Blog
Notes on AI Research, OSINT, and Building Workflows That Hold Up
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Understanding AI Context Windows
If AI sometimes feels brilliant in one prompt and forgetful in the next, context windows are usually the hidden constraint, and understanding them changes how you work.
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NotebookLM for High-Stakes Case Research: Why Source-Grounded AI Matters
When accuracy and defensibility matter, NotebookLM offers a more grounded way to work with source material, and the difference becomes obvious once the stakes are real.
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Using NotebookLM Slide Decks and Flashcards for Internal Case Briefings
NotebookLM can turn case notes into grounded slide decks and study materials quickly, which makes it unusually useful for internal briefings where speed matters more than presentation polish.
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Context Engineering for Reliable AI Workflows
Better prompts help, but reliable results usually come from better context design, which is where serious AI workflows start to separate themselves.
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Using AI to Find and Verify News Sources
AI is excellent at surfacing leads and patterns in news research, but the real advantage comes from knowing how to turn those leads into verified source trails.
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AI Misuse in the Real World: Why Bad Workflows Fail Faster
AI does not just speed up good workflows; it accelerates bad ones too, and the lesson from real failures is that a few disciplined checks can prevent expensive mistakes.
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Building an AI Knowledge Base with Obsidian Notes
AI gets far more useful when it is working against notes that are local, linked, and structured, which is why Obsidian can become more than just a note-taking app.
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Confidence Labels and Evidence Logs for Defensible AI Research
AI becomes operationally safer when teams separate confirmed facts from likely inferences and unverified leads, then log the evidence behind each one.
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Using AI to Extract Entities and Build Timelines from Case Files
AI becomes more useful when it pulls names, dates, organizations, locations, and dollar amounts into a structure your team can sort, review, and turn into working timelines.
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Why AI Adoption Should Start with One Active Case and One Internal Champion
AI rollout works better when one active case tests the workflow and one person owns the standard before the rest of the team is asked to follow it.
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Advanced AI Scripting for Research Workflows
AI can now help non-programmers build serious automation, but the real skill is knowing where speed helps, where risk starts, and how to stay on the right side of both.
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Advanced AI Workflows in Cursor and VS Code
Cursor and VS Code are no longer just for engineers; used properly, they can become structured workbenches for teams producing timelines, notes, evidence logs, and briefings.
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Prompt Injection: The Attack That Rewrites Your AI's Instructions
Prompt injection can cause outside content to steer your AI in ways you never intended, which is why high-trust workflows need clear boundaries between source material and system instructions.
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Private AI Infrastructure for Sensitive Casework
Private AI infrastructure can give sensitive teams tighter control over data and model behavior, but the real question is when that control is worth the added operational burden.
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Using OpenAI Codex Desktop for Research Ingestion, Case Management, and Custom Reports
OpenAI Codex Desktop can help advanced teams ingest research, manage case files, and generate custom reports inside a structured local workspace instead of scattering work across disconnected chats and folders.
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Advanced ChatGPT Deep Research Workflows for Source-Cited Briefings
ChatGPT deep research is most useful when it is constrained to trusted sites, uploaded files, and approved apps, then routed into a human-reviewed briefing workflow with citations.
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Advanced AI Monitoring Workflows for Entity Watchlists and Public Web Changes
AI monitoring becomes operationally useful when alerts, live search, archived snapshots, and briefing templates work together to turn public changes into source-cited watchlist reporting.
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AI-Assisted Leak and Discovery Processing for Large Document Sets
Large discovery sets become more useful when OCR, structured extraction, semantic retrieval, and source-linked review turn raw files into a queryable archive instead of a document pile.
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Connecting MCP Servers and Skills Across ChatGPT, Claude Code, and OpenAI Codex
MCP servers and reusable skills become more useful when teams separate protocol access, workflow instructions, and client-specific controls across ChatGPT web, Claude Code, and OpenAI Codex.
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Building Private AI Dashboards for Watchlists, Source Review, and Executive Briefings
Private AI dashboards become useful when alerts, connected data, cited summaries, and recurring briefing templates reduce manual aggregation without hiding the source trail.