UNCLASSIFIED. Open Brief. Surface Cut.
Don’t wait for someone to forward it.
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Field Signals
Copilot agent, now from your CLI
Trigger code tasks and PRs on demand, mid-call.
Postman adds AI requests, safer variables
Run LLM calls alongside APIs; reduce secret sprawl.
Amazon Q gets remote MCP, tangents
Securely pull Jira/PR context; explore ideas without losing thread.
🔒 Also Inside
— Playbook Drop: Vanta questionnaire automation pilot
— Benchmark: Cloudflare’s Rust proxy, faster edges
— Tool in Focus: Vanta automation, test in 15 minutes
— Role Intel: SE cover sheet that speeds SQs
Don’t wait for someone to forward it.
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🔒 CLASSIFIED. Operator Brief. Deep Cut.
Field Signals
GitHub Copilot agent from the CLI (command-line interface)
Impact: Kick off code changes mid-call; a PR (pull request) opens itself, then iterates via PR comments.
Action: Install gh 2.80.0+. Try gh agent-task create "seed demo data"; tail with gh agent-task view --log --follow.
🔗 The GitHub Blog →
Postman: AI (artificial intelligence) requests inside Collections + redesigned variables
Impact: Run LLM (large language model) calls next to REST (Representational State Transfer) and GraphQL flows; saner secret scope; MCP (Model Context Protocol) for context.
Action: Convert one workspace to the new variables model; add an “AI request” to generate fuzzed payloads.
🔗 Postman Blog →
Amazon Q Developer: remote MCP (Model Context Protocol) servers + tangent mode
Impact: Securely wire Jira/GitHub/Confluence; explore side ideas without losing context.
Action: Register a remote MCP with OAuth (Open Authorization); scope to a demo-only project; trial a tangent spike.
🔗 AWS Documentation →
Playbook Drop
Vanta questionnaire automation
Goal: Cut inbound SQ (security questionnaire) turnaround by 40%+ in one live pilot.
Prep KB (knowledge base): Export last 3 approved questionnaires + current SOC (System and Organisation Controls) and ISO (International Organisation for Standardisation) docs to Vanta’s Questionnaire Automation.
Create an SQ run: Upload the customer Excel/portal; auto-answer; flag unknowns.
Reviewer pass: Security lead reviews deltas vs past answers; lock edits.
Redlines: Use the AI review summary to surface risks and changes since prior review.
Ship: Export to customer format; store final in KB; note cycle time.
Guardrails: Enable KB verification cadence and named owners before you start.
🔗 Vanta →
Benchmark Snap
Stat: Cloudflare’s Rust-based core proxy replaced NGINX; Birthday Week data shows meaningful latency improvements on edge paths.
Provenance: Network performance deep dive, 26 Sep; “20% of the Internet” explainer.
SE (Sales Engineer) implication: Prefer live, edge-transiting demos over GIFs when routes traverse Cloudflare.
🔗 The Cloudflare Blog →
Tool in Focus
Vanta questionnaire automation
What it does
AI-assisted workflows that auto-answer customer SQs (security questionnaires), generate review summaries, and keep answers governed in a KB.
Where it fits in the SE workflow
Pre-sales: respond to SQs and the security sections of RFPs (requests for proposal) faster; keep answers consistent across deals.
Post-sale: vendor risk reviews via VRM (vendor risk management) features.
How to test in 15 minutes
Start a trial or sandbox; enable Questionnaire Automation.
Upload a redacted, real SQ (10–20 questions).
Run auto-answer; review suggested responses; export. Aim for under 15 minutes with 5 or fewer manual edits.
Pricing note
AI review summaries are part of Vanta’s VRM add-on; Questionnaire Automation is in the customer-trust bundle. Confirm plan and add-ons with Vanta.
🔗 Vanta →
Role Intel
Role: Enterprise SE (Sales Engineer), SaaS (software as a service) platform.
Context: Inbound SQ blocks a seven-figure bake-off.
Field trick: Run Vanta on the live SQ, then attach the AI security review summary as a cover sheet highlighting changes since the prospect’s last review. Reduces reviewer fatigue and speeds procurement.
🔗 Vanta →
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