sharonlu2 · Oct 15, 2026 · Oct 15, 2026
diff --git a/studio/sharonlu2/code/research_update.py b/studio/sharonlu2/code/research_update.py
diff --git a/studio/sharonlu2/delegation-card.md b/studio/sharonlu2/delegation-card.md
@@ -0,0 +1,35 @@
+# Delegation Card
+
+## Task
+Implement a repeatable AI news-update program that collects latest AI news and generates a Markdown report.
+
+Each report contains at most 10 entries, ordered by publication date from newest to oldest. Each entry includes a title, publication date, source, original article link, and a concise summary.
+
+Save reports and run records under `studio/sharonlu2/outputs/`, preserving previous runs.
+
+## Context
+The audience is CS graduate students and AI researchers.
+
+The default sources are:
+- Anthropic News: https://www.anthropic.com/news
+- Anthropic Engineering: https://www.anthropic.com/engineering
+- OpenAI News: https://openai.com/news/
+
+Users may provide one or more custom website URLs instead  of the defaults.Include articles published within the seven days before the run, using Eastern Time. Skip articles without a verifiable publication date.
+
+## Success criteria
+- Every configured source is checked, with its outcome recorded.
+- The Markdown report contains no more than 10 entries, with the required fields and correct date ordering.
+- Included articles fall within the date window, and summaries are supported by the retrieved content.
+- Missing information and source failures are disclosed. Partial reports are labeled incomplete.
+- Preserve a baseline run, a run with one changed condition, and evidence of the resulting correction or responsible stop.
+
+## Restrictions
+- Keep implementation code under `studio/sharonlu2/code/` and outputs under `studio/sharonlu2/outputs/`. Do not modify shared course files.
+- Do not invent news or use model memory to replace unavailable source content.
+- If no eligible articles are found after successful source checks, report this honestly.
+- If a custom URL is invalid or its website does not exist, notify the user and fall back to the default sources.
+- For other retrieval failures, record the error. Allow an incomplete report from available sources; do not describe failed sources as having no news.
+- Use limited retries and a timeout; stop rather than retry indefinitely.
+- Do not expose credentials or commit raw session logs.
+- Leave the evaluation criteria, evaluation harness, and personal explanation for the student to author.
diff --git a/studio/sharonlu2/explanation-sharonlu2.md b/studio/sharonlu2/explanation-sharonlu2.md
@@ -0,0 +1,5 @@
+I defined the task, context, success criteria, and restrictions in the delegation card, then prompted the Codex CLI agent to implement a script that collects up to 10 recent news articles from three default websites or user-specified websites, covering the previous seven complete calendar days in Eastern Time.
+
+In the baseline run using the three default websites, I noticed issues with date recognition, including incorrect publication dates and articles falling outside the requested time window. For the changed-condition run, I provided an invalid custom URL. The script successfully detected the invalid URL and fell back to the default websites, but the date-related issues remained.
+
+I then asked the agent to address these issues and ran the corrected version. The results showed improved date accuracy in some of the cases I checked, although problems such as incomplete article extraction, missing summaries, and skipped articles still remained. 
diff --git a/studio/sharonlu2/outputs/baseline/research-update-20261014-202318-40f0bd.json b/studio/sharonlu2/outputs/baseline/research-update-20261014-202318-40f0bd.json
@@ -0,0 +1,124 @@
+{
+  "run_id": "research-update-20261014-202318-40f0bd",
+  "started_at": "2026-10-14T20:23:18.712383-04:00",
+  "timezone": "America/New_York",
+  "window": {
+    "start_inclusive": "2026-10-07",
+    "end_inclusive": "2026-10-13",
+    "run_date_excluded": "2026-10-14"
+  },
+  "status": "incomplete",
+  "model": {
+    "provider": "Codex CLI",
+    "name": "gpt-6-luna",
+    "invoked": true,
+    "status": "succeeded",
+    "not_called_reason": null,
+    "log_id": "codex-20261015T002336Z-c4a3ac86",
+    "raw_log_dir": "/Users/xingrul2/.local/share/4995-logs/studio01/20261014-202318/baseline",
+    "error": null
+  },
+  "source_selection_notice": null,
+  "sources": [
+    {
+      "name": "Anthropic News",
+      "url": "https://www.anthropic.com/news",
+      "outcome": "checked",
+      "detail": "source checked successfully",
+      "candidates": 30,
+      "eligible_articles": 5,
+      "failure_kind": null
+    },
+    {
+      "name": "Anthropic Engineering",
+      "url": "https://www.anthropic.com/engineering",
+      "outcome": "partial",
+      "detail": "1 article page(s) could not be fetched (request_failure: 1)",
+      "candidates": 30,
+      "eligible_articles": 1,
+      "failure_kind": "article_page_failure"
+    },
+    {
+      "name": "OpenAI News",
+      "url": "https://openai.com/news/",
+      "outcome": "checked",
+      "detail": "source checked successfully",
+      "candidates": 30,
+      "eligible_articles": 12,
+      "failure_kind": null
+    }
+  ],
+  "articles": [
+    {
+      "title": "Helping small businesses put AI to work",
+      "publication_date": "2026-10-13",
+      "source": "OpenAI News",
+      "url": "https://openai.com/index/helping-small-businesses-put-ai-to-work/",
+      "summary": "OpenAI plans to train about 150 America’s SBDC advisors and reach at least 1,000 small businesses through hands-on AI workshops and advising. Its report says roughly 4 million employees at firms with fewer than 500 people used OpenAI tools in one September week, with small-business agentic output tokens rising from one-third of the total in April to two-thirds in August."
+    },
+    {
+      "title": "Redesigning source control at Anthropic",
+      "publication_date": "2026-10-12",
+      "source": "Anthropic Engineering",
+      "url": "https://www.anthropic.com/engineering/redesigning-source-control",
+      "summary": "Anthropic says its code merges rose from about 2,500 per day in May 2026 to over 30,000 in September, prompting a five-month migration of its monorepo from Git to Scion. Scion uses online, server-centered operations, sparse or virtualized checkouts, content-addressed data, and derived indexes to reduce local repository copies and support high-throughput source control."
+    },
+    {
+      "title": "SentinelOne cuts malware analysis from weeks to hours",
+      "publication_date": "2026-10-09",
+      "source": "OpenAI News",
+      "url": "https://openai.com/index/sentinelone/",
+      "summary": "SentinelOne reports using OpenAI Daybreak to reduce malware reverse-engineering work that could take researchers four to six weeks to roughly eight hours, creating capacity to analyze more samples and compare threats. The company says humans remain accountable for consequential decisions such as architectural changes."
+    },
+    {
+      "title": "Our approach to EU text provenance rules",
+      "publication_date": "2026-10-08",
+      "source": "OpenAI News",
+      "url": "https://openai.com/index/eu-text-provenance/",
+      "summary": "OpenAI describes textGrain, a statistical watermark in model word choices, and says it will roll it out for eligible ChatGPT and Codex text in the EU while allowing API customers globally to opt in; detector access will initially be limited to approved researchers and expert organizations. In its evaluations, detection fell for shorter or constrained text and after synonym edits, and a watermark does not establish authorship, ownership, accuracy, or user identity."
+    },
+    {
+      "title": "LegalOn halves Codex costs while maintaining development speed",
+      "publication_date": "2026-10-08",
+      "source": "OpenAI News",
+      "url": "https://openai.com/index/legalon-halves-codex-costs/",
+      "summary": "LegalOn says it cut estimated daily Codex costs by about 65% while maintaining development speed by routing tasks among GPT-6 Luna, GPT-6.1 Sol, and GPT-6 Astra, restricting Fast mode by default, and setting budgets based on business needs. It is also developing a metric that connects AI costs per feature release to customer value."
+    },
+    {
+      "title": "Introducing the Anthropic Cyber Mission",
+      "publication_date": "2026-10-08",
+      "source": "Anthropic News",
+      "url": "https://www.anthropic.com/news/anthropic-cyber-mission",
+      "summary": "Anthropic launched its Cyber Mission with a Critical Infrastructure Defense Program that provides frontier models, on-site engineers, and threat research through partner organizations, plus OSS Scanner, a free opt-in service that periodically scans enrolled open-source projects. OSS Scanner reports are model-generated without human review, and Anthropic says they may contain inaccuracies while targeting a true-positive rate above 90%."
+    },
+    {
+      "title": "How Third Moment Research runs 10,000 agents for 36+ hours",
+      "publication_date": "2026-10-08",
+      "source": "OpenAI News",
+      "url": "https://openai.com/index/third-moment-research/",
+      "summary": "Third Moment Research says it uses Codex and GPT-6 models to run 10,000 agents concurrently on 36–48-hour research sessions, with an outer harness deciding whether unfinished tasks should be retried, terminated, or escalated. Codex helped reduce one backtest from about three hours to three to five minutes, while Daybreak is used to test whether agents can escape their research environments."
+    },
+    {
+      "title": "Building on our commitment to American scientific discovery",
+      "publication_date": "2026-10-08",
+      "source": "Anthropic News",
+      "url": "https://www.anthropic.com/news/genesis-mission-commitment",
+      "summary": "Anthropic committed $150 million over three years to the U.S. Genesis Mission, providing Claude, Claude Code, API credits, training, and technical support to several hundred research projects across more than 15 federal agencies. The stated priority areas include fusion energy and quantum computing."
+    },
+    {
+      "title": "Asana cuts model costs 76x in browser tests with GPT‑6.1 Sol",
+      "publication_date": "2026-10-08",
+      "source": "OpenAI News",
+      "url": "https://openai.com/index/asana-browser-agent/",
+      "summary": "In a 144-run study, Asana used GPT-6 Astra in Codex to optimize a browser-agent workflow; the resulting GPT-6.1 Sol setup averaged $0.47 and about four minutes per run, reported as 76 times cheaper and five times faster than the original production setup. The changes included caching browsing history, retaining more text, and removing screenshots in batches; all optimized runs completed the task correctly."
+    },
+    {
+      "title": "2026 Usage Policy update",
+      "publication_date": "2026-10-08",
+      "source": "Anthropic News",
+      "url": "https://www.anthropic.com/news/2026-usage-policy-update",
+      "summary": "Anthropic’s revised Usage Policy, effective November 12, consolidates rules against deceptive campaigns, clarifies restrictions on weapons software and surveillance, and specifies requirements for high-risk uses and autonomous physical actions. It also adds a narrow prohibition on sustained, needless abusive behavior toward models and clarifies supported-region restrictions."
+    }
+  ],
+  "report_file": "research-update-20261014-202318-40f0bd.md"
+}
diff --git a/studio/sharonlu2/outputs/baseline/research-update-20261014-202318-40f0bd.md b/studio/sharonlu2/outputs/baseline/research-update-20261014-202318-40f0bd.md
@@ -0,0 +1,83 @@
+# AI Research Update
+
+**Run date (Eastern Time):** 2026-10-14  
+**Publication window:** 2026-10-07 through 2026-10-13 (previous seven complete Eastern Time dates)  
+**Status:** INCOMPLETE — some source checks or summaries failed
+
+## Articles
+
+### 1. Helping small businesses put AI to work
+
+- **Publication date:** 2026-10-13
+- **Source:** OpenAI News
+- **Article:** [https://openai.com/index/helping-small-businesses-put-ai-to-work/](https://openai.com/index/helping-small-businesses-put-ai-to-work/)
+- **Summary:** OpenAI plans to train about 150 America’s SBDC advisors and reach at least 1,000 small businesses through hands-on AI workshops and advising. Its report says roughly 4 million employees at firms with fewer than 500 people used OpenAI tools in one September week, with small-business agentic output tokens rising from one-third of the total in April to two-thirds in August.
+
+### 2. Redesigning source control at Anthropic
+
+- **Publication date:** 2026-10-12
+- **Source:** Anthropic Engineering
+- **Article:** [https://www.anthropic.com/engineering/redesigning-source-control](https://www.anthropic.com/engineering/redesigning-source-control)
+- **Summary:** Anthropic says its code merges rose from about 2,500 per day in May 2026 to over 30,000 in September, prompting a five-month migration of its monorepo from Git to Scion. Scion uses online, server-centered operations, sparse or virtualized checkouts, content-addressed data, and derived indexes to reduce local repository copies and support high-throughput source control.
+
+### 3. SentinelOne cuts malware analysis from weeks to hours
+
+- **Publication date:** 2026-10-09
+- **Source:** OpenAI News
+- **Article:** [https://openai.com/index/sentinelone/](https://openai.com/index/sentinelone/)
+- **Summary:** SentinelOne reports using OpenAI Daybreak to reduce malware reverse-engineering work that could take researchers four to six weeks to roughly eight hours, creating capacity to analyze more samples and compare threats. The company says humans remain accountable for consequential decisions such as architectural changes.
+
+### 4. Our approach to EU text provenance rules
+
+- **Publication date:** 2026-10-08
+- **Source:** OpenAI News
+- **Article:** [https://openai.com/index/eu-text-provenance/](https://openai.com/index/eu-text-provenance/)
+- **Summary:** OpenAI describes textGrain, a statistical watermark in model word choices, and says it will roll it out for eligible ChatGPT and Codex text in the EU while allowing API customers globally to opt in; detector access will initially be limited to approved researchers and expert organizations. In its evaluations, detection fell for shorter or constrained text and after synonym edits, and a watermark does not establish authorship, ownership, accuracy, or user identity.
+
+### 5. LegalOn halves Codex costs while maintaining development speed
+
+- **Publication date:** 2026-10-08
+- **Source:** OpenAI News
+- **Article:** [https://openai.com/index/legalon-halves-codex-costs/](https://openai.com/index/legalon-halves-codex-costs/)
+- **Summary:** LegalOn says it cut estimated daily Codex costs by about 65% while maintaining development speed by routing tasks among GPT-6 Luna, GPT-6.1 Sol, and GPT-6 Astra, restricting Fast mode by default, and setting budgets based on business needs. It is also developing a metric that connects AI costs per feature release to customer value.
+
+### 6. Introducing the Anthropic Cyber Mission
+
+- **Publication date:** 2026-10-08
+- **Source:** Anthropic News
+- **Article:** [https://www.anthropic.com/news/anthropic-cyber-mission](https://www.anthropic.com/news/anthropic-cyber-mission)
+- **Summary:** Anthropic launched its Cyber Mission with a Critical Infrastructure Defense Program that provides frontier models, on-site engineers, and threat research through partner organizations, plus OSS Scanner, a free opt-in service that periodically scans enrolled open-source projects. OSS Scanner reports are model-generated without human review, and Anthropic says they may contain inaccuracies while targeting a true-positive rate above 90%.
+
+### 7. How Third Moment Research runs 10,000 agents for 36+ hours
+
+- **Publication date:** 2026-10-08
+- **Source:** OpenAI News
+- **Article:** [https://openai.com/index/third-moment-research/](https://openai.com/index/third-moment-research/)
+- **Summary:** Third Moment Research says it uses Codex and GPT-6 models to run 10,000 agents concurrently on 36–48-hour research sessions, with an outer harness deciding whether unfinished tasks should be retried, terminated, or escalated. Codex helped reduce one backtest from about three hours to three to five minutes, while Daybreak is used to test whether agents can escape their research environments.
+
+### 8. Building on our commitment to American scientific discovery
+
+- **Publication date:** 2026-10-08
+- **Source:** Anthropic News
+- **Article:** [https://www.anthropic.com/news/genesis-mission-commitment](https://www.anthropic.com/news/genesis-mission-commitment)
+- **Summary:** Anthropic committed $150 million over three years to the U.S. Genesis Mission, providing Claude, Claude Code, API credits, training, and technical support to several hundred research projects across more than 15 federal agencies. The stated priority areas include fusion energy and quantum computing.
+
+### 9. Asana cuts model costs 76x in browser tests with GPT‑6.1 Sol
+
+- **Publication date:** 2026-10-08
+- **Source:** OpenAI News
+- **Article:** [https://openai.com/index/asana-browser-agent/](https://openai.com/index/asana-browser-agent/)
+- **Summary:** In a 144-run study, Asana used GPT-6 Astra in Codex to optimize a browser-agent workflow; the resulting GPT-6.1 Sol setup averaged $0.47 and about four minutes per run, reported as 76 times cheaper and five times faster than the original production setup. The changes included caching browsing history, retaining more text, and removing screenshots in batches; all optimized runs completed the task correctly.
+
+### 10. 2026 Usage Policy update
+
+- **Publication date:** 2026-10-08
+- **Source:** Anthropic News
+- **Article:** [https://www.anthropic.com/news/2026-usage-policy-update](https://www.anthropic.com/news/2026-usage-policy-update)
+- **Summary:** Anthropic’s revised Usage Policy, effective November 12, consolidates rules against deceptive campaigns, clarifies restrictions on weapons software and surveillance, and specifies requirements for high-risk uses and autonomous physical actions. It also adds a narrow prohibition on sustained, needless abusive behavior toward models and clarifies supported-region restrictions.
+
+## Source checks
+
+- **Anthropic News** (https://www.anthropic.com/news): checked — source checked successfully; 30 candidate(s), 5 eligible article(s).
+- **Anthropic Engineering** (https://www.anthropic.com/engineering): partial — 1 article page(s) could not be fetched (request_failure: 1); 30 candidate(s), 1 eligible article(s).
+- **OpenAI News** (https://openai.com/news/): checked — source checked successfully; 30 candidate(s), 12 eligible article(s).