This document discusses several stories related to a project involving the Google Spreadsheet API and IBM Watson API. It notes issues encountered with the novice architecture used for the Google Spreadsheet API project, including incomplete input validation and lack of readiness to scale. It also covers topics like caching, input limitations, and performance issues for the IBM Watson API. The document advocates for an approach that avoids quick fixes for the wrong problems, and emphasizes qualitative growth through scenarios and experience over time.

1. When juniors fail.

2. Roman & Dmytro

4. Project “S.”

6. Google Spreadsheet API.Story #1.
=if(query(FinalOutput!$A$2:$AZ$1000, SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(“SELECT {{Openness}} WHERE {{Name}} = ‘Alex Mot’ AND {{department}}
= ‘Sales’“, “{{Openness}}“, REGEXEXTRACT(ADDRESS(1, MATCH(“Openness”, FinalOutput!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), “{{Name}}“,
REGEXEXTRACT(ADDRESS(1, MATCH(“Name”, FinalOutput!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), “{{department}}“, REGEXEXTRACT(ADDRESS(1,
MATCH(“department”, FinalOutput!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), -1) <> “”, ((query(FinalOutput!$A$2:$AZ$1000,
SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(“SELECT {{Openness}} WHERE {{Name}} = ‘Todd Weiland’ AND {{department}} = ‘Sales’“, “{{Openness}}“,
REGEXEXTRACT(ADDRESS(1, MATCH(“Openness”, FinalOutput!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), “{{Name}}“, REGEXEXTRACT(ADDRESS(1,
MATCH(“Name”, FinalOutput!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), “{{department}}“, REGEXEXTRACT(ADDRESS(1, MATCH(“department”,
FinalOutput!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), -1)) - (query(Params1!$A$2:$AZ$1000, SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(“SELECT {{mean}}
WHERE {{variable}} = ‘Openness’ AND {{department}} = ‘Sales’“, “{{mean}}“, REGEXEXTRACT(ADDRESS(1, MATCH(“mean”, Params1!$A$1:$AZ$1, 0), 4,
TRUE), “[a-zA-Z]+“), 1), “{{variable}}“, REGEXEXTRACT(ADDRESS(1, MATCH(“variable”, Params1!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1),
“{{department}}“, REGEXEXTRACT(ADDRESS(1, MATCH(“department”, Params1!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), -1))) /
(query(Params1!$A$2:$AZ$1000, SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(“SELECT {{sd}} WHERE {{variable}} = ‘Openness’ AND {{department}} = ‘Sales’“,
“{{sd}}“, REGEXEXTRACT(ADDRESS(1, MATCH(“sd”, Params1!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), “{{variable}}“, REGEXEXTRACT(ADDRESS(1,
MATCH(“variable”, Params1!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), “{{department}}“, REGEXEXTRACT(ADDRESS(1, MATCH(“department”,
Params1!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), -1)) * (query(Params1!$A$2:$AZ$1000, SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(“SELECT {{beta}}
WHERE {{variable}} = ‘Openness’ AND {{department}} = ‘Sales’“, “{{beta}}“, REGEXEXTRACT(ADDRESS(1, MATCH(“beta”, Params1!$A$1:$AZ$1, 0), 4,
TRUE), “[a-zA-Z]+“), 1), “{{variable}}“, REGEXEXTRACT(ADDRESS(1, MATCH(“variable”, Params1!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1),
“{{department}}“, REGEXEXTRACT(ADDRESS(1, MATCH(“department”, Params1!$A$1:$AZ$1, 0), 4, TRUE), “[a-zA-Z]+“), 1), -1)), “”)
- Batch delete.
- Bulk save.
- Circular calculations.
- Query builder.
- CRUD limited for cols/rows.

9. - Novice architecture.
- Questions to community.
- Google-solution.
- Incomplete input validation.
- Not ready to scale.
Architecture.Story #2.

10. Story #3.
IBM Watson API.
- Public API with limitations.
- Caching.
- Input limitations.

11. - Performance.
- Fat builds.
- Updates mechanism.
- Security.
Electron.js.
Story #4.

12. - Estimates.
- Deployment & Delivery.
- Code-review process.
- Communication.
Approach.
Story #5.

13. - Quick fixes (wrong problems).
- Googling.
- Scenarios.
- Freedom!
Experience. Qualitative growth.
Story #6.

14. Experience matters.