job is only to explain the next step. Start asking it to build the thing that removes the friction altogether. Lou’s habit of asking AI to build small one-purpose apps on demand reframes what is possible without requiring you to become a traditional developer. The new literacy is operational imagination, not coding syntax. The new entrepreneurial verb is generate the tool rather than find the tool.
That is the headline. Underneath it sit three distinct decisions, and conflating them is what made the original insight overload.
The Three Stages
1. Decide — Where you build determines what kind of tool it can become
→ Insight - Decide the Abstraction Layer Before You Build
The first decision is not “what feature” but “at what layer.” Markdown checklist, shell script, prompt template, local desktop app, hosted micro-app — each layer up adds capability and cost. The right layer is the lowest one that solves the problem. AI makes higher layers feel cheap, which is exactly why this decision needs discipline.
2. Build — How you structure it determines whether it composes or rots
→ Insight - Design Tiny Tools for Maximum Composability
Once you know the layer, the next move is to build the tool as a member of an ecosystem rather than a private island. Tools that share skills, prompts, and small services compound. Tools built as one-off monoliths become a junk drawer. The composability mindset is what turns a private tool collection into a private leverage graph.
3. Leverage — What you do next determines whether this is a one-shot or an asset
→ Insight - From Solution to Asset - Capture Every Friction-Fix as Reusable IP
The highest-leverage move is treating every finished tool as raw material for two more artifacts: a teachable story (content) and a reusable component (product). Most builders capture only the tool itself. The high-leverage move is the three-layer capture before you move on.
The Sequence
The three stages are not interchangeable — they are sequential, and skipping one bites you specifically:
- Skip “decide” → you overshoot the layer because AI made the higher version feel cheap. You spend a day building a hosted app for a problem a five-line script would have solved.
- Skip “build” → you ship the tool but it shares no plumbing with any other tool. The next nine tools re-implement the same pieces. Maintenance compounds.
- Skip “leverage” → you solve the friction but capture no second-order value. The teachable story decays within the day. The component never gets extracted. The tool stays private and one-shot.
Related Insights
The three sub-insights above are the structural splits. For the broader cluster of related work — abstraction-layer decisions, composability patterns, IP extraction — follow the related-insights from each sub-insight.
Evolution Across Sessions
The original insight was created 2026-04-05 from the 2026-04-02 mastermind session. It became the canonical hub for the entire “tiny tools as personal leverage” theme of the vault, accumulating 26 inbound references by 2026-04-08. At that point it crossed the >15 inbound threshold and was split per the Hub Split Protocol. The three sub-insights preserve the original arguments verbatim where possible; this meta-page replaces the original synthesis with a stage-and-sequence frame.