Evaluate
Map the current workflow, tools, access boundaries, delivery pressure, and operational risks.
Specialized Advisory / AI Agents / Delivery Workflows
Agentic Delivery
A customized advisory engagement for engineering organizations that want to use AI agents in real software delivery without losing control of quality, security, cost, or production responsibility.
- Customized
- Ongoing advisory
- Company-wide
- Hands-on
Advisory Premise
No single advisory plan works perfectly for every real company.
Agentic Delivery is not a fixed program. Every engineering organization has different tools, release habits, risk tolerance, product pressure, and AI maturity. The engagement starts with an evaluation, and then the advisory is adapted to the company.
01 / How It Works
From your current workflow to a safer way of working.
Customize
Choose the right depth, examples, and exercises for the developers, PMs, and systems involved.
Practice
Work through realistic agent tasks with explicit permissions, review gates, and failure conditions.
Apply
Turn the engagement into a practical workflow the team can continue running after the sessions.
Evaluation Map
Before engaging, we map the system.
Current development and delivery workflowCI/CD, release, and review processAI tools, agents, and coding harnesses already in useAccess levels, secrets, shell permissions, and security risksDeveloper and PM expectations from AI-assisted workTeam maturity, operational ownership, and production responsibility
02 / Engagement Options
Different companies need different depth.
Assessment
A one-time evaluation of your current delivery workflow, tools, and access model, with a clear agent readiness and risk map.
Ongoing Advisory
Recurring sessions that guide the organization as agent adoption matures, reviewing new tools, permissions, and incidents.
Embedded Support
Hands-on support during rollout, working directly inside your delivery process, review gates, and CI/CD pipeline.
03 / Core Topics
Practical AI agent usage for serious delivery.
The advisory focuses on the engineering reality under the headline: which combination of model, harness, permissions, tools, and workflow is appropriate for the task.
Models, providers, harnesses, and agentsPrompt rules versus technical guardrailsShell access, tools, permissions, and sandboxingGit, PR, CI/CD, and release workflowsSecrets, environments, and production safetyHuman review, accountability, and rollback thinkingCost, latency, context, and effort trade-offsWhat works in demos versus real projects
Hands-on Exercise
Bring one real workflow.
We define its permissions, success criteria, review gates, failure conditions, and rollback path together.
04 / Deliverables
Leave with something the team can use.
An agent readiness and risk map for the selected workflow.
Recommended permissions, responsibility boundaries, and review gates.
A team-specific agent workflow with success and failure conditions.
A practical checklist for testing, review, release, and rollback.
A prioritized adoption plan for what the team should try next.
05 / Engagement Format
The shape follows the company.
- Delivery
- Live, company-based sessions
- Shape
- Focused engagement or ongoing advisory program
- Audience
- Whole engineering org or a specific team
- Starting point
- One real workflow the team wants to evaluate
Advisor
Payam Saderi
DevOps and platform engineer with a long relationship with Linux, production systems, automation, and the discipline of keeping systems understandable under pressure.
The advisory connects practical AI agent use with CI/CD, security habits, operational ownership, and real delivery constraints.
About Payam06 / FAQ
Before the first conversation.
Is the engagement tied to a specific model or agent?
No. The advisory is vendor-neutral and uses the models, harnesses, and delivery tools that are relevant to your organization.
Do you need access to our source code?
Not by default. Sessions can use a representative workflow or a controlled example when source access is not appropriate.
Can we start with an assessment before committing to ongoing advisory?
Yes. Most engagements begin with a one-time assessment, and move to ongoing advisory or embedded support only if it is a good fit.
Can the engagement use our existing workflow and tools?
Yes. The evaluation exists to adapt the advisory to your repositories, review process, CI/CD, access model, and operational constraints.
Is implementation included?
The engagement focuses on advisory and workflow design. Any production implementation or longer-term engineering work is scoped separately.
Discovery Call
Start with a short evaluation conversation.
Bring one workflow your team is considering delegating to an AI agent. The first conversation is used to understand its scope, permissions, verification needs, and the right engagement depth.
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