Results for “engineering”

Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.

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6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

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Knowledge base from NIST SP 800-160 Vol 1 (Engineering Trustworthy Secure Systems) and Vol 2 (Developing Cyber-Resilient Systems). Use for systems security engineering (SSE): the three SSE framework contexts (problem/solution/trustworthiness), the 30+ design principles for trustworthy secure design, trustworthiness and assurance/assurance cases, security across the ISO/IEC/IEEE 15288 life-cycle process groups, and the Vol 2 cyber-resiliency engineering framework — 4 goals (anticipate/withstand/recover/adapt), objectives, 14 techniques, implementation approaches, and design principles for the APT/adverse-conditions threat model. Bridges systems engineering and the NIST security cluster (CSF/SSDF/RMF). Does not reproduce ISO/IEC/IEEE 15288 process text, nor cover SP 800-53 control catalogs in depth.

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Knowledge base from the DoD Digital Engineering Strategy (2018, OUSD/ODASD(SE)). Use for the Department of Defense's five digital engineering goals — (1) formalize the development, integration, and use of models; (2) provide an enduring authoritative source of truth; (3) incorporate technological innovation; (4) establish supporting infrastructure and environments; (5) transform the culture and workforce — plus their focus areas, the document-to-model and design-build-test→model-analyze-build shifts, model formalisms/provenance, governance and access control of the authoritative source of truth, and the coordinate→plan→pilot→sustain rollout. A vision-and-policy strategy, deliberately non-prescriptive. Does NOT provide a how-to method, tool tutorials, MBSE/SysML mechanics, or implementation-plan content; thin on metrics, acquisition-policy detail, and step-by-step procedure. Excludes the CAC-gated Digital Engineering Body of Knowledge (DEBoK).

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Knowledge base from the DoD Systems Engineering Guidebook (OUSD R&E, February 2022). Use for the DoD SE process model — the 16 SE processes (8 technical management + 8 technical) mapped to ISO/IEC/IEEE 15288, the event-driven technical reviews and audits across the Major Capability Acquisition life cycle (ASR, SRR, SFR, PDR, CDR, SVR/FCA, PRR, PCA), the Systems Engineering Plan (SEP), risk/issue/opportunity management, TPMs and leading indicators, system-of-systems and digital engineering, and the 24 design considerations (RAM, system safety, HSI, system security engineering, MOSA, supportability, etc.). Acquisition-program oriented: thin on detailed cost estimating, contracting law, and non-DoD or commercial life cycles.

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Knowledge base from NASA NPR 7150.2D — NASA Software Engineering Requirements. Use for NASA's Agency-wide software-engineering requirements: the software classification scheme (Classes A–F), the Requirements Mapping Matrix and class-driven applicability, tailoring and Technical Authority governance, the SWE-### 'shall' requirements across software management (Ch 3) and the engineering life cycle (Ch 4), the supporting disciplines (configuration management, risk, peer reviews/inspections, measurement, non-conformance — Ch 5), safety-critical and cybersecurity requirements, IV&V applicability, traceability, and the Appendix A definitions. Does not cover detailed software-assurance/safety procedures (see NASA-STD-8739.8), implementation how-to and document content (see NASA-HDBK-2203), the systems-engineering process framework (see NPR 7123.1), or program/project management (see NPR 7120.5).

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6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

The English summary is being prepared. Showing the original description.

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

The English summary is being prepared. Showing the original description.

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

The English summary is being prepared. Showing the original description.

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

The English summary is being prepared. Showing the original description.

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

The English summary is being prepared. Showing the original description.

Social engineering attack techniques beyond email phishing for authorized red team and physical penetration testing engagements. Covers pretexting methodology (persona creation, authority and urgency psychological triggers, rapport building), vishing (voice phishing via caller ID spoofing, IVR system exploitation, VoIP infrastructure setup with Twilio/Asterisk), smishing (SMS-based phishing, carrier gateway abuse, short code impersonation), physical social engineering (tailgating and piggybacking, RFID badge cloning with Proxmark3, lock picking and bypass, dumpster diving for sensitive documents), USB drop attacks (Rubber Ducky keystroke injection, Bash Bunny multi-vector payloads, O.MG cable covert implants, BadUSB firmware attacks), watering hole attack planning and execution, and OSINT-driven targeting (LinkedIn harvesting, organizational chart reconstruction, employee pattern analysis). Integrates with the Social Engineering Toolkit for attack automation, Proxmark3 for RFID/NFC cloning, USB Rubber Duc...

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Organize engineering work carried out by AI agents with clear completion criteria, small verifiable tasks, and evaluations before and after implementation. Match model choice to task complexity and track tokens, retries, time, and outcomes to manage cost.

• Planning development work for AI agents
• Splitting a large change into independently verifiable tasks
• Comparing evaluations before and after implementation

Review a week of engineering work using commit history, work patterns, and code quality measures. It tracks trends across retrospectives and breaks down each team member’s contributions, highlighting strengths and areas for growth.

• Review the week’s engineering work
• Summarize work completed during a sprint
• Reflect on each team member’s contributions

Take a ten-question interactive quiz across five AI and machine learning areas. Use the results to find a starting point in a 523-lesson curriculum, identify topics to review, and estimate the time for your learning path.

• Find where to begin studying AI and machine learning
• Skip familiar material in the curriculum
• Identify areas that need review

Learn to create, discover, invoke, secure, evaluate, package, and port Agent Skills through one interactive lesson at a time. Practical checkpoints and quizzes track demonstrated progress in a local file, so later sessions resume where you stopped.

• Learn to build and invoke a minimal Agent Skill
• Understand discovery and automatic routing
• Check permission, sandbox, and trust boundaries

Coordinate software investigations, implementation, code reviews, and testing through Codex tasks in desktop, remote, or cloud environments. Inspect pull requests and automated checks, follow up on authorized fixes, and report results with verification limits.

• Investigate bugs and implement requested features
• Review code and run relevant tests
• Diagnose blocked pull requests

Find available computers and remote environments, then start or continue a task in the requested location. Route work involving files or apps on the user's computer to that computer, and follow progress while preserving the selected environment.

• Start a task on a named remote environment
• Route work involving files on your own computer
• Select your computer for work with a desktop app

Carry out an engineering plan through stepwise code changes, dependency impact checks, tests, and focused commits. It also handles small, bounded tasks directly, checking the code relationship index before relying on its results.

• Implementing an existing engineering plan
• Making a small change across one or two files
• Testing each step before committing

Route authorized reverse engineering, security analysis, CTF challenge, and defensive testing requests to specialist skills in a local repository. This Codex adapter selects the relevant workflow and checks the task scope before target actions begin.

• Selecting a specialist skill for reverse engineering
• Starting security analysis with a defined scope
• Routing CTF challenge tasks to a suitable workflow

Plan authorized voice phishing assessments to evaluate how employees verify callers and report suspicious calls. Organize approved scenarios, record assessment outcomes, and summarize disclosure, verification, and reporting rates to review security awareness training.

• Planning an authorized voice phishing assessment
• Evaluating caller verification and security reporting
• Reviewing the effectiveness of security awareness training

Analyze suspicious Linux ELF executables through file inspection, runtime tracing, and reverse engineering. Identify malware behavior, network destinations, and persistence mechanisms, then organize findings and indicators for investigations involving servers, containers, or cloud infrastructure.

• Triaging suspicious executables on Linux servers
• Investigating suspected cryptominers
• Analyzing malware found in containers

Analyze Go malware binaries in Ghidra by extracting build metadata, function names, dependencies, and relevant strings. Use GoResolver to help recover obscured names and organize functions so analysts can focus their reverse engineering work.

• Investigating the structure of a Go malware sample
• Recovering function names from stripped or obfuscated binaries
• Identifying embedded Go modules and dependencies

Draft weekly or monthly progress updates, launch announcements, and risk escalations for specific audiences. Turn shared project information into concise leadership summaries, detailed engineering updates, or customer-facing messages with clear next steps.

• Writing weekly or monthly updates for leadership
• Sharing blockers and decisions with engineering teams
• Preparing customer-facing launch announcements