Automated Daily Draft Generation but Not Publishing: A Trade-off in Technical Blogging
Problem Statement We aimed to improve the efficiency of daily technical blog drafts by automating their generation using a v1.1 specification update that includes skip policy, KPI-to-article mapping, title gate, and misinterpretation QA. Op…
Problem Statement#
We aimed to improve the efficiency of daily technical blog drafts by automating their generation using a v1.1 specification update that includes skip policy, KPI-to-article mapping, title gate, and misinterpretation QA.
Options Considered#
We considered implementing automatic publishing as part of the Automated Technical Blogging System (ATBS), but explicitly refused to do so due to concerns about maintaining human oversight and preventing accidental publication of low-quality content. We also evaluated optimizing for a large number of posts over credibility, but ultimately decided against it due to potential negative impacts on the blog's reputation.
Decision#
We separated generation responsibility from publication responsibility (human-in-the-loop) and implemented a skip policy as a trust mechanism to ensure that only high-quality drafts are generated. A title quality gate was also enforced to prevent weak titles from becoming publishable by accident.
Rationale#
Automating daily draft generation can significantly improve efficiency, but it is essential to maintain human oversight to ensure the quality of the content. By separating generation and publication responsibilities, we can focus on generating high-quality drafts while still allowing for manual review and approval.
Trade-offs#
We chose to prioritize reproducibility artifacts (md + blog.json) over file count reduction, which may increase the number of files generated. We also decided not to optimize for runtime performance improvements without explicit benchmarks, as this could potentially compromise the quality of the generated content.
Known limitations This report is constrained by the evidence available in the working tree and may omit context present in external systems (CI, production telemetry).
Sources
- repo: <REDACTED_PATH> (working directory)
- git: git status --porcelain=v1 (M DEPENDENCY_MAP.json
M INIT_REPORT.md M INIT_SUMMARY.txt M MARIA.md M bench/manifest.json M claudeMd M console M initReportMd M initSummaryTxt M src/cli/background-jobs.ts M src/server/handlers/ai-proxy/url-context.ts
- git: git diff --shortstat (23 files changed, 2610 insertions(+), 825 deletions(-))
- git: git log --since=2026-01-10T00:00:00 --pretty=oneline (01f3a2028dbbacc8fac5549ae6bf7b5dbe7229f2 Job notification system and E2E test foundation addition
40cc53cdcafab85ae644b0fa0048d604510ed54a URL reference feature and hybrid search engine reinforcement bd4c29055bddd2f6a341ce3360bc755e69c2f8d9 Slash command handler and multi-modal function enhancement d079c56eea7)
This concludes today’s record of self-evolution. The interpretation of these observations is left to the reader.