Boundary Action Auditing Against Staged Prompt Injection
article · ~2 min
Defending long-horizon AI agents requires auditing decisions at the exact boundary before each consequential action (not just screening inputs or reviewing completed runs), and tracing what data source and influence shaped each element of a pending action can reliably distinguish attacker-manipulated steps from benign ones.
Binary Pass/Fail Scoring for LLM Judges
Hamel Husain · youtube · ~1 min
Avoid continuous or Likert-scale scoring in LLM evaluation pipelines since it obscures decision-making; force a binary pass/fail judgment tied directly to a real decision like shipping a feature.
Capability-Driven Self-Evolution of Agent Memory (PrisMem)
article · ~1 min
When iteratively improving AI agent memory via feedback, decomposing optimization into distinct capability dimensions (rather than relying on aggregate performance) prevents masking of localized improvements and enables more targeted, effective self-evolution.
article · ~15 min
Review manually.
Context Libraries for AI Agent Management
article · ~10 min
Context libraries require ongoing maintenance just like code—treat them as living infrastructure that needs periodic review, not one-time setup, and consider letting the agent itself update context to reduce decay over time.
Error Analysis Without Direct Data Access
Hamel Husain · youtube · ~2 min
Follow a hierarchy when data access is restricted—real data (even limited) > domain expert review > redacted traces > synthetic data as last resort—since each step down loses fidelity in catching actual model failures.
AI Roll-Ups: Buying Small Businesses with AI Agents
Greg Isenberg · youtube · ~11 min
The convergence of retiring owners with no succession plan, AI finally being capable enough to handle repetitive back-office work (data entry, status updates, document chasing), and widespread underpricing of this opportunity creates a window for solo founders to acquire cash-flowing small businesses and dramatically improve margins using AI agents instead of raising large funds.
Auto-flagged as cortex-relevant. Drafts get composed when 3+ items cluster around a topic and pushed to core/methodology/_drafts/ for review.
Boundary Action Auditing Against Staged Prompt Injection
article · ~2 min
Defending long-horizon AI agents requires auditing decisions at the exact boundary before each consequential action (not just screening inputs or reviewing completed runs), and tracing what data source and influence shaped each element of a pending action can reliably distinguish attacker-manipulated steps from benign ones.
Binary Pass/Fail Scoring for LLM Judges
Hamel Husain · youtube · ~1 min
Avoid continuous or Likert-scale scoring in LLM evaluation pipelines since it obscures decision-making; force a binary pass/fail judgment tied directly to a real decision like shipping a feature.
Capability-Driven Self-Evolution of Agent Memory (PrisMem)
article · ~1 min
When iteratively improving AI agent memory via feedback, decomposing optimization into distinct capability dimensions (rather than relying on aggregate performance) prevents masking of localized improvements and enables more targeted, effective self-evolution.
Context Libraries for AI Agent Management
article · ~10 min
Context libraries require ongoing maintenance just like code—treat them as living infrastructure that needs periodic review, not one-time setup, and consider letting the agent itself update context to reduce decay over time.
Error Analysis Without Direct Data Access
Hamel Husain · youtube · ~2 min
Follow a hierarchy when data access is restricted—real data (even limited) > domain expert review > redacted traces > synthetic data as last resort—since each step down loses fidelity in catching actual model failures.
AI Roll-Ups: Buying Small Businesses with AI Agents
Greg Isenberg · youtube · ~11 min
The convergence of retiring owners with no succession plan, AI finally being capable enough to handle repetitive back-office work (data entry, status updates, document chasing), and widespread underpricing of this opportunity creates a window for solo founders to acquire cash-flowing small businesses and dramatically improve margins using AI agents instead of raising large funds.
Shared Company Agent vs. Personal AI Agents
Laura Entis · article · ~8 min
When deploying AI agents in a team setting, favor one shared, continuously-learning company agent over many individual personal bots to avoid maintenance overhead and fragmented knowledge; reserve personal agents for transactional vs. relationship-based tasks at an individual level.
Forward Deployed Engineering: Monetizing AI Agent Deployment
Greg Isenberg · youtube · ~12 min
Forward deployed engineers capture outsized compensation by taking a percentage of the measurable value they create (e.g., $5-25M in efficiency or revenue gains) through AI agent deployment, rather than charging flat fees for implementation work.
Every Agent: Slack-Based AI Coworker Tool
Dan Shipper · article · ~8 min
Prompting in public (working with AI visibly in shared channels rather than private chats) helps AI workflows spread organically across a team, since coworkers can see and replicate successful prompts/skills instead of just the finished output.